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Link to Microsoft Excel-Model
In order to gain a better understanding of the following analysis and valuation, it is recommended to
consider the original excel model, which has been built in a self-explanatory manner and can be found
via the following link: https://www.dropbox.com/s/csj7ii75mvzcng7/Valuation of LHA - Master
Thesis.xlsx?dl=0
While the main findings and explanations can be found in the text, you are welcome to contact me
via e-mail with any questions or if problems with opening the file occur: [email protected]
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Abstract
The ultimate goal of this report is to provide the marginal investor with a thorough strategic as well as financial
analysis of Deutsche Lufthansa AG leading towards a recommendation whether to buy, sell or hold the
company's stock on 30.12.2016. Included in this analysis is an assessment of the credibility of current rumors
about Lufthansa's potential engagement in M&A activity with Air Berlin. As consolidation is generally
anticipated within the European airline industry, an informed assessment of the rumors' credibility is of
relevance for the marginal investor. The applied DCF-valuation model derives at an estimate of 18,41€ for
Deutsche Lufthansa AG's fair share price. As the stock is trading for 12,27€ on the valuation date, this report
suggests that the market undervalues Lufthansa's stock. The additional constructions of a best and worst case
scenario provide a potential range of share prices resembling possible deviations in estimated future growth
rates of ASKs, load factors, unit yields, fuel and staff costs. The scenarios lead to a share price of 21,19€ in
the best case and 14,10€ in the worst case. With the purpose of further triangulating the results of the present
value model, a relative valuation based on multiples suggests a fair value of 26,14€ per share. Thus, the relative
valuation supports the general tendency of the DCF, however implies a more significant undervaluation. The
current rumors about an acquisition of Air Berlin have been evaluated as non-credible due to the limited
strategic as well as synergetic fit. It is further found that a wet-lease agreement in 2016 has already provided
Deutsche Lufthansa AG with a predominant share of Air Berlin's only initially attractive assets.
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Table of Contents
Abstract ......................................................................................................................................... 1 Table of Contents ......................................................................................................................... 2 1. Introduction ....................................................................................................................... 3
1.1. Motivation behind the chosen the industry and case ................................................. 3 1.2. Aim of the report ....................................................................................................... 4 1.3. Methodology ............................................................................................................. 6 1.4. Structure of the report ............................................................................................... 7
2. Industry Overview ............................................................................................................. 8
2.1. Global Airline Industry ............................................................................................. 8 2.2. European airline industry ........................................................................................ 13
3. Deutsche Lufthansa AG .................................................................................................. 17
3.1. Corporate Overview ................................................................................................ 17 3.2. Business Model & Strategy ..................................................................................... 19 3.3. Share performance ................................................................................................... 20
4. External/internal factor analysis .................................................................................... 22
4.1. Macroeconomic Analysis PESTLE ......................................................................... 22 4.2. Industry Analysis Porter’s Five Forces ................................................................... 23 4.3. SWOT Analysis ....................................................................................................... 26
5. Financial Analysis ............................................................................................................ 26
5.1. Reformulation of Financial Statements ................................................................... 27 5.2. Historical Financial Performance Analysis (Profitability, liquidity, solvency) ...... 31
6. Forecasting ....................................................................................................................... 42
6.1. Revenue forecast ..................................................................................................... 44 6.2. Forecasting costs and balance sheet items .............................................................. 47 6.3. Best & Worst case scenarios ................................................................................... 49
7. Valuation .......................................................................................................................... 50
7.1. DCF Approach ........................................................................................................ 50 7.2. EVA & Sensitivity analysis ..................................................................................... 57 7.3. Multiple Analysis .................................................................................................... 59
8. Airline's M&A rationals ................................................................................................. 63
8.1. Introduction to M&A within the airline industry .................................................... 63 8.2. M&A motives for commercial airlines ................................................................... 64 8.3. Analysis of an acquisition of Air Berlin .................................................................. 68
9. Impact of 2016 wet lease with Air Berlin on acquisition consideration ..................... 74
9.1. Overview of deal ..................................................................................................... 74 9.2. Effect of the lease agreement on acquisition rationales .......................................... 76
10. Conclusion ........................................................................................................................ 79 11. References ............................................................................................................................ I 12. Appendix ........................................................................................................................ VIII
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1. Introduction
1.1. Motivation behind the chosen the industry and case
As airlines offer services related to the global transportation of passengers and freight, the industry is
considered one of the most influential drivers of the globalization process throughout the last decades.
Furthermore, as the industry is only part of the larger overall aviation industry, it has a general strong interlink
with multiple nation’s economies, other major industries and numerous regulatory environments. Air travel
has fueled regional and global economic growth, world trade and also tourism through increasing the mobility
of individuals and the ability of global freight shipment. Thus, the air travel and transportation industry is by
nature vast and complex, as it interlinks with multiple influential environments. The services offered drive the
global economy, the industry’s own growth, development and profitability. In consequence it is also extremely
depended on global macro-economic, social, cultural and technological developments (Stalnaker, Usman and
Taylor, 2015). A recent macro-economic development which massive attention was the universal drop of oil
prices. Between June 2014 and January 2016, the crude oil price dropped about 75% reaching an almost 15-
year low at prices below 27$ a barrel. The effects of such a developments are not only visual not on a macro-
economic level, but also for everyone in their daily lives, through e.g. cheaper petrol, costs for appliances,
increased occurrence of traffic or even long-term effects on the price of medicine. Thus, the question arises, if
decreasing oil prices have a predominantly positive effect on the economy and if not, how cheap oil can become
before it evolves into a problem?
Throughout recent history, cheap fuel and low crude oil prices have regularly functioned as a siren call to the
airline CEOs. After all, lower oil prices reduce the cost of jet fuel, which represents about 1/3 of a carrier's
overall expenses. The potential beneficial effect of such macro-economic developments can also exceed the
direct impact on a carrier's bottom line. The consequences low oil prices can have on the GDP growth and,
particularly, disposal income are potentially of much greater impact, given the importance of economic activity
as an underlying driver of traffic demand. However, externally driven short-term demand increases can also
result in unsustainable changes in industry dynamics, as flight frequencies are shifted towards off-peak periods,
resulting in a potential disadvantage for legacy carriers. Thus, the factors and trends determining an airline’s
ability to generate future revenues and profits can provide both, opportunities and concerns. Furthermore,
given the recent strong fluctuations of financial performance drivers such as e.g. fuel costs, it is questionable
if an airline's share price continuously adapts to the changing conditions and correctly reflects expected future
earnings.
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Having grown up in Germany, the airline industry is an influential factor and driver for our local economy –
especially as the globally operating aviation group Deutsche Lufthansa AG is one of our oldest, most traditional
companies. As one of Germany's thirty largest companies, the carrier is also part of the nation's leading stock
market index, and thus also a direct influence on a main indicator of the economy's financial state. While
Lufthansa resembles a successful history and presence, Germany’s second largest airline Air Berlin has
financially struggled over multiple past periods. The firm has repeatedly received financial support from its
parent company Etihad Airways, however it is questionable if this support will continue. By the end of 2016
many industry experts and aviation news databases speculated that Lufthansa would takeover Air Berlin.
However, in September 2016 the companies unexpectedly announced the agreement of a wet-lease resulting
in the transfer of multiple airplanes and routes from Air Berlin to Lufthansa. While Ryanair is currently
preparing additional complaints to Germany’s cartel authority and the European Commission, independent
news sources have ambivalent perspectives regarding the purpose of the deal. While some analysts see the
wet-lease as an alternative to M&A, through which any previous merger considerations are redundant, others
publically argue for why the deal is an initial cooperation setting the tone for a soon to follow takeover.
1.1.1. Personal interest in topic
A strategic analysis and financial valuation of a company provides the opportunity to apply theoretical concepts
of both corporate strategy and the financial world in one product. My personal interest in the combination of
exactly these academic fields has already been my main reason for choosing the FSM (finance and strategic
mgmt.) master program. Moreover, the courses of the program have provided me with precious however
separate insights into each of the economic fields. The prospect and ability of conducting a valuation has fueled
in my interest in merging the learnings of both fields in a single-target oriented analysis.
1.2. Aim of the report
This report aims to identify the true fair value of Deutsche Lufthansa AG and hence determine if the company’s
share price on the 30th December 2016 is over-or undervalued. An associated strategic and financial analysis
provides the foundation to ultimately give a buy or sell recommendation regarding Lufthansa’s share for a
hypothetical marginal investor. Several valuation approaches are used for which preceding in-depth strategic,
financial and ratio analyses provide inputs as they help in assessing Lufthansa’s past operations and act as a
foundation for forecasting the future performance of the Group. The corresponding estimate of the true value
is calculated through a Discounted Cash Flow (DCF) valuation model. Additional valuations through an EVA
model and market multiples are presented in order to triangulate the value derived from the DCF model.
Furthermore, the analysis of Deutsche Lufthansa AG's future potential performance is completed through an
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evaluation of recent rumors about the group’s engagement in M&A activity with Air Berlin. Within this
section, the most relevant potential synergies of a combined entity are identified and the credibility behind the
rumor is assessed.
1.2.1. Problem statement & research questions
The problem statement is covered by the following main research question. A catalog of sub-questions is
further created to guide the analysis and support in generating an informed response towards the main research
question.
Main research question:
“What is the stand alone fair value of Deutsche Lufthansa AG's common stock on December 30th, 2016 and
is the rumor regarding a takeover of Air Berlin credible from the perspective of a marginal investor?”
Furthermore, six defined sub-questions related to the main research question are listed below. These sub-
questions will be addressed in different sections of the thesis and will provide a basis for answering the main
research question, which mainly will be addressed in the valuation section and in the conclusion.
1. What are the internal strengths and weaknesses of the Lufthansa Group?
2. How did Lufthansa perform financially in comparison to its main competitors?
3. How does Lufthansa perform operationally in comparison to its competitors?
4. What are the general future expectations for the airline industry, and how is Lufthansa expected to
perform financially in the future?
5. How sensitive is the valuation method to changes in key assumptions?
6. Is the rumor of an Air Berlin takeover credible? How high is the strategic and synergetic potential of
Air Berlin as an acquisition target for Lufthansa and has the 2016 wet lease deal influenced this
evaluation?
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1.3. Methodology
1.3.1. Framework and theories:
The theories and guidelines followed throughout the financial statement analysis as well as the three valuation
models are derived from combining the concepts of both Petersen and Plenborg (2012) and Koller, Goedhart
and Wessels (2015). While the authors' perspectives on the fundamental theories predominantly overlap, the
differently stressed emphasizes are complimentary to one another. Furthermore, as Koller, Goedhart and
Wessels (2015) partially address the airline industry specifically, the best fitting concepts per section at hand
have been chosen. While the above books are also used as a base for the calculation of Lufthansa's weighted
average cost of capital (WACC), the main applied concepts for estimating an appropriate discount factor follow
the theories and procedures set by Aswath Damodaran - a renown author of academic and practitioner papers
on Valuation, Corporate Finance and Investment Management. The frameworks applied for the strategic
analysis are the concepts most commonly selected by practitioners and divided into an external and internal
analysis. After elaborating on Lufthansa's corporate strategy and business model, a PEST analysis as well as
Porter's Five Forces Model are applied to understand the external drivers and the most influential external
factors of the airline industry. Subsequently, the display of a SWOT framework summaries and structures all
main findings of the strategic analysis. In order to identify the potential of Air Berlin as an acquisition target
company for Lufthansa, the carrier's attractiveness is analyzed in light of Merkert and Morrell’s (2012) six
main rationales for M&As within the airline industry. Overall, reasons behind the use of selected frameworks
are only explained if evaluated as necessary to understand the flow of this report and are otherwise treated as
self-explanatory.
1.3.2. Data collection:
The conclusions of this report are drawn upon extensive research, in which sources are analyzed, cross-
checked, aggregated and presented in a consistent and accessible manner. Preparatory research is based on
search through databases of news, analyst commentary, company profiles and macroeconomic as well as
demographic information. Most figures and materials used in relation to the financial performance of the
companies included in this report has been retrieved from the respective annual and quarterly reports. Despite
the theoretical risk of data manipulation by the respective entities as these are inclined to overstate their
performance, this hypothetical bias is assumed to be trivial. As all companies included in the analysis are
publically traded, the legal obligation and IFRS standardization of accounting principles are trusted to inhibit
manipulations. Among practitioners it is also common to gather necessary statistical data from independent
sources as capital IQ, Bloomberg, Reuters, etc. While these independent sources provide less incentives for
dishonesty, the presented figures are sometimes subject to opaque adjustments in the calculations.
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Nevertheless, especially for the relative valuation of Lufthansa, the effect on retrieved market multiples is
assumed to be negligible. The financial ratios and fundamental calculations of the discounted cash flow
valuation model are all based on the self-created analytical income statements and balance sheets.
1.3.3. Assumptions
Prior to the analysis a few guiding and restraining assumptions need to be set in order to concentration the
focus of the analysis on the core as well as critical issues, rather than minor matters. In general, this report
assumes readers are knowledgeable about the common theories surrounding economics, corporate strategy and
principles of valuation. Thus, while the implications of common concepts are seen as self-explanatory,
clarifications are provided when reasons seem necessary. As minor assumptions are needed throughout each
section of this report, these are referred to when appropriate. A few general assumptions regarding the overall
analysis are:
• This report is solely based on public data and has been created from the perspective of an external investor.
• Proprietary information from neither Lufthansa nor Air Berlin is needed to replicate the findings.
• As this thesis is written from November 2016 to mid 2017 the cut-off date of this thesis is December 30th,
2016. Any further news or information published after this date is neglected and treated as non-existent.
• Accordingly, the valuation date is also set to the 30th December of 2016, on which the share of Deutsche
Lufthansa AG had a closing price of 12,27€.
• The historic analysis is based of the most recently available full 5 fiscal years of data. As Lufthansa
publishes annual reports in March/April, this thesis' research is based on annual reports up to and including
the 2015 annual report. Thus the year 2016 is included as the first year of the forecasted period.
1.4. Structure of the report
This thesis is structured into four main sections. The first section serves as an introduction to the airline industry
as well as the Lufthansa Group. To get a better understanding, first the global airline industry as a whole and
subsequently the European airline industry is investigated in terms of its main players, performance, trends
and future outlook. The second section comprises an assessment of Lufthansa's strategic as well as financial
positioning relative to its peers. In this chapter the external as well as internal drivers of performance are
outlined. The third section builds upon prior results and elaborates on the forecasting as well as discounting
procedures of Lufthansa's operational and financial future performance. After deriving at an estimated fair
value of the company's share, the rumors surrounding an acquisition of Air Berlin are further investigated,
followed by an assessment of their credibility for a marginal investor in the Lufthansa share.
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2. Industry Overview
2.1. Global Airline Industry
The development of air travel over the past 20 years has been extremely successful, resembling an average
annual growth rate of around 5%. The most recent period from 2011-2015 has been one of the strongest with
as the industry has grown consistently at a rate of 5,2%. The strong growth after the financial crises has been
mainly fueled by increased flight frequency as well as technological developments continuously enabling
carriers to safely operate larger airplanes. In 2015, the industry volume reached 3,3bn traveling passengers.
Through the provision of these services the air travel is estimated to create employment for 9,9mn people and
contribute 664 bn$ directly to the global GDP (ATAG, 2016a). Additionally, services provided by air
transportation fuel growth in many related industries, some of which are the operations of key fuel suppliers
or infrastructure and airport construction companies. Thus, the airline industry's GDP contribution is
commonly presented in both direct and indirect terms, measuring about 0,8% directly and 3,5% indirectly
(ATAG, 2016a). In perspective, air travel has about half the global economic contribution compared to the
financial services industry, however is larger than both the automotive and the chemical industry, which are
estimated to have shares of about 1,2% and 2,1% respectively (ATAG, 2016b).
Discretionary income developments as well as current events such as currency shocks and air plane crashes
have historically shown similar impacts on the global economy as well as the demand for air travel. As the
relation and interdependence of the two is undisputed, global and regional GDPs often serve as the most
accurate benchmarks for measuring the state and performance of the industry (Boeing, 2015). In terms of
measurement, ASKs (available seat-kilometers) are commonly used as the preferred indicator of industry
growth, as it describes the total capacity offered to consumers.
Figure 1: Value of the global airline industry (2011 - 2015) Source MarketLine, 2016a; own depiction
Marketdevelopment bygeographyMarketdevelopment
+7,3%
2011
525.750
396.041
NorthAmerica
136.004
2011
168.654
+5,5%
2015
Middle East
Europe
20152011
28.110
+11%
42.735
X% =CAGR
(measuredinmillionrevenueUS$)
2011
+5,3%
94.932
2015
116.895 Asia-Pacific
+9,6%
176.691122.298
20152011
(measuredinmillionrevenueUS$)
2015
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In terms of revenue, in 2015 players within the airline industry generated about €525bn globally. As shown in
figure 1 above, this represents a CAGR of 7,3% when measured on the basis of 2011. The driving market in
achieving a high global growth has been Asia Pacific. With a CAGR of 9,6%, the region has developed to the
largest revenue market, surpassing North America which grew 5,4% year-on-year sine 2011 (Market Line,
2016). Compared to the growth of economies, appendix 1 shows that ASKs growth has significantly
outperforming the GDP on a global and regional level. Thus, the capacities offered in all major geographical
sectors have grown faster than respective GDP expectations. While this may seem natural for markets in
developing regions, the industry also outperformed GDP growth prospects in mature markets. With every
major geographic region displaying at least an ASK growth of 4,3% the highest rates have been achieved in
Africa/Middle East and Asia/Oceania with 10,3% and 8,4 % respectively (Stalnaker et. al., 2015).
An interesting observation is that while ASKs increased by 6,3%, actual available seats rose by 5.5% and flight
frequency only grew by 3.1% (Stalnaker et. al., 2015). Taken together, these three measurements point towards
a clear efficiency trend within the airline industry. These rates further point towards two additional
observations: First, aircrafts are either becoming larger and capacity is offered more densely. Second, airlines
are tending to fly longer distances.
Regarding competitiveness, rankings of the largest players can strongly differ if size is measured by total
revenue, ASKs, revenue per kilometer (RPKs) or transported passengers. Rankings can additionally differ, if
individual airline brands or corporate groups are considered as players. However, regardless of measurement,
the most carriers within the Top 15 originate from the US, with individual airlines from Europe, the Middle
East and Asia following. As figure 2 shows the leading airline brands based on December 2015 RPKs, we can
see that the market is led by the US-based carriers, American, United and Delta Airlines, followed by Emirates
and a group of European carries including KLM, IAG and Lufthansa.
Figure 2: Leading airlines worldwide in December 2015, based on revenue passenger kilometers (in billions) Source: Statista 2016; Own creation
29,527,6 26,3
22,6
18,57 17,5516,1 15,2 15,1 14,2
12 10,8 10,6 9,7 9,6
0
5
10
15
20
25
30
35
reve
nue
pass
enge
r kilo
met
ers
(RPK
s)
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One reason for the dominance of US carriers is the size advantage of the home market. As airlines usually
originate and grow out of their home market, domestic demand is of essential importance. As depicted in figure
2 above, around 60% of all scheduled flights in 2015 have been recorded as domestic. Further sources state
similar measurements, as it has also been reported that about 58% of the 3.314 million passengers in 2015 flew
domestically. While Europe as a whole is size wise comparable to North America, the individual countries are
only fractions. Thus, while US based carries of course also play an important role internationally, their overall
high ranks stem from a large domestic market.
2.1.1. Major impacts to global airline development
Through enabling the connection of buyers and sellers globally as well as transporting goods across borders,
players within the airline industry are some of the most internationally operating companies of the world. As
the external environment of any business is impactful of the respective operations, the nature of the airline
industry makes players uniquely effected by current events such as terrorism, oil price changes or currency
fluctuations (Boeing, 2015). Especially the oil price development and recent terrorist attacks have had
tremendous effect on the industry, due to which role and impact of these developments is shortly specified.
Oil price:
The movements in oil prices are commonly known as volatile and very hard to predict. It's significance for the
airline industry, as one of the main cost drivers, makes it one of the most important macro-economic factors
for the operations of all players. While 2014 was a year of unfavorable oil prices for airlines, fuel costs across
the industry added up to a combined total of $226bn. Subsequently, price dropped to 40$-a-barrel by year-end
2015 - the lowest since 2009 - causing a respective 20,5% decline in airlines fuel costs. However, despite
prices at a significant low, further reductions in the industry wide average fuel costs are expected for 2016
(Iata, 2015a). Such developments benefit not only airline companies cost COGS, but also consumers.
Throughout the year, many airlines saw themselves forced to pass on savings in relation to the oil price
reductions in form of cheaper tickets. Unfortunately, these actions also resulted in industry wide revenue
reductions of roughly 6% from $758bn in 2014 to $710bn in 2015 (Iata, 2015a).
Due to the significance as a main cost driver as well as the natural volatility of the commodity, airlines
commonly protect themselves from the impact of price movements through the use of various hedging
strategies. Most commonly, companies either establish contracts with suppliers securing fixed future prices,
or acquire call options to execute for lower spot prices in the future (Iata, 2015a).
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Figure 3: System average fuel price (US Carriers) and fuel spot price 2009 – 2015 Source: Stalnaker et. al., 2015
Nevertheless, hedging strategies are not solely beneficial. While these strategies protect airlines from volatility
and especially sudden sharp increases in the price of crude oil, such strategies also dampen potential benefits
if prices decrease. Figure 3 compares the jet fuel spot price with the average cost payed by US airline carriers
over a time period from 2009-2015 (Stalnaker et. al., 2015). Despite the fact that the recorded system wide
fuel prices only include US carriers, the figures and the resulting hedging effect are assumed to representative
for the overall industry. The two main undesirable oil price characteristics are generally volatility and overall
price height. Measured from 2013 to mid-2014, price volatility was measured as low, as oil prices remained
on a relatively stable level. The low volatility and the stability of major cost elements, enables more accurate
forecasting and simplifies decision making.
Yet, low volatility is not the most beneficial oil price characteristic, as experienced after September 2014.
System wide fuel prices averaged almost 20% above the market spot rate, as the sharp decrease in oil price
could not be exploited due to hedging strategies (Stalnaker et. al., 2015). Additionally, as mentioned above,
industry wide revenues declined due the decrease in unit yields. However, despite these developments, the
industry's profit margin doubled in 2015 reaching 4,3%, resulting in an industry wide profit increase from
$17,3bn to $33bn. Thus, despite the uncertainty in decision making, realizing hedging losses and experiencing
overall revenues declines, 2015 and 2016 have been favorable years for the airline industry. Accordingly, for
airline executives low fuel prices seem preferred over stabile, but high ones.
Plane crashes and the risks of terror attacks:
In terms of other macro-economic factors, 2015 was also overshadowed by two high-profile air plane disasters
- both reaching wide spread publicity, partly because the number of victims exceeded 370 people. The first of
which was the deliberate crash by a Germanwings A320 co-pilot and the second caused through a suspected
bomb on board a Metrojet A321 (Smith, 2016a). The year 2016 has in contrast been recorded as one of the
safest in history (Smith 2016b). While fatalities like these are by nature devastating events, it is common that
0
1
2
3
4
US$
per
gal
lon Fuel spot price
System average fuel price
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implications on companies involved are neglected by the public. Though, as both the world economy and the
global demand for flights are sensitive to such events, such events can have severe effects on the short- and
long-term demand of the airline industry. The main reason for the industry's vulnerability to such events lies
in the asset structure. The majority of a carrier's assets is by nature fixed and composed mainly of a small
number of highly expensive elements, such as the actual aircrafts themselves. Thus, players are unable to
respond to sudden demand decreases leading to oversupply and inefficient operations (Boeing, 2016).
2.1.2. Regional Performance
Following two subsequent years of increasing profit margins, air travel experts have optimistic expectations
regarding the short term future of the industry. In late 2016, Iata (2016) announced an expected increase in net
profit for 2017, reaching $29,8bn. This implies an overall profit margin of 4,1%. Thus, airlines' 2017
consequential expected rate of return on investment will exceed the average WACC for the third time ever in
history - following the two previous years (Iata, 2016).
While profits above the WACC are normal for most businesses, achieving these levels is a first for the airline
industry and a result of high level restructuring. Most strikingly is however that essential regional differences
in profits exist. The overall positive result is mainly due to the strong performance in the US (Iata, 2016).
Reasons for the variations in performance of the major geographical regions and especially the European
market are manifold. As the succeeding section deep dives into the specific characteristics of the European
airline industry, a quick overview of remaining region's key stats is provided.
North America: Driven by the US, North America has historically been the largest and most profitable region
for airlines. As the market has matured, the industry was led in 2015 by few very large players to an overall
net profit of $19,4bn. While the decrease in oil prices in 2015 resulted in increased profits across all regions,
the achieved average margin of 9,5% by North American airlines is regardless the highest globally.
Asia Pacific: Displaying the highest of all growth rates in 2016, the Asian Pacific market has caught up to
North American in terms of market volume. Furthermore, strong growth rates in the short-term future are
expected, as household incomes continue to rise and access to traveling is provided to an increasing part of the
population. However, overall technological shortcomings present a major hurdle for the industry as it is still
considered a rather developing than mature region. Though, while recent attempts fostering developments of
new airline models and progressive liberalization have shown success in closing the gap to mature markets,
the regions already intense competition has further been fueled - pressuring profit margins (Iata, 2016).
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South & Middle America: The south and middle American aviation markets have developed significantly
throughout the last decade. As urbanization has made the region more attractive for global carriers, it has
gained in connectivity to markets such as Europe and the US. As a trend towards tighter partnerships of South
and Middle American based carriers with global operators can be observed, many analysts expect consistent
above average traffic growth throughout the upcoming decade (Aviation Voice, 2016).
Middle East: Throughout the past decades, state-owned and subsidized Gulf carriers have gained increasing
global recognition. In 2016, 46,9% of the regions departure seats have been measured to belong to one of the
regions 4 largest airlines, implying a rather consolidated competitive environment. However, the region's
aviation market also holds new threats for the upcoming future. While, international players are gaining access
to the market, uprising competition by LLCs is simultaneously on the verge to making the market much more
price competitive. Furthermore, as the regions players are maturing and the market has grown to internationally
recognizable size, airports are gradually increasing fees and charges, potentially diminishing future profit
expectations (Iata, 2016).
2.2. European airline industry
While analysts have optimistic expectations for the European aviation market's future, the region is
characterized by high competitiveness and low profitability. With 237 recorded airline groups operating in
2016, Europe has 38% more carriers than North America, 14% more than Asia Pacific. Thus more carriers
operate in Europe than any other region in the world, despite the fact that there are only 20% more seats than
in the US and even 18% less than in Asia Pacific (Capa, 2016). A common explanation for these observation
often lies within the number and size of various small European countries. E.g. Germany and France are
commonly considered separate markets due to their cultural differences, hence "domestic" flights are in general
much shorter than in North America. As average distances are much shorter, aircrafts tend to be smaller and
airports denser, enabling more players access. Nevertheless, the extreme discrepancy in ratios regarding the
number of operating carriers to departure seats in comparison to the North America and Asia Pacific indicates
that too many airlines operate within Europe.
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Figure 4: Top 20 European airlines Source: Centre for Aviation (2016); own depiction; Sample period: Departured seats between 30-May-2016 to 5-Jun-2016
Figure 4 shows that 49% of the market is divided among Europe's leading six airlines. In comparison, the same
market share is reached in the Middle East through four carriers. Measured on the sample of departured seats
in a selected a week in mid-2016, the leading airline groups are Lufthansa, IAG, Air France-KLM, Turkish
Airlines and EasyJet. These six carriers stand out, as there is a 20% market gap separating them from the
seventh largest carrier. It is important to note that in this sample, both individual airlines such as Air Berlin as
well as carrier groups such as Lufthansa and IAG are counted as one. While the Middle East may not be the
most comparable market for Europe, comparisons to other geographical sectors highlight problems of the
European market even more. In North America 72% of market share is owned by the leading five carriers. An
additional indication of the competition within regions lies within the final 10% market share. While 190
European carriers split the tail of the final 10%, only 156 in North America, 158 in Asia Pacific and even less
than 100 in remaining geographical sectors split these allocations (Capa, 2016).
However, while the number of players by itself does not define market concentration, it still seems to be a
reason for the low profitability of European carries' in comparison to the North American and Middle Eastern.
A common measure in determining the degree of market concentration is the Herfindahl-Hirschman Index
(HHI). The index is calculated by summing the squares of all of an industry's player's market shares. The
results can range from 0 to 10.000, as the upper boundary is reached when there is only one player in the
market with 100% market share and the lower boundary is hypothetically for when there are infinitely many
companies each with a market share close to 0%. Consequently, the higher the HHI for a specific industry, the
higher also the concentration of market power and the low the degree of competition.
- 1.000.000 2.000.000 3.000.000 4.000.000
49% Top 6
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Figure 5: Herfindahl-Hirschman Index by region Source: Capa - Centre for Aviation (2016); own depiction
Figure 5 shows regional HHI figures provided by Capa Centre for Aviation (2016), measured in 2016 based
on departured seats per airline. Score benchmarks introduced by UK-based CMA (Competition and Markets
Authority) state that industries and markets which receive a HHI of above 1.000 are generally seen as
concentrated. Accordingly, only the North American aviation market is considered concentrated and all
remaining markets are classified as fragmented. Europe's score is about a third of the North American and half
of the Middle Eastern, strengthening the observations from before.
As it seems that European carriers' lack of profitability could stem from the different level in competition it
experiences compared to North America, figure 6 below combines the received HHI data with estimated 2016
regional profit margins provided by Iata (2015a). The included trend line indicates, that while the European
market generally resembles satisfactory profit margins, airlines could if benefit through consolidation.
Figure 6: Regional forecasted 2016 profit margins vs HHI Source: Capa - Centre for Aviation (2016); Iata (2015b); own depiction
NorthAmerica
1215
X =HHI
Latin America
742
Europe
487
Africa
400
Middle East
889
AsiaPacific
341
-2%
0%
2%
4%
6%
8%
10%
0 200 400 600 800 1000 1200 1400
Netp
rofitm
argin2016E
HHI
Europe
NorthAmerica
AsiaPacific
LatinAmerica
MiddleEast
Africa
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According to analysts, the difference in market characteristics between North America and Europe can be
reasoned in multiple ways. Firstly, LLC sector in Europe seems to be tougher and more developed than in the
US - pressuring unit yields and margins stronger. LLCs are also increasingly altering products as well as
distribution channels in order to better target specific customer groups (Capa, 2016). Secondly, the European
Commission states that mirroring the US market structure and level of concentration is not their goal as Europe
tends to favor a consumer rather than a corporate friendly structure. While higher concentrated allows players
to earn higher profit margins, consolidation also happens at the expense of consumers, as unit yields and ticket
prices generally rise significantly.
Regarding the intercontinental markets of Europe, the individual domestic markets seem to show a similar
situation. Displayed in figure 7, the European aviation industry can be split into 5 main markets collectively
accounting for 60% of the traffic value. The remaining 40% are split among all other countries, each accounting
for less than 7%. The two largest markets in terms of share of value are Germany (16%) and UK (14%),
followed by Spain, France (both 11%) and Italy (7%). In regards to this thesis, the German market is of especial
interest, as both Lufthansa and Air Berlin operate originate there.
Figure 7: Segmentation of the European and German airline market MarketLine, 2016; Frommberg, 2016; German Aerospace Center, 2016; own depiction
The German domestic market is clearly dominated by the Lufthansa Group. As the 3 leading airlines combined
hold a market share of 59%, two of these brands are wholly owned by the Group. Counted together, Lufthansa's
share of seats within the German market adds up to 46%, almost 4 times as much as the second largest player
Air Berlin with 13%. However, as not all the airlines stand in competition with each other. The LLC segment
34%
13%
12%
6%3%3%
30%
Lufthansa
RyanairEasyjetCondor
Others
2016
100%
59%
Top 3
Europe split by country Overall German market German LLC sector
Eurowings
Air Berlin
Ryanair
EasyjetWizzOthers
2016
100%
Germany17%
UK14%
Spain11%
France11%
Italy7%
Others40%
(2015, split by value in bnEUR)
82%Air Berlin
Eurowings
Projected split of seats end 2016
Top 3
Split by departures in July 2016
35%
34%
13%
7%2%
9%
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has experienced tremendous growth throughout the past decade, reaching a share of 28% of the entire German
aviation market in 2015 (German Aviation Center, 2015). As the Lufthansa group has only recently entered
this segment, it does not hold high market shares since long. Since multiple restructurings initiatives and
rebrandings, the group has defined its subsidiary Eurowings as the sole player within the LLC segment.
Overall, the leading 7 carriers within the German LLC segment hold a combined total of 95% of the market.
While the number of players competing is much less, the competition among them is much stronger. Based on
figure 7, Air Berlin and Lufthansa are the two largest players within the market. As the two largest players in
both the LLC segment as well as in the overall market, their relationship is impactful for the competitive
structure of the market both the overall German as well as the European market. Thus, figure 7 additionally
builds the basis for the analysis of the 2016 wet lease between both carriers - examined in chapter 8/9 of this
thesis.
3. Deutsche Lufthansa AG
3.1. Corporate Overview
Deutsche Lufthansa AG is a holding company and one of the most complete aviation groups in the world.
Commonly only recognized as the passenger airline brand, the group operates in almost all segments of the
aviation sector with stakes in over 500 subsidiaries and equity investments. In terms of passengers carried the
airline is the largest in Germany and one of leading players across Europe and the globe. Since its first
departured flight in 1955, the company has grown to a group of airlines collectively operating 600 aircrafts
and employing around 120.000 people, making the company one of Germany’s largest employers (Lufthansa,
2016). Due to this national importance the carrier had been state owned throughout the majority of its history
and was privatized only in 1994 (Blüthmann, 1994). Nowadays publically traded, Lufthansa's share is owned
to 53,9% by institutional investors and 46,1% by individual stock holders. As one of Germany's 30 largest
publically traded companies it is included in German leading index DAX since its establishment.
Since 2012 the company has been repeatedly in the news due to ongoing conflicts with worker unions and
strikes of pilots. The conflicts with the pilot's unions surround conflicts such as wage agreements as well as
retirement benefits. Since then pilots have gone on strikes 29 days, causing an estimated 14.900 flights with
1,8m passengers to be cancelled. Due to flight cancelations, Lufthansa's estimated financial loss is about €10-
15m per strike day, not including reputational damages (Stanek, 2016).
The groups CEO is former pilot Carsten Spohr, who took over in 2014 after Lufthansa had been facing financial
and competitive challenges. In the year of his introduction, Mr. Spohr pushed through a new corporate strategy
based on a group wide innovation campaign and international expansion of the company’s low-cost
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subsidiaries - Germanwings and Eurowings. To the time, the carriers had a fleet of 60 and 24 aircrafts,
respectively. The first major challenge arose in March 2015 as a Germanwings pilot deliberately crashed an
aircraft. As mentioned above, the crash was one of the worst events in the group's history and had sever effects
on both the company and the entire industry. Few months after the crash, the group announced a rebranding
of all Germanwings vehicles into the Eurowings brand. While the company states that a merge and rebranding
of the two subsidiaries was already planned and to be completed irrespective of the crash, analysts assume that
the reputational loss has nevertheless accelerated the process (Schlappig, 2015). Accordingly, since then
Eurowings is planned as the group's sole low-cost carrier. While the LLC plays an important role in the
company's transformation strategy, Lufthansa further has operations in almost all segments of the aviation
industry. Thus, figure 8 below shows the division and the respective revenue shares of the group's main five
business segments: Passenger Airline Group, Logistics, MRO, Catering and Others. Others, comprising mainly
group functions as well as financial companies.
Figure 8: Lufthansa's business segments and respective share of revenue Source: Lufthansa Annual report (2016); own depiction
Lufthansa's Passenger Airline Group segment resembles the activities most commonly associated with an
aviation company. With 74,3% of the revenues, the segment is the backbone of the group and the main driver
of growth. Including the airlines already mentioned - Lufthansa, Germanwings and Eurowings - the Passenger
Airline Group is completed with SWISS and Austrian Airlines. Further equity interests are within Brussels
Airlines, which is expected to be fully taken over in early 2017 and SunExpress. Altogether, Lufthansa's
Passenger Airline Group follows a multi-hub strategy with core locations in Frankfurt, Munich, Zurich and
Vienna and provides services through a route network connecting 297 destinations in 89 countries (Lufthansa,
2016).
Lufthansa's Logistics segment is the group's smallest business segment with EUR2,4bn generated in 2015 -
representing a total revenue share of 7,3%. The main companies included in this segment are the leading freight
airline Lufthansa Cargo, the container management specialist Jettainer Groupan and AeroLogic GmbH.
Through these, a variety of airfreight solutions are offered, most of which are based out of a specialized
MRO: 10,2%
Catering: 7,4%
Logistics: 7,3% Others: 10,2%
Passenger Airline Group: 74,3%
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infrastructure at Frankfurt Airport and reach up to 300 destinations globally. Due to proximity, the segments
main markets are Germany and the rest of Europe, in which about 50% of the segment's revenues are generated.
The business segment MRO comprises all operations regarding the maintenance, repair, and overhaul of other
civilian commercial aircrafts. The business segment is the leading independent MRO provider as it fully owns
31 operators globally and has additional 54 direct and indirect company stakes. Through this portfolio of MRO
specialists, services to both the Lufthansa Group and further independent international airline carriers are
offered. In 2015 the segment generated €6bn in revenues, €1,8bn of which came from within the group and
66% originated in Europe.
The business segment Catering generated €3bn in 2015 through offerings of the main parent company LSG
Lufthansa Service Holding AG and its 155 globally operating subsidiaries. Similarly to MRO, the segment
provides services to both Lufthansa itself (21%) as well as other unrelated airlines (79%). Through
continuously extending to the product offering and expanding the geographical presence, the segment grew
almost 15% in revenues and has established operations at 211 airports in 50 countries (Lufthansa 2016).
3.2. Business Model & Strategy
As the passenger airline group contributes 74,3% of the group's revenue and is the backbone of Lufthansa's
operations, the group's overall strategy focuses to a large extend on this business segment. While each of the
remaining business segments also have own operating strategies, the following analysis will solely concentrate
on Lufthansa's core passenger airline business.
After the inauguration of a new CEO in 2014, Lufthansa emphasized the focus on its overarching goal to be
the number 1 choice in aviation for customers, employees, shareholders. Accordingly, the corporate strategy
Mr. Spohr introduced is called “7to1-Our Way Forward” - articulating the seven key fields of actions, which
have been identified to assist the objective of becoming a global leader. These fields of action include elements
such as innovation and digitalization, customer centricity & quality focus, consistently improving efficiency
and four more. Appendix 2 shows a visualization of the strategy, in which the operational fields of actions aim
to strengthen the market position, financial stability as well as the age of fleet - the levers through which the
fields of action have influence on the overall goal. In order to achieve this mission, the company is built upon
three main pillars: premium hub airlines, Eurowings group and aviation services (Appendix 3). With this
structure, Lufthansa consolidates all non-passenger-airline activities under one pillar and divides its passenger
airlines according to the market structure into hub and low cost carriers.
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Brand portfolio: Through the diverse brand portfolio, Lufthansa has been able to cater to different market
segments, which has fueled the positive financial development for 2015 and the beginning of 2016. Lead by
Lufthansa as the largest carrier, SWISS and Austrian complete the groups premium hub airlines. The
companies pursue on a product differentiation strategy, focusing on the customer experience and integrated
route network and personalized offers. With these qualities, Lufthansa's hub airlines aim to serve the large
population of high-quality customers within the respective home markets Germany, Switzerland and Austria.
In light of recent developments, most investments and available capital is allocated to the LLC sector, due to
which Eurowings is of especial importance. Since the rebranding of Germanwings in 2015 and the
establishment of Eurowings as the group's sole LLC carrier the respective fleet has grown significantly.
Lufthansa plans to grow this business segment both organically as well as through acquisitions. Most recently,
it has been articulated that Eurowings shall become the third largest provider of point-to-point flights in
Europe, due to which the group announced in late 2016 that it will fully acquire Brussels Airlines and
additionally charter 40 airplanes from Air Berlin - both deals to go it effect as of 2017.
3.3. Share performance
3.3.1. Peer Group
As Lufthansa is one of the most complete aviation companies globally, the peers selected for this report have
been chosen due to individual reasons: First, KLM and IAG are included, as main European competitors. Both
are large European premium hub carriers and similar to Lufthansa's core business and largest brand. The three
companies have continuously battled for the leading share of market (Euromonitor, 2016) and hence are
considered the core of the peer group. Secondly, Delta is included as one of the leading global airlines and
third largest in the world. The North American based player mirrors Lufthansa's global exposure, business
diversity and is also considered of relatable size. Thirdly, Air Berlin is naturally included being second largest
German carrier, main competitor in Lufthansa's domestic market and of relevance for this report due to the
M&A analysis. Lastly, Ryanair completes the group as the company is currently the figurehead of LLCs and
main competitor of Lufthansa's Eurowings branch, a central business pillar of Lufthansa's strategy looking
forward.
3.3.2. Indexed comparison
The stock of Deutsche Lufthansa AG (LHA:Xetra) is traded on the exchanges Frankfurt, Stuttgart, Munich,
Hanover, Dusseldorf, Berlin, Hamburg and Xetra. As one of Germany's 30 largest publically traded companies,
the share is included in the DAX. With a 2016-year-end share price of €12,27, Lufthansa had a market
capitalization of €5,8bn. Figure 9 below shows the company's performance throughout 2015 and 2016, relative
to its peers as well as the DAX. The comparison is made based on daily closing stock prices extracted from
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Bloomberg. After calculating daily returns and adjusting for the peers' stock market's differences in holidays
(English, French and American), all figures have been indexed to 100. In addition, Appendix 4 and 5 show
Lufthansa's one-year relative performance for 2015 and 2016 respectively and Appendix 6 shows a comparison
of only European carriers over 2015 and 2016.
Figure 9: Performance of the Lufthansa share 2015-2016 relative to peer group and DAX; indexed 01.01.2015 Source: Bloomberg; own depiction
One of the most obvious observations in figure 9 is the airline industry's volatility. Similar to its peers,
Lufthansa's returns over the last two years include many fluctuations, both high and low. Looking at the 2
depicted years individually, Lufthansa increased its share value throughout 2015 by 5,3%, followed by a
decline in shareholder return of 12,3% in 2016. The company's performance ended below the its initial
benchmark, strongly outperformed by both the DAX as well as the North American carrier Delta Airlines.
While this would resemble a very negative development for companies any other industry, Lufthansa's
performance relative to its European peers has been above average. This is because these two years
incorporated multiple striking geopolitical events, which effected especially the European airline industry.
Lead by negative future expectation caused by the Brexit decision in 2016, multiple terror attacks in various
European cities resulted in decreased demand for both intercontinental leisure travels as well as long-haul
flights from Asia and the Americas. In light of these developments, Appendix 6 provides a comparison of
solely European carriers, indicating that only Lufthansa Ryanair and IAG had strong relative performances.
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4. External/internal factor analysis
4.1. Macroeconomic Analysis PEST
In terms of performance, many factors influencing a company's decision-making are outside of its direct
control. Hence, a determining factor for accurate forecasting as well as for the valuation as a whole, is an
understanding of key value drivers and most influential external factors. In the case of Lufthansa, the most
relevant influential factors are the oil price development, terrorist attacks and conflicts with worker's unions.
As these points have all been discussed above, the following will highlight some selected additional factors of
the group's external environment. In order to do so, the PEST framework is considered to be the most common
among practitioners, as it covers political/legal, economic, social/cultural and technological aspects and
therefore covers the most influential aspects of companies' external environment.
Political: The political environment regarding the operations of passenger airlines is highly regulated due to
their strong interlink with local economies and the paramount focus on passenger safety. Demand for air travel
is strongly intertwined with determining factors of local economies such as discretionary income. Furthermore,
for all larger carriers, home markets play an important role, as these are usually the origins of growth. Hence,
as governments generally aim to strengthen the local economy, they consequently tend to support local airlines
through preferential rights. Some of these are expressed through selective allocation of airport slots, as
governments tend to have large stakes and governing roles at local airports. Nevertheless, especially the
European market has a strong deregulation of the industry's supply side, promoting intense completion. In
these markets, the political environment tends to favor consumer amenities and low prices over corporate
profitability welfares.
Economic: The economic environment is often regarded as the most crucial source of external factors to airline
companies. As some of the most globally operators, airlines have especial dependency on national growth and
currency exchange rates. As especially LLC play pay particular attention to operating costs due to their small
profit margins, the ongoing global economic slowdown has been troublesome for many players. Current
economic challengers for carriers are declines in passenger traffic, decreasing national growth rates, labor
demands, and soaring maintenance as well as operating costs (MarketLine, 2016). The impact of these
influences have spread predominantly in the North American market, resulting in players seeking to leverage
efficiency through consolidation.
Social/Cultural: The social environment has strongly changed with an emergence of the Millennial generation
and the increasing drop of baby boomers as customer groups. The development has fueled a shift from business
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class customers with large spending power to much more cost conscious ones. It has also lead towards
passengers traveling increasingly for leisure and less for business purposes. Thus, while the general customer
places more value on entitlement and has increasing demands in terms of service, airlines are faced with the
challenge of balancing costs with increasing service requirements.
Technology: Technology is a very apparent aspect throughout almost all operations of airlines, ranging from
efficiencies in security checks, to the aircraft itself and also developments in baggage claim. However, due to
the recent social developments, technological investments are currently concentrated solely in two areas.
Firstly, increasing the efficiency of aircrafts and secondly, improving customer facing functions such as mobile
technologies, digital target advertisements, ticketing, distribution, and customer service.
4.2. Industry Analysis Porter’s Five Forces
With the purpose of complementing the internal strategic analysis and further providing an in-depth view on
the external environment effecting Lufthansa, the following section provides an analysis of the main factors
driving the competitive landscape of the airline industry. According to Grant (2013), the intensity of
competition within an industry is one of the main determinants of a player’s potential profitability. A widely
accepted framework among practitioners and economists is Michael Porter’s Five Forces model, which
emphasizes the following five elements: The threat of new entrants, the threat of substitute products, the
bargaining power of buyers, the bargaining power of suppliers and the overall competitive rivalry within the
industry (Porter, 1979). In regards to Lufthansa’s business model and despite the company’s operations within
multiple sectors, the focus of this analysis will solely be on passenger transportation, as this segment is with
74,3% (figure 8) revenue the main driver of Lufthansa’s business.
Industry Rivalry: Over the last decades, the increasing growth of low-cost carriers is clearly one of the main
drivers of competition with in airline industry. LLC players have established themselves and gained relevant
market shares especially within the North American and European aviation market. As the low-cost sector
mainly focus on short-haul routes, most full-service providers have by now already seen themselves forced to
establish LLC subsidiaries themselves, in order to protect their representation within the extremely important
domestic markets. One of the main characteristics of this segment is aggressive price-matching and hence low
fares, unit costs and thus thin profit margins determine the LLC player’s business model (MarketLine, 2016).
Despite the recent beneficial oil/fuel price development, the extensive competition especially in the fragmented
European market has pressured players to pass on most fuel-related cost savings to end consumers in form of
cheaper ticket prices.
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Regarding the rivalry for infrastructure, the limited airport landing slots and routes are often strategically
allocated by airports and the assignments are often additionally overseen by governments. Also the capital
requirements for routes to popular destinations are often extremely large and can cost up to 15 mUSD
(Schlappig, 2015). Hence, it is typical for large companies to acquire smaller airlines even if solely due to their
slots and routes (Merkert & Morrell, 2012). Moreover, capital requirements are even higher has the necessary
assets to establish an airplane fleet often exceed investments of multiple bnUSD. In general, the industry is
characterized by high barriers to exit, due to the difficulty to sell assets at market value to competitors and
because players typically form long-term contracts with all forms of suppliers including, airports, fuel
suppliers, banks, airplane manufacturers and further (Peoples, 2014). Due to the large required capital
investment and the industries importance for local economies, many players were established as state owned
enterprises and still mostly operate on routes to and from their home country.
A further rivalry defining factor is that “(a)irlines service tends to be what economists call an undifferentiated
product” (O’Connor, 1995). While most airlines have some form of loyalty programs, these often fail to
successfully incentivize customer choices and represent the only form of switching costs (Deloitte, 2013).
Whilst some players try to set themselves apart by offering additional services, entertainment programs, special
offers or other features, the only relevant and important forms of differentiation are flight scheduling, times of
departure as well as arrival and the route itself (O’Connor, 1995).
Threat of Substitutes: The availability of substitutes for passenger air traffic is contingent on the length of
the route in question. According to the Committee on Climate Change (CCC) (2010), substitutes for air travel
exits especially on domestic journeys of less than 400km, as railways and modern high-speed trains often offer
more conventional and faster alternatives measured on a point to point basis. On journeys above 400km
however below 800km, substitution threats “have the potential to enable significant modal shift” (CCC, 2010).
Frequent flyer miles aside, for travels of these lengths, substituting air transportation with rail or car travel may
even be of more convenience for consumers, especially as there are nearly no switching costs. The situation
changes for travel plans of above 800 km. Measured by door-to-door journey time, air travel is likely to be the
fastest and most convenient option (CCC, 2010). In order to even be considered competitive, substitute options
like high speed trains would need to have significant other advantages as e.g. much lower prices. This is
especially advantageous for airlines, as while the often most profitable routes also happen to be the popular
long-distance flights between New York and Europe or Asia and Europe, these routes are also the most unlikely
to be substituted (Peterson, 2011).
Threat of new entrants: The combination of recent strong growth with consumer's low switching costs, the
nature of the industry shows attractiveness for potential entrants. However, the industry has also proven to be
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highly price sensitive thus an attempt of entry is unlikely to be unanswered by current players. However, as
margins are especially thin in the fragmented markets and profits are often only achievable through optimized
economies of scale, a market entry is generally too risky for potential investors. Additionally, establishing a
fleet and route network of destinations requires substantial upfront investments. Hand in hand with these
requirements are also often the need for long-term supplier contracts to e.g. hedge oil price developments as
well as access to global alliances or partnerships. Both of these agreements enable current players to exploit
synergies and optimize efficiency. Also, without alliance access potential entrants face a lack reputation, which
is becoming increasingly more important for customers due to the publicity of recent disasters related to air
travel (Iata, 2014).
Buyer Power: Buyers are mainly perceived to be individual end consumers, business accounts or travel
agencies acting as brokers. Based on the entry barriers described above, end consumers themselves as well as
most businesses accounts are highly unlikely to establish an own airline. While, some travel agencies having
cooperated historically to form smaller versions of charter airlines, most of these projects are commonly
unsuccessful (MarketLine, 2016). Thus, airlines are able to sell tickets on a take it or leave it basis resulting in
overall low bargaining power of buyers. Nevertheless, the price sensitive mass of consumers in combination
with low-switching costs can be extremely pressuring to offer adequate prices. Hence, the buyer power is seen
as moderate.
Supplier Power: The power of suppliers for airline companies varies with their type. For aircraft
manufacturing, the main two global players are the corporates Boing and Airbus. The small amount of players
within this industry is based on the high capital intensity as well as the required technological knowhow. Due
to the oligopoly structure of the supplier industry individual airlines usually comprise only a small share of a
suppliers’ business. While aircraft prices used to be sold on a profitable take-it-or-leave-it-basis, slight room
for negotiations and conditions has come up during the recent decade (MarketLine, 2016). Regarding the
supply of infrastructure, airlines face substantial switching costs when it comes changing airports or routes –
especially if the airport is located in a market in which airlines have a representative share of end-consumers.
Nonetheless, most airports bargaining power is limited, as the key components of an airport’s and an airlines
business is interdependent – the push of passenger traffic. Airports enter into long-term agreements and even
collaborations if airlines are willing to create “hub-airports”. Moreover, the commoditization of oil as well as
the use of external hedging strategies largely weaken the power of fuel suppliers (Iata, 2016). Hence, overall
the supplier power can be seen as moderate.
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Conclusion: The severeness of competition driving forces within the industry for passenger air travel are
moderate. The exposure to both buyer and supplier power is moderate due to the interdependency among the
player key business components. Buyer power is mainly influenced by the large customer base who have low
switching costs, while oligopoly market structure defines the supplier relationship. Furthermore, substantial
capital requirements and thin profit margins impede market entry by new players. Lastly, substitution effects
are low on long-haul flight, however impose threats on domestic and short-haul flights.
4.3. SWOT Analysis
In order to categorize and highlight the main findings from sections 3 & 4 of this report a SWOT analysis is
displayed in figure 10 below. The concept is a popular tool for strategic planning as it depicts the company's
current positioning and ability to exploit or avert external circumstances (Petersen & Plenborg, 2012).
Figure 10: SWOT analysis of Deutsche Lufthansa AG Source: Own creation
5. Financial Analysis
So far, the previous sections have shed light on the operations as well as the environment of Deutsche
Lufthansa AG. The internal and external analysis help understand the company's revenue as well as profit
drivers and provide a strategic overview of the company's operations going forward. Understanding how the
company has performed financially within this environment is essential in forecasting the company's future
• Volatile earnings have only stabilizing slowly since 2008. The upcoming Brexit has only made the economic environment more unstable.
• Terrorist attacks have overshadowed the last two years. A continuation will further negatively impact flight demand
• Gulf Coast carriers show strong increases in market share as they receive increasing government support and face lower labor costs
• LLCs are tapping into the long-haul market, increasing the competitiveness on some brand’s most profitable routes
• Multiple well positioned network carriers with one of the largest route networks globally
• Large shares and strong market positions at the hubs in Frankfurt,
Munich, Zurich and Vienna
• Brand portfolio is well diversified with competitive hub airlines, a growing LLC segment and leading aviation service companies
• Worker unions have caused cancelations of 14.900 flights and while agreements have been made with cabin crew employees, pilots remain unsettled.
• Historic high costs and a large full-time employee base have pressured both gross profit and net income.
• Through growing Eurowings with numerous simultaneous acquisitions, Lufthansa is facing a
challenging multi-brand integration
• Careful incorporation of Brussel Airlines can significantly extend Lufthansa’s route network and enable an all brands to benefit from an increased catchment area reach
• Eurowings will be the third largest LLC Europe’s 2017, after having a fleet size of only 27 aircrafts in 2015. Thorough planning and investments can potentially enable the brand to establish itself as one a top LLCs in Europe
xxx
Strengths Weaknesses
xxxxxxxxx
Opportunities Threats
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performance and in setting up a robust valuation model. In order to understand the financial performance, a
quantitative analysis of the Lufthansa's historic financial and accounting performance is necessary.
When considering to acquire stocks, an investor's main interest is typically devoted to the anticipated return
on invested capital (ROIC) and future expected free cash flow (FCF). These essentially determine the stock's
worth for an investor and thus are essential to the valuation process in quantifying the true fair value and stock
price of a company. However, both factors are not readily available from a company’s annual reports, as
companies usually summarize all conducted transactions and do not differentiate between operating
performance and financial performance. Therefore, to enable an analysis of Lufthansa's relevant performance,
the following section will begin with a reformulation of financial statements in which operating and non-
operating activities are distinctly separated.
The peer group included in the financial analysis remains the one introduced in section 4 of this report and has
a similar set of companies as the ones Bloomberg, Reuters and Capital IQ select as relevant peers. To qualify
as a comparable peer, a few conditions need to be considered, such as similarity in corporate size and business
model, accounting standards, reporting currency and the reporting period. While similarity size and business
model are not observable through the ratios, they influence e.g. a company's growth potential. Therefore, Air
Berlin and Ryanair differ strongly from the other four Full-Service Network Providers and will selectively be
excluded from individual the calculations. Both are of smaller size, only point-to-point LLCs and lack exposure
to global events. Also, all peers except Delta Air Lines use International Financial Reporting Standards (IFRS)
accounting principles, while the North American carrier applies GAAP standards. Similarly, Delta Air Lines
is also the only company deviating from reporting in EURO as it uses the dollar (USD). The company's
financial reports have been transformed into Euros based on the exchange rate on the valuation date, 30th
December, 2016. Lastly all companies' fiscal years are based on the calendar year except Ryanair's which
reports from 1st April onwards. Overall, the comparability of the peer group is somewhat limited, however
with the mentioned adjustments regarding the reporting standards and a selective exclusion of Air Berlin and
Ryanair, a financial analysis among these companies will nevertheless support an understanding of Lufthansa's
performance.
5.1. Reformulation of Financial Statements
As mentioned above this sub-section will guide the separation of statement items into operational or financial
categories. In order to do so, an analytical income statement and balance sheet will be created for all peers
which depict the reclassification of the mentioned items. While for the majority items the chosen classifications
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are self-explanatory, a reasoning is provided if justification seems necessary. The guidelines by which the
classifications have been chosen follow the methodology of Petersen and Plenborg (2012). Evaluating and
explaining all items of the peers' financial statements is out of the scope of this report and not crucially needed
because most statements follow a similar structure. All final analytical income statements as well as balance
sheets are presented in the appendix 7 - appendix 18.
In the process of reformulation, two new elements are introduced, one on the analytical balance sheet and one
on the analytical income statement. The new elements are Invested Capital and Net Operating Profit Less
Adjusted Taxes (NOPLAT), respectively. Invested capital embodies the capital which has been required to
fund operations. As the source of financing is irrelevant, both equity and debt investments are considered. The
second term NOPAT is added to the analytical income statement and resembles the income generated through
business operations, excluding financial expenses/income and after subtracting cash operating taxes.
Furthermore, it should be noted that the accounting principles set by IFRS differ between annual reports used
for the historic analysis. In 2014 the International Accounting Standards Board (IASB) introduced changes to
the accounting principles IFRS, affecting the reporting of joint ventures and principles in disclosing interests
in other entities. The changes had no relevance for 2014, as the company did not engage in activities affected.
While, Lufthansa had many investing and divesting activities in 2015, the company states that the implemented
changes had little or no material effect on 2015 figures (Lufthansa, 2015; Lufthansa, 2016).
Revenue: The reported group level revenue on the consolidated financial statements solely comprises external
income generated through the business segments Passenger Air Group, Logistics, MRO, Catering and others
(Lufthansa, 2016). In line with the accounting standards, sales are recorded with the transfer of the good or
service to the customer. The figures also only depict externally generated revenue, thus sales within the group
are already eliminated. This allows us to classify the entire groups revenue as operational.
Depreciation, amortization and impairment: The items of depreciation, amortization and impairment,
expenses are broken down into aircraft and property, plant and other equipment. Changes in impairment
include to a large extend value changes of aircrafts held for sale and it is assumed that other depreciation is
split according to the shares of assets and are thus operational. Deutsche Lufthansa AG lists depreciation,
amortization and impairment as cost of goods sold due to which they need to be extracted and deducted from
EBITDA.
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Result of equity investments accounted for using the equity method & other equity investments: This
item mainly comprises results related to equity investments and joint ventures within the business segments
Logistics, MRO and Catering. As these are necessary to and benefit the operations conducted in these business
areas, both income statement items are classified as operational.
Other operating income and other operating expenses: Both items mainly consist out of foreign exchange
gains or losses excluding financial liabilities. The occurrence of these is dependent on differences between the
currency exchange rates on transaction dates with those at the time of payment. Foreign exchange gains from
these transactions are listed under other operating income while foreign exchange losses are accounted for
under other operating expenses. Other items include income from staff secondment, compensation received
for damages, rental income and income from sub-leasing aircrafts. Expenses in relation to staff mainly include
travel as well as training expenses for employees both inside and outside the group. All items are reported
under other operating income/expenses and remain classified as operational.
Corporation tax: Lufthansa's amount payed in corporation tax is determined through both operational and
financial activities. Taxes paid in relation to operations reduce the company profit, however expenses such as
mortgage interest, charitable donations, amortization and depreciation provide companies with reductions in
taxes to be paid. These discounts on taxes due to financing activities are generally termed tax shied and are
provided as governmental incentive to fuel investments and growth. Limited information is given by Lufthansa
on the size of the tax shield and how taxes are computed. In order to account for the tax shield in the best
possible manner, it is calculated through multiplying the net financial result with Germany's reported tax rate
(25%). Potentially the group's debt may also stem from borrowings held in other countries with different tax
rates, however the information regarding the origin of debt is limited and thus the most relevant statutory tax
rate is used (Petersen & Plenborg, 2012).
Reclassification of balance sheet items: The figures presented in the balance sheet resemble only a snapshot
of Lufthansa's financial position at a single point in time, in the case of the group the 31st December. Despite
limitations of the snapshot representing a whole year of operational developments, it is still useful in providing
an understanding about a company's financial setup. A comparison over time reveals trends in the development
of singular line items and shows shifts in operational focus. Similar to the income statement, accounting
standards also do not require a separation of operational and financial assets within the balance sheets.
Therefore, as mentioned above the element Invested Capital is added and resembles the capital necessary to
create value. It is defined through the difference in operational assets and liabilities as well as the difference
between interest bearing debt and the combined total of equity and financial assets.
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Aircraft and reserve engines: Lufthansa's assets reported under aircrafts include the company's vehicle's
residual values. Incorporated here are 79 aircrafts totaling €2,489m currently rented out to Asian, French and
Irish leasing companies serving the Bermuda’s in order to retrieve more favorable leasing terms. Furthermore,
six airplanes, reported at €70m, have the purpose of realizing a positive PV through cross-border leasing
constructions. The listed employments of vehicles are partially limited in their operational use as it is unclear
if they are operated solely in their respective airspaces. Despite the lack of information a doubt regarding the
operational classification is not justified and thus the balance sheet element is completely categorized as
operational.
Property plant and equipment: Property, plant and equipment additionally include assets in relation to
technical equipment and machinery, operating and office equipment, advanced payments and plant under
construction write offs. As limited information is provided, it also assumed that all of items are operational.
Investments using the equity method: This item combines joint ventures and investments into associated
companies. These co-operations are essential parts of the business model pursued by the group's subsidiaries
operating in secondary business segments. Notable are individual reclassifications in 2015 as e.g. Aircraft
Maintenance and Engineering Corp. (AMECO) is now not reported as a joint venture but rather as an associated
company. This and further reallocations follow a reduction initiative in the respective equity interest. As the
co-operations are essential to MRO, Logistics and Catering services, the item is classified as operational.
Other equity investments and non-current securities: Equity investments and securities include share
positions in corporation traded on active market. If prices are publically available, these are reported at fair
value. The Lufthansa group is not involved the operations of these underlying companies and no co-operations
are publically announced. Therefore, the investments are assumed not to be in relation with Lufthansa's core
operations and have been classified as financial.
Loans and receivables: The loans and receivables to be declared by the Lufthansa Group are mainly for the
use of gaining emission certificates. In accordance with the financial nature of a loan, Lufthansa discloses the
reported elements as cash-generating units and are therefore classified as financial assets in the respective
analytical balance sheet.
Trade receivables: The largest share of this item stems from receivables from affiliated companies as well as
third parties. Also included are insurance claims concerning the deliberate crash of the Germanwings aircraft
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earlier in 2015, which are partially offset through outstanding financial liabilities. Due to the affiliation with
subsidiaries and the effects of daily business, this item is classified as operational.
Current securities: Lufthansa itself claims this item is solely related to fixed income investments securities
and investments in cash-generating activities on money market funds. Thus it is classified as financial.
Cash: The Lufthansa group reports total bank balances only separated by respective currencies. The group has
capital in EUR, USD and Swiss francs, however does not articulate the share of cash required to fund
operations and the share of excess cash for hedging reasons. Bank balances have been held at a relatively stable
level throughout the last five years. The slight variations are to be explained in exchange rate fluctuations, as
amounts held in foreign currencies are translated at the exchange rate on the balance sheet date. In case
companies do not distinguish between operating and excess cash, Petersen & Plenborg (2012) outline that the
effect of classifying operational cash as excess is likely to be inconsequential and to have little material effect.
Thus, Lufthansa's bank balances are in total classified as a financial item.
Comments to balance sheet after reclassification: Appendix 19 depicts the development of Lufthansa's
reclassified operational assets in relation to its peers. The development from 2011 to 2015 shows a healthy
growth rate and no strong fluctuations in value. Lufthansa has a stabile reinvestment rate and ensures a
satisfactory fleet age as well as value through continuous reinvestments in aircrafts. Both operational assets as
well as the equity have slightly decreased in 2012 however recovered by 2015. The decreases in joint ventures
are purely of regulatory nature due to the changes in the IFRS and the losses here are offset by gains in
investments using the equity method. Further changes in the pension provisions are related to the ongoing
negotiations with worker unions of both cabin crews and pilots. The 2015 increase in pension provisions do
not indicate rising staff costs, even in the contrary, as multiple existing pension agreements needed to be
terminated in order to negotiate new employment conditions throughout 2016. Recently, agreements have been
reached with the cabin crew which are forecasted to positively affect staff costs, effective immediately
(Lufthansa, 2016).
5.2. Historical Financial Performance Analysis (Profitability, liquidity, solvency)
The reformulation of financial statements enables the analysis of Lufthansa's and its peer's historic financial
performance. Understanding how the strategic and competitive position has historically translated into a
quantitative financial performance is essential in predicting future expectations for the company as well as for
potential investors (Petersen & Plenborg, 2012). A financial analysis can be conducted through multiple
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methods, hence the following section will begin with a ratio analysis of the relationship between Lufthansa's
profitability, operational efficiency, liquidity and financial solvency. Insights regarding the developments over
time will show how well Lufthansa has created value in comparison to other players in the industry. As this
report aims to assist investors in deciding whether or not to invest in Lufthansa's equity, the analysis will begin
with the company's ability to generate a return on investment relative to its peers. Subsequently, the analysis
will follow a suggested structure indicated by the Du Pont model of Petersen & Plenborg (2012), which is
depicted in figure 11 below.
Figure 11: Du Pont Model Source: Petersen and Plenborg (2011); own depiction
Following the Du Pont model, after looking into ROE the key focus areas will be return on invested capital,
revenue growth and the financial health of the company. The first section will drill down into the components
of the return on invested capital in order to understand Lufthansa's operational key value drivers. Secondly,
the revenue developments and the key components determining an airlines revenue are outlined. Questions to
consider are if Lufthansa's revenue is driven from the inside or by influences outside the company's control, as
e.g. currency changes. Lastly, the financial situation of the company is evaluated in order to determine if capital
is available to fund short- and long-term investments.
Return on equity (ROE): For every growth opportunity, a company faces two decisions, the investment
decision and the financing decision. While first of which revolves around how to allocate the capital, the second
revolves around how to fund the investment - essential if debt or equity is to be used. Therefore, the ROE of a
company represents the return on equity components rather than the return of all investments. This is of
essential importance for equity investors, as their return depends on both the operating performance as well as
the financial leverage of a company (Petersen & Plenborg, 2012). Due to the pecking order, an equity investor
only receives returns on his invested capital after debt holders have been satisfied.
ROE
ROIC Profit Margin
Revenue
ASKs
Yield
Load factorFuel Costs
Payroll Expenses
Other ExpensesTurnover rate
Financial leverage
NBC
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Figure 12: Peer group return on equity (2010-2015) Source: Own creation; all relevant annual reports
From the perspective of an equity investor, the most desirable characteristics of the return rate are the actual
height and stability, as these would resemble a consistent profitable allocation of capital (Loth, 2016). The
returns generated by Lufthansa and the peer group, depicted in figure 12, mirror the volatile nature of the
airline industry as well as its earnings. In general, there is no long term trend to be identified for any of the
players, however Lufthansa shows one of the healthier ROE rates among its peers. The return rates experienced
a strong decrease in 2014, however recovered to an acceptable rate in 2015. However, in comparison to peers
the carrier is one of the more attractive investment options. The company displays the least fluctuations in
returns and was the only one able to positive returns in years of recession, as e.g. in 2012. Thus, Lufthansa's
equity seems more robust for unfavorable settings. The lower volatility in returns comes at the cost of lower
absolute returns when the industry dynamics are favorable, as to be seen in 2015, when the company depicted
the lowest rates. Notable is also that KLM (2014) and Delta (2011 & 2012) display negative shareholder equity.
This occurs if a company experiences strong losses, as the book value of equity reflects retained earnings and
therefore can become negative. As the respective calculated ROEs are consequently meaningless (Damodaran,
2007), the values have been excluded from the figure.
Return on Invested Capital (ROIC): As mentioned above, the ROIC is a more exact indicator of how
successful investment decisions have been, because it measures the total return on invest and not only what is
left after deducting the debtholder's share. According to Petersen & Plenborg (2012), the ROIC is a very
influential determinant of a company's valuation estimate. A higher ROIC can also favor a lower cost of debt
as it indicates potential lenders lower risk of defaulting on payments. The underlying focus of the ROIC is the
operational profitability and is therefore calculated through the newly introduced elements NOPAT and
Invested Capital. In general, investors desire the ROIC to exceed the WACC, as this indicates value generation.
The ability to generate value leads to higher prospects and in turn a higher stock price. Figure 13 below shows
both the level and development of Lufthansa's ROIC benchmarked by the selected peers.
-50% -30% -10% 10% 30% 50%
2011 2012 2013 2014 2015
Peeraverage LHA KLM IAG Delta
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Figure 13: Peer group return on invested capital(2010-2015) Source: Own creation; all relevant annual reports
On the first sight, the ROIC resembles a similar picture as the ROE. All companies show a strong volatility in
returns with Lufthansa as the most stable among its peers. All also experienced a low in 2014, followed by
significant improvements in 2015. In terms of the absolute level, the North American player Delta Air Lines
depicts the highest return rates. This is expected as section 2 of this report has outlined the higher profitability
potential of North American players due to a more favorable competitive environment. While, investors
generally expect the ROIC to exceed the WACC, this is not the case for the airline industry, as 2015 has been
the first year in history in which the industry wide ROIC as exceeded the average WACC. In comparison,
Lufthansa's stable return rate increases the company's attractiveness for investors, while the absolute level of
returns is lacking behind its more volatile peers.
As the ROE and also the ROIC provide a good overview of Lufthansa's operational performance, neither of
the ratios can be used in order to identify what the source of Lufthansa's value creation is. Therefore, the
following sections will decompose the ROIC and analyze the specific components in more detail. As depicted
in the Du Pont model, the first level of components aims at identifying if revenue generation, capital utilization
or expense management are responsible for driving the company's value.
Profit Margin: The profit margin is the first ratio of relevance in the decomposition process of the ROIC. The
ratio varies based on the point to be made, as there is no one way to calculate it. The figures which can be used
are either gross profit, operating profit, pre-tax profit or net profit. Depending on choice, the selected ratio
represents the percentage of sales which remains for the selected income statement element after the
corresponding deductions.
-20% -10% 0%
10% 20% 30%
2011 2012 2013 2014 2015
Peeraverage LHA KLM IAG Delta
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Figure 14: Peer group profit margins (2011 - 2015) Source: own depiction; all relevant annual statements
Figure 14 above shows the net profit margins of Lufthansa and the peer group over the time period from 2011
to 2015. Across the board the level of profit margins is lower than in other industries, especially however for
the three European players. Also, the industry's volatility is again reflected, as airlines are especially prone to
the economic cycle. Lufthansa and Delta are the only companies able to maintain a consistently positive net
profit. Their more robust business even in down times of the economy is again apparent. Overall Lufthansa
shows consistent and acceptable levels of profit margins, in comparison to it peers. The company was however
not able to exploit the favorable conditions in 2015 as it underperformed both IAG and Delta. Thus, there is
potential for the planned strategic initiatives to improve group wide efficiency.
EBITDA-Margin: A popular measure to compare the performance of aviation companies is the EBITDA
margin, as it is commonly understood as the profit from operating activities. The industry's nature is
characterized by the high fixed costs concerning the ownership of airlines, which results in abnormally high
non-cash items such as depreciation, rent costs and amortization. Thus EBITDA-margin is most superior as it
excludes these factors and presents a more realistic ground for performance comparison.
Figure 15: Peer group EBITDA margins (2011 - 2015) Source: own depiction; all relevant annual statements
Figure 15 depicts the set of comparable company's EBITDA margin over the analyzed time period. The shown
stabile development of the peer average resembles the comprehensive trend among the chosen players. The
closer look at the margins again demonstrate Lufthansa's anticipated lower operating efficiency than its peers.
Thus, the question arises if the carrier's low performance in favorable conditions is due to limited abilities on
-5%
0%
5%
10%
15%
2011 2012 2013 2014 2015
Peer average LHA KLM IAG Delta Air Berlin Ryanair
-10%
0%
10%
20%
30%
2011 2012 2013 2014 2015
Peer average LHA KLM IAG Delta Air Berlin Ryanair
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in revenue generating or in cost structure. For this a trend analysis of each line item of the carrier's income
statement can provide more clarity.
Trend- & Common-size Analysis: The depictions of a trend as well as common-size analysis of Lufthansa's
operational elements are provided in appendix 20 & 21. Both are used to generate insights regarding
Lufthansa's operational performance. The first and most obvious insight is Lufthansa's stagnant passenger
revenue growth. While a 4% increase from 2011-2012 is an acceptable rate, the subsequent years lacked
revenue generation. After two years of negative and no growth in 2013 and 2014 respectively, the company
was able to grow passenger revenue again by 4,8% in 2015. However, even this is most probably not the result
of company initiatives, but rather due to the strong decrease in fuel prices, which is also observable in both the
trend- and common-size analysis. The competitive environment of the European industry is likely to have
forced carriers to pass savings related to fuel costs on to customers, which has in turn resulted in lower ticket
prices and an industry wide increase in demand for flying.
Further mentionable developments depicted in the trend analysis are the sharp increase in raw material and
staff costs. While raw material costs are not high in absolute terms, sharp increases of staff costs have
significant influence on the bottom line. Luckily for Lufthansa, the 2015 rise in staff costs does not resemble
a trend, but is rather explainable through one time payments in provision paid to the cabin crew and pilots in
order to renegotiate contract conditions. As these were necessary in order to generate an improved costs
structure going forward these increases are acceptable. However, the company does not report additional
information regarding the increase in raw materials, thus it seems as a potential area of efficiency improvement.
Nevertheless, the most significant development can be observed in the increase of EBIT and NOPAT from
2014 to 2015. This results from both the very low profit generated in 2014 and the better recovery in 2015.
Consequently, shareholder's expectations in 2015 were met also due to the resulting dividend payments and
the increase in EPS from 0,12€ in 2014 to 3,67€ in 2015.
5.2.1. Revenue and cost analysis
Succeeding the observations from Lufthansa's profit and trend analysis, the operational drivers are further
decomposed. Based on the highlights of the analyzed figures above, the following deep-dive will focus on
revenues, fuel costs, salaries and other operating expenses. As sales and the COGS are generally subject to
different impacts and each driven by unalike initiatives, the following section will be divided into subsequent
analyses of revenues and costs.
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Revenue analysis: As airlines sell individual seats for flights with limited capacity, the underlying components
of airlines' revenue are different than from companies in other industries. While revenue are generally the
product of quantities and prices, the factor capacity is additionally to the equation. This report will use the
following figures and equations to calculate the revenues of the companies at hand.
𝑁𝑒𝑡𝑇𝑟𝑎𝑓𝑓𝑖𝑐𝑅𝑒𝑣𝑒𝑛𝑢𝑒 = 𝑅𝑆𝐾 ∗ 𝑈𝑛𝑖𝑡𝑌𝑖𝑒𝑙𝑑
𝑁𝑒𝑡𝑇𝑟𝑎𝑓𝑓𝑖𝑐𝑅𝑒𝑣𝑒𝑛𝑢𝑒 = 𝐴𝑆𝐾 ∗ 𝐿𝑜𝑎𝑑𝐹𝑎𝑐𝑡𝑜𝑟 ∗ 𝑈𝑛𝑖𝑡𝑌𝑖𝑒𝑙𝑑
(1.1)
(1.2)
Revenue seat-kilometers (RSK) are the standard measure to identify how many quantities have actually been
sold, as these represent every seat-kilometer flown for which revenue has been generated. RSKs are the product
of available seat-kilometers (ASK), which represent the capacity of seats flown for one kilometer, and the load
factor, which represents the percentage of seat-kilometers serviced. In the nature of the airline industry, unfilled
seats are forgone potential revenue, which is why the load factor is the main measure for utilization. Thus in
understanding the revenue developments of a passenger carrier, the three driving factors need to be analyzed -
ASKs, Unit Yields, and Load Factors.
Figure 16: Peer group comparison of traffic revenue, ASKs and load factor Source: All relevant annual reports; own depiction
Net Traffic Revenue (in bn€) ASKS (in mio.) Load factor 2014 2015 % change 2014 2015 % change 2014 2015 % change
LHA 24.388 25.322 3,8% 268.105 273.974 2,2% 79,6% 79,8% 0,3% KLM 24.912 26.059 4,6% 105.755 107.851 2,0% 86,5% 86,4% -0,1% IAG 18.817 21.374 13,6% 251.931 272.702 8,2% 80,4% 81,4% 1,2% Delta 36.761 36.580 -0,5% 383.482 394.822 3,0% 84,7% 84,9% 0,2% Air Berlin 3.808 3.709 -2,6% 59.030 55.840 -5,4% 83,5% 84,2% 0,9% Ryanair 3.790 4.260 12,4% 92.457 86.822 -6,1% 82,0% 83,0% 1,2%
Figure 16 above shows the revenue, ASK and load factor levels and developments for 2014 - 2015 for
Lufthansa and the selected peer group. The revenue levels are in proportions as expected. As the three largest
European carriers have historically repeatedly battled for leadership, their revenue levels are similar. In the
case of Lufthansa, net traffic revenues had slightly dropped in 2014, but then recovered in 2015 by increasing
3,8% to €25,3bn. The main contribution of 89,3% to this element came from the business segment Passenger
Airline Group. The growth was fostered through both the 2,2% increase in capacity (ASKs) and positive
exchange rate effects (5,9%) (Lufthansa, 2016). However, a decline in overall yields due to the drop in fuel
prices negatively affected overall revenues.
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The previous sections have outlined that Lufthansa has not met revenue growth expectations throughout the
recent years. Figure 16 underlines these findings as it shows that the company's growth rate in 2015 has
underperformed most of the peer's. Only the financially struggling carrier Air Berlin and the North American
player delta portray lower growth rates. In terms of ASKs, Lufthansa is closest with its competitor IAG,
however, responsible for this is the 8% growth in 2015 due to the implementation of multiple initiatives. In
addition, Lufthansa's load factor is the lowest of all comparable companies and therefore utilizes its aircrafts
and available seats the least. However, the growth of the load factor and of ASKs need to be considered in
combination. A capacity increase usually by itself results in a challenge to sell additional seats. In comparison
to KLM and Delta, the Lufthansa Group portrays a higher increase in load factors. Thus, the company has
slightly caught up in terms of efficiency as it sold a higher share of the additionally added capacity in 2015.
Furthermore, appendix 22 shows a regional overview of Lufthansa's Revenue, ASK, RASK and Load Factor
developments. The company's load factors only declined in two regions, North America and the middle east.
This needs to be seen in perspective, as e.g. capacity in the already largest market North America increased by
4% growth. In line with above, after adding a significant share of capacity, a subsequent drop in utilization is
expected.
Cost analysis: Commonly, the main factors influencing airlines' financial performance are the three accounts
fuel, labor and other expenses. In accordance with this perspective, Koller et al. (2015) believe the best method
in assessing airlines' performance relative to peers is through analyzing operational drivers. An understanding
of each company's operational drivers and the relationships between cost accounts provides valuable insights
regarding differences among rivals. Especially airlines are favorable companies for such an analysis, as they
are required to report an extraordinary high amount of operational and traffic statistics due to safety regulations.
While a pure financial analysis provides insights about the level & trend of cost elements such as fuel, salary
and other expenses, including the associations and ratios with operating data such as Full-time Equivalent
(FTE) employees or flown distance (ASKs), reveal greater insights towards the operating efficiency.
Therefore, the 2015 operating statistics retrieved for Lufthansa and its peers are transformed into a branch of
the ROIC tree, as according to a Koller et al. (2015). At first glance Lufthansa and KLM both lack operational
performance as they show the lowest operating profit margin and strongly underperform their peers, excluding
Air Berlin. Thus, after deductions there is not much profit left from the initial revenues. The main sources of
deductions are as anticipated fuel, salaries and other expenses. These three categories alone cost the company
more half of its revenue, as shares for the year 2015 amount 56%, which is shown in the second branch.
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Figure 17: Operational drivers of labor expenses to revenue, 2015 Source: Koller et al., 2015; all relevant annual statements of airlines; Own depiction
Of the individual cost accounts, labor expenses, causes the largest deductions from revenues with 23%.
Nevertheless, despite the large losses in regards to the strikes, Lufthansa still exhibits competitive ratios as the
share of revenue is similar or better in relation to its main European rivals KLM and IAG. The absolute level
of salaries rose by 10,1% in 2015 reaching €8,1bn, while the number of FTE employees stagnated around
120.000. Reasons, were mainly the one-time payments in pension benefits as well as the reduction of discount
rates which triggered clauses in wage agreements (Lufthansa, 2016). While Lufthansa's labor costs share of
revenues was better than KLM's and comparable to IAG's, it was also significantly higher than Air Berlin's
and Ryanair's.
Superior ratios for Air Berlin and Ryanair in comparison to the peer group need to be assessed in perspective,
because the two smaller LLCs differ in their business model. While the FSNCs Lufthansa, IAG, KLM and
Delta rely on extensive networks based on a hub-and-spoke system, the LLCs service routes on a point-to-
point basis (Koller et al., 2015). Fewer serviced locations, operations at less popular airports and significantly
less complex as well as fewer services result for LLCs in lower labor costs. This is also depicted in the ratio
of labor costs per one million ASK. With 3 %, Lufthansa is slightly less efficient than the peer average, though
is also on a similar level with both IAG as well as Delta. KLM shows significantly worse management of labor
expenses in comparison to all remaining peers. The final decomposition of operating drivers depicted in figure
17 shows that Lufthansa has the most cost effective labor agreements per employee. Thus, the company's
overall high staff costs are not driven by expensive employee contracts, but rather by the total amount of
employees. In terms of labor costs, the number of employees is the main reason Lufthansa's is lacking in
efficiency. The ASKs offered per employee are the lowest among all peers. While human presence might be
Fuel/Revenue
LHA 17%KLM 24%IAG 26%Delta 16%Air Berlin 23% Laborexpense/ASKm Laborexpense/employeesRynanair 35%
LHA 3% LHA 7%Operatingprofitanalyis Salaries/Revenue KLM 7% KLM 24%
IAG 2% IAG 8%LHA 4% LHA 23% Delta 2% Delta 11%KLM 4% KLM 30% Air Berlin 1% Air Berlin 7%IAG 9% IAG 21% Rynanair 1% Rynanair 6%Delta 12% Delta 22%Air Berlin -13% Air Berlin 14% Revenue/ASKm MillionsofASM/employeesRynanair 16% Rynanair 9%
LHA 13% LHA 2,3Otherexpenses/Revenue KLM 24% KLM 3,3
IAG 8% IAG 4,5LHA 18% Delta 10% Delta 4,0KLM 36% Air Berlin 7% Air Berlin 6,3IAG 36% Rynanair 2% Rynanair 31,9Delta 39%Air Berlin 70%Rynanair 31%
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essential to the company's value proposition, the operational cost analysis suggests that a reduction of total
employees contains the highest potential in cost savings for the company.
5.2.2. Financial health:
Liquidity risk analysis: Following the structure introduced through the Du Pont Model in figure 11, the
following section will evaluate Lufthansa's financial situation in order to determine if capital is available to
fund short- and long-term investments. The representative measure is liquidity risk, which is determined
through a company's ability to generate sufficient positive net cash flows in order to cover both its short-term
as well as long-term obligations (Petersen & Plenborg, 2012). For a company with poor liquidity, investors
fear the possibility of not receiving promised capital and in turn demand a higher cost of capital due to
increased risk. The selected ratios to analyze Lufthansa's liquidity and financial health are presented in the
following.
Current ratio: The current ratio is a common measure for the ability of a company to repay its short term
liabilities through potentially liquidating its current assets. While a high score indicates low risk and cost of
capital, an excessively high value can also indicate a managements ineffective use of funds. Thus a generally
acceptable range of the current ratio is between 2.0 and 5.0, with the respective boundaries indicating a risk of
liquidity and inefficient capital use, respectively (Petersen & Plenborg, 2012). This general range of accepted
values may adjust according to the underlying industry.
Figure 18: Peer group current ratios (2010-2015) Source: Own creation; all relevant annual reports
At first glance of figure 18 above, the selected set of comparable companies cannot be measured on the general
scale. With only Ryanair exhibiting a current ratio near the lower boundary of 2.0, the peer group's average is
around the 1.0 mark. The ratios of the FSNCs are even lower ranging between 0.5 and 1.0. Overall apart from
0,0
0,5
1,0
1,5
2,0
2011 2012 2013 2014 2015
Peeraverage LHA KLM IAG Delta AirBerlin Ryanair
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the outlier Ryanair, all peers depict nearly identical high risk levels of current ratios, with Lufthansa slightly
leading the group. Nevertheless, while these values would generally indicate a strong threat of bankruptcy for
all peers, the standard of the airline industry varies. The overarching ability of airlines to generate enough short
term cash to meet obligations allows the companies to maintain low cash reserves. Overall, there is a slightly
negative trend of the ratios. However, Lufthansa resembles a conservative financing strategy and as the level
of its current ratio is in line with standard among peers, the short-term liquidity risk seems acceptable.
Quick ratio: A commonly more conservative but as meaningful measure of short term liquidity risk is the
quick ratio. The main adaption to the figures used in the current ratio is that only the most liquid assets instead
of all current assets are used. Thus, the quick ratio exhibits a more realistic picture of a company's ability to
pay off obligations, while the current ratio displays a rather hypothetical. This is because riskier current assets
are excluded from the calculation, as e.g. the book value of inventories will not be realizable in order pay off
obligations in the case of bankruptcy. The resulting range of satisfactory values lies between 1.0 and 3.5. The
depiction of Lufthansa's and its peer's quick ratios can be seen in appendix 23. In contrast to the current ratio,
all peer's figures are much more concentrated around the mean, without Ryanair as an outlier. Again all results
are below a satisfactory level of 1.0. While Lufthansa's quick ratio shows a slightly negative trend over the
recent years, it's relative development from 2011 is positive, as it resembles an improvement in comparison to
its peers. The levels of the current and quick ratio should not alarm investors as the industry standard level
across markets (North America & Europe) as well as segments (FSNCs & LLCs) seem to be achieved by all
players.
Financial Leverage: In contrast to the purely short-term focus of both the current and the quick ratios, the
assessment of financial leverage depicts a more holistic view on a company's financial health. The measure is
calculated as the ratio of total liabilities to equity, for which the total net interest bearing debt and book value
of equity are used. A high value reveals that a company preferably uses debt financing, which in turn has a
negative effect on earnings as interest payments rise with the amount of debt (Petersen & Plenborg, 2012).
Figure 19: Peer group financial leverage (2010-2015) Source: Own creation; all relevant annual reports
-10,0
0,0
10,0
20,0
2011 2012 2013 2014 2015
Peeraverage LHA KLM IAG AirBelrin Ryanair
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Figure 19 above shows the results for Lufthansa and its peer group. At first sight the extreme fluctuations and
extraordinary values of Air Berlin as well as KLM become obvious. Disregarding the two outliers, the
remaining group resembles similarly stabile values between 2,0 and 5,0. On an individual basis, the results
seem alarmingly high as all companies seem to fund the majority of growth with debt. However again the
nature of the airline industry causes many deviations from the norm. As competing within the airline industry
is naturally very capital intensive, the carriers are required to take on excessive debt, in order to finance the
expensive necessary aircrafts, acquire slots, expand the route network and enable the developments of
infrastructure. In comparison to its peers, Lufthansa has an average leverage ratio. After a peak in 2014, the
company subsequently increased its book value of equity. Generally, excessive D/E ratios can signal
significant risk to investors and can potentially lead to a drop in ratings, though this is not a current risk for
Lufthansa. In contrast, Brealey, Myers and Allen (2014) state that stock volatility is positively correlated with
financial leverage. Thus in comparison to its peers, Lufthansa may seem as a less risky investment opportunity
in comparison to its peers. Important to note are the negative values some players exhibit. Similar to the
scenario above in the ROE, these are again a consequence of negative book values of equity, which commonly
result from high cumulative losses. The resulting values are meaningless due to the mathematical mechanics
behind the ratio.
The presentation of the ratios above provides a good understanding of Lufthansa's overall financial health and
cover the most important determinants. However, during the course of the historical financial analysis, further
ratios and measures have been calculated and used as inputs for the forecasts. These include the Turnover rate
of Net Working Capital and the Liquidity cycle, of which the results can be observed in appendix 24.
6. Forecasting
The essential foundation of a valuation is the forecast of a company's financial performance and the required
invested capital necessary to fund ongoing operations. Thus the following section will elaborate on the forecast
of individual financial statement items which are necessary to predict these two main elements. The
combination of the preceding strategic as well as financial analysis deliver essential insights in quantifying the
future financial performance as well as the required invested capital. Despite the general inability of historical
performance to foresee the future, Lipsey & Lancaster (1957) as well as Koller et al. (2015) emphasize its
relevance for predictions as these already include underlying and hard to replicate relationships between firm-
specific events, economic forces, and socioeconomic factors.
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Sections two and three of this report have emphasized the strong relation between the airline industry and the
macro economic development. Thus intuitively, the GDP forecast seems like a good initial indicator for
Lufthansa's revenue forecast. In order to justify transferring forecasts of the GDP growth to Lufthansa's
expected revenue development, a correlation between these two historic growth rates needs to be apparent.
Therefore, figure 20 below compares the historic GDP growth with Lufthansa's revenue growth rates over the
last 5 years. As Iata's estimates of the historic global revenue rates are a good representation of the overall
development of the airline industry, these are included to control against Lufthansa specific deviations from
the mean.
Figure 20: Revenue growth in comparison to GDP and Iata estimates Source: Lufthansa annual report 2015, Iata, 2016; own depiction
The numbers reveal that there is not a strong enough correlation of historical GDP growth with Lufthansa's or
the industry's revenue growth. The deviations in growth can potentially be caused through factors of
specifically in Lufthansa's external environment, through industry developments or firm-specific events such
as changes in the regulatory environment for passenger carriers, technological developments in transportation,
an air plane crash, company employee strikes or Lufthansa's involvement in M&A. Either way, it becomes
apparent that the sole use of GDP forecasts is not a good indicator for Lufthansa's revenue growth.
Therefore, the main drivers of Lufthansa's operations and most influential factors of the company's bottom line
will be assessed and forecasted. Obliviously, in order to derive at forecasted free cash flow, all financial
statement items will need to be forecasted. Apart from the selected main elements which are discussed in the
next chapter, the remaining items are assumed to have minor relative importance and it is assumed that
analyzing all other factors will not significantly improve the margin of error of this valuation. Thus, these items
are forecasted based on their historic average percentage share of revenue.
Regarding the forecast horizon, a five-year time period has been chosen, ranging from 2016 to 2021, of which
the last year's predictions are used to estimate the terminal value. The terminal value is of particular importance,
as it makes up a large portion of a company's present value of future cash flows and thus of the current stock
price. Multiple calculations are feasible to estimate the terminal value, which depend on underlying
assumptions. This thesis applies an approach suggested by both Damodaran (2012) and Brunner (2004), due
Economic & revenue growth drivers 2011 2012 2013 2014 2015GDP 3,2% 2,5% 2,5% 2,7% 2,5%LHATrafficrevenuegrowth - 6,0% -2,6% -0,5% 9,4%LHAtrafficgrowth - 5,5% 1,3% -0,8% 4,9%LHANOPATgrowth - 149,1% -56,4% 24,3% 60,0%IATAglobalrevenuegrowthestimate 14,0% 9,8% 2,1% 4,3% -4,4%
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to which it is assumed that Lufthansa will operate for an infinite future time span and it's cash flows will
increase at a constant rate, the terminal growth rate. An alternative assumption would be that the company is
liquidated at a certain point in time for which the spot price is calculated, however it is currently unlikely that
Lufthansa will liquidate in the near future. The conducted forecasts do not include any potential negative
effects of any currently unforeseen events such as possible strikes of the worker union or terrorist attacks. As
a valuation is by nature build on multiple assumptions, which are not guaranteed to become true, the forecasts
for all following elements have been made for three different scenarios: Base case, best case and worst case.
This provides an investor with a potential range of values which provide a better perspective on potential
outcomes. The base case however will be the focus of both the forecasts and the valuation.
6.1. Revenue forecast
As the GDP development is not a good indicator for Lufthansa's revenue development, individual forecasts
will be made for the revenue components identified in the financial analysis: ASKs, load factor and unit yield.
A determining observation for forecasting the group's total revenue, is that passenger traffic is the core of
Lufthansa’s business model and has historically contributed 71% to the group's total. Thus, the passenger
revenue growth will be treated as the sole determinant for the group's revenue development. As Lufthansa's
other business segments also operate in sub-industries of the aviation industry, a high correlation between all
businesses is assumed. Thus, after forecasting the traffic revenue, the remaining segments' development will
be forecasted based on their historic average percentage share of revenue. While individual forecasts would
improve the accuracy of the valuation, an exhaustive examination of each segment is not justified due to the
high correlation between Lufthansa's business segments.
Also, the industry and internal analysis of sections two and three of this report have emphasized the significant
differences in geographical markets within the airline industry. In order to capture the diversity of the
geographical markets and consider Lufthansa's very different development in each region, ASK growth will
be forecasted on a regional basis. This division will follow Lufthansa's own organizational structure, which is
divided into the four main markets: North America, Europe, Middle East/Africa and Asia/Pacific.
Forecasting ASKs: ASKS are one of the main drivers of revenue as the capacity offered by airlines determines
the quantity limit of potential sales. Therefore, the capacity growth is an important determinant for Lufthansa's
overall revenue growth. A major influence on Lufthansa's ASK growth is the projected travel development
world-wide as well as regionally. The estimates of the regional ASK growth are based on a weighted average
of multiple analyst forecasts. Predictions of ASK growth on a regional basis have been retrieved from
MarketLine (2016) and Boing (2016). Additionally, the Federal Aviation Administration (2016) has published
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base, best and worst case prediction of the global ASK growth, which have also been retrieved and included
in the respective scenarios' ASK estimates. All analyst's ASK growth forecasts have then been aggregated and
a regional average was calculated. These analyst averages are further combined with regional GDP
development projections retrieved from the World Bank (2016). While the GDP development is by itself not
the solely most accurate forecast, Lufthansa's growth is nevertheless dependent on economic cycles. Therefore
the projected GDP development is included in the ASK forecast. Subsequently, Lufthansa's regional historic
average ASK growth rates over the past five years (2011-2015) have been calculated and also included as an
input for each regions future ASK growth estimates. While historic performance cannot determine future
performance, it is often seen as the second best alternative and thus should necessarily be included in
forecasting (Koller et al., 2015; Lipsey & Lancaster, 1957). Lastly, manual adjustments to the resulting
regional ASK growth rates for the years 2016-2021 have been made based on insights gained through the
internal and external analysis of this report. The best understanding of the ASK forecast model is gained
through directly accessing the excel-file or appendix 25 & 26. The main adjustments in the form of slight in-
or decreases of the ASK growth rate have been made on yearly and regional basis. One reason is: Lufthansa's
acquisition of SunExpress and Brussels Airlines as well as the wet lease of 38 Air Berlin aircrafts, which are
all to be included in the group's European network beginning 2017. While these acquisitions are expected to
additionally increase the company's ASK in Europe as of 2017 year, the successful implementation and growth
of Lufthansa's European capacity varies for the base case, best case and worst case.
Forecasting load factors: The inputs for forecasting Lufthansa's regional load factors are based on combining
three sources: Industry development projections retrieved from the Federal Aviation Administration (2016)
(FAA), Lufthansa's own published forecasts and lastly own estimated implications based on recent company
specific events analyzed in section 2 of this report. The FAA has forecasted industry wide load factor
developments and project very little variation in respect to a base, best and worst case scenario. They predict
the average global system wide load factor to grow less than 1% between 2016 and 2036, implying that the
overall asset utilization will remain stable at the current level. Figure 16 shows that Lufthansa's own seat
utilization in 2015 was 79,78%, trailing the peer average. However, multiple group wide efficiency initiatives
throughout the recent years have enabled the company to improve its asset utilization by 3,3% from an initial
load factor of only 77,25% in 2011. In regards to the regional forecasts of this thesis, neither continued growth
at this rate, nor a large increase overall is expected for the carrier. Lufthansa itself has expressed the projection
of a stable/slightly decreasing load factor for 2016 and a rise in subsequent years. However, these predictions
were made before the acquisitions of SunExpress, Brussels Airlines and the lease agreement with Air Berlin.
Thus, it is more reasonable to expect a drop in European load factors for 2016 and 2017 (Standard & Poor's,
2016). In the mid-term Lufthansa is expected to fill the excess seats better and increase the European aircraft's
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utilization. The forecasted growth rates of the regional load factors for the base, best and worst case can be
observed in the referred to Excel-Model or appendix 27.
Forecasting Price/Unit Yield: In line with the other revenue components, Lufthansa's yields are also
forecasted on a regional basis, due to strong differences in pricing between services offered in different
geographies. A major determinant for the pricing forecasts of this report is the projected global yield
development published by the FAA. Their analysts estimate the yields to grow at a rate of 1,9% in their
published base scenario, starting at an industry average of 13,98€ in 2016 and reaching a forecasted 21,17€ by
2036. While these respective estimates are taken as a base case, adjustments per region per year have been
made based on Lufthansa specific events as well as the development of fuel prices. As mention, it is typical
that additional savings or expenses in relation to fuel costs developments are passed on to consumers through
changes in the unit yields. Eurocontrol (2015) has analyzed the relationship between oil price developments
and air fare ticket prices and has identified that a 50% fall in fuel costs typically results in a 7-10% fall in ticket
prices. Thus, adjustments in Lufthansa's yield in regard to each year's projected fuel costs have been made
respectively. An explanation of the projected fuel costs can be found below. Furthermore, Lufthansa has
strongly expanded its Eurowings brand to form 29 aircrafts in 2014 to the third largest European LLC player
with over 100 aircrafts beginning 2017. The relative growth of low cost offerings compared to the carrier's
remaining services has been expected to cause a slight drop in European average yields in 2017. North
American average yields are also expected to slightly decrease in 2017 based on increasing competition
through rising LLC offerings and significantly added capacity to the market. In Asia the increasing effect of
fuel cost developments are expected to slightly outweigh competitive price pressures. As of 2018, effects of
capacity increases are expected to have stabilized and the forecasting per region is mainly driven by the
developments of fuel costs and the industry wide expected yield growth published by the FAA. The exact
estimated growth rates per region and year of the forecasting period can be seen in appendix 28 or the referred
to excel-file.
Forecasting other operating revenue: Lufthansa's reported item „other operating income“ comprises to the
largest extend foreign exchange gains, which have been realized through the differences between the exchange
rates on the transaction date and at the time of payment. By nature, these are out of the control of the company
itself and highly subject to the uncertain political and economic developments within the EU, USA and China.
Due to the uncertainty, these are assumed to move with revenue, with an exception in 2016, as the observed
continued drop of exchange rates is assumed to result in a slight decrease of the other operating income. In
regards to potential developments, the past US election, the Brexit, the upcoming French election and a
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potential delay of the interest rates by the European Central Bank could all lead to a strong USD, which would
have continuing effects on other operating income.
6.2. Forecasting costs and balance sheet items
Forecasting labor cost: Historically Lufthansa's staff costs have been strongly determined through strikes and
inefficient as well as outdated employment contracts with its main three employee groups: Ground staff, cabin
crew and pilots. Throughout 2015 the company's salary costs increased 5% to a total €2,8bn, while the total
headcount fell by 1%. As mentioned above, this increase is related to a one-time payment for wage settlements
with 30,00 ground staff employees, which was negotiated with the United Services Union "ver.di". The
agreements in late 2015 enabled the discontinuation of the defined benefit pension schemes, which was
severely necessary as Lufthansa has been overcompensating its employees in comparison to competitors. The
renewed contracts with ground staff are expected to show results as of 2016. Furthermore, in late 2016
Lufthansa additionally reached new collective labor agreements with the Flight Attendants' Organizations
(UFO) which are expected to decrease costs in relation to salaries, retirement and benefits for cabin crew
members beginning 2017 (Hofmann, 2016). Simultaneously, the large expansion of the Eurowings brand is
expected to increase the group's overall head count, which is also factored in the respective forecast. The long-
term staff cost development has been forecasted conservatively due to the uncertainty surrounding agreements
with the pilot's worker union. The resulting staff cost forecasts can be observed in appendix 29 - appendix 31.
Overall, the two collective labor contract agreements are expected to result in a more efficient cost structure
of Lufthansa and positively influence the carrier's EBIT-margins as of 2016.
Forecasting fuel costs: As mentioned previously, the development of oil prices does not only have a direct
effect on Lufthansa's bottom line through the fuel costs, but also an indirect effect on the development of ticket
prices as well as the demand for air travel. In 2015, the global drop in crude oil prices resulted in a 14,3%
reduction in Lufthansa's fuel costs. The absolute amount of 5,8b€ included a loss of 988m€ due to hedging
activities. While these risk mitigating strategies are beneficial in times of price increases, they naturally prevent
the full exploitation of spot price drops. For 2016 an almost identical growth estimate for Lufthansa's fuel costs
is expected. This is based on the year's first-half average price of one crude oil barrel, which traded for 41,2$,
representing a 30,5% decrease from 2015. Consequently, also the analysts of Standard & Poor's have reported
the expectation of Lufthansa's 2016 total fuel costs to drop to 15% of revenue - this represents a 17% reduction
in costs. In this report, the 2016 fuel cost growth estimate has been set slightly more conservative, as it seems
more reasonable that the hedging activities as well as the second half-year increase in prices slightly diminish
these reductions. Thus only a 10% reduction in group wide fuel costs is expected. For the remaining year's
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growth estimates, projections of three different analysts regarding future oil price developments have been
retrieved. In line with the market expectations, fuel costs are expected to rise again in the mid- and long-term.
A further input which is necessarily needed to be considered in the fuel cost development is the growth of
ASKs and the fleet overall. Lufthansa has added 80 aircrafts to its fleet as of 2017 and existing aircraft orders
up until 2025. Thus, these growth expectations are expected to have an increasing effect on overall fuel costs.
Figure 21 below depicts the estimated fuel cost development, considering all three factors: oil price
development, hedging effects and capacity growth.
Figure 21: Oil price projections and fuel cost estimates Source: Knoema (2016); own creation
Other operating income: As this cost element consists of similar items as its counterpart "other operating
income", the determining circumstances for future development are as uncertain. Thus, a development in
accordance with the historic average share of revenue is expected.
Forecasting aircrafts, reserve engines and spare parts: The main determinant for forecasting Lufthansa's
CAPEX is the currently existing order book of the company. The group is expecting the delivery of 52 new
aircrafts in 2016. These are additionally to the 40 vehicles chartered from Air Berlin of which the costs are
also capitalized. Furthermore, as part of a group wide fleet renewal and rejuvenation program the carrier's
order book comprises 251 aircrafts to be delivered by 2025. Thus, these increases in fleet are reflected in the
projected balance sheets. In accordance with Standard & Poor's (2016) Lufthansa's CAPEX in 2016 and 2017
is expected to slightly exceed 2€bn. The group capitalizes investments in the four main elements: Aircrafts,
Reserve engines, spare parts and PPE. Further forecasts of balance sheet items have been made to the book
value of reserve engines as well as repairable spare parts. As these in their nature are expected to be stocked
based on the number of underlying aircrafts, both elements have been forecasted based on their historic
percentage of the book value of aircrafts. Consequently, these balance sheet items are estimated to develop
similarly to the book value of aircrafts and contribute to Lufthansa's capital expenditures.
Forecasting depreciation: Lufthansa has identified three asset groups of which investments are depreciated,
these are: (1) Land and Building, (2) Technical equipment, machinery, vehicles as well as spare parts and (3)
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Other equipment and office equipment. Based on these categorization, depreciation has been forecasted based
on the historic % of these equivalent balance sheet items. Thus, the above mentioned fleet renewal and
rejuvenation plan of the group results accordingly in a proportional increase in depreciation for the years 2016
and 2017.
Conclusion forecasting: Overall, passenger traffic remains a growth sector as ongoing global economic
growth in 2015 had a positive impact on demand for air travel around the world. This is also reflected in the
estimates of Lufthansa's future growth. While the company's cost reduction initiatives for staff as well as
efficiency improvements are expected to improve the EBIT margin starting in 2016, partial benefits of the
continued decrease in fuel prices pressure unit yields as savings are forced to be passed on to customers. These
effects result in a 2016 decrease of group revenue but increase in efficiency. Moreover, strong additions to the
fleet in 2017 through the continued rebranding of Germanwings into Eurowings, the acquisition of Brussels
Airlines and the added aircrafts from Air Berlin are expected to strengthen Lufthansa's footprint in Germany,
the carriers largest market in terms of traffic revenue. The group-wide planned fleet renewal and increase in
capacity is assumed to result in a lower 2017 load factor as the company will not be able to fill all additional
seat during the first year. In combination with expected rising fuel prices and normalized growth of staff costs,
a slight decrease in NOPAT and FCF is projected. In the medium and long run, Lufthansa is expected to fill
the added seats better, through which traffic revenue and EBIT slowly normalize in growth.
6.3. Best & Worst case scenarios
Best and worst case scenarios have been created in order to analyze Lufthansa's stock price by considering
alternative possible outcomes. The main two reasons for including a scenario analysis are: Firstly, because the
Lufthansa Group including all its business segments operate in a volatile environment in which external factors
have severe impact on development potentials. Secondly, the group is facing a challenging multi-brand
integration of Brussels Airlines, SunExpress and Air Berlin in Europe. As this is a challenging task, a best and
worst case scenario resemble a favorable and unfavorable degree of successful integration. Generally, the
revenue calculations for all scenarios are is still derived through the product of regional ASKs, load factors
and unit yields, but the assumptions which the growth rates are built on differ. The best case scenario resembles
a situation in which more favorable fuel price developments as well as greater success of efficiency initiatives
is assumed. The worst case in contrast displays unfavorable assumptions regarding the estimated growth rates.
As these changes affect the major underlying forecasting elements of this valuation, the three scenarios result
in a range of potential share prices for the Lufthansa group. All relationships between the growth estimates for
revenue, staff costs and fuel costs with the forecasted income statement as well as balance sheet are kept the
same for the three scenarios.
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7. Valuation
7.1. DCF Approach
Among practitioners, the discounted cash flow (DCF) approach is one of the most popular used methods to
assess the attractiveness of an investment opportunity (Petersen & Plenborg, 2012). Practically speaking, the
method aims at evaluating an opportunity based on today's terms for which all forecasted cash flows of an
enterprise are discounted to arrive at a present value of the company. The respective equation is:
𝐸𝑛𝑡𝑒𝑟𝑝𝑟𝑖𝑠𝑣𝑎𝑙𝑢𝑒 =𝐹𝐹𝐶𝐹
(1 + 𝑊𝐴𝐶𝐶)D
E
DFG
+ 𝑇𝑒𝑟𝑚𝑖𝑛𝑎𝑙𝑉𝑎𝑙𝑢𝑒(1 + 𝑊𝐴𝐶𝐶)E
In order to derive at the present values of cash flows, these need to be discounted with a factor commonly
known as the weighted average cost of capital - WACC. The WACC represents the total cost of capital,
influenced by a company's financing choices. Enterprises can fund investments through equity or debt, which
differ in the rate of return corresponding investors expected from the company. The WACC averages the cost
of equity and debt respectively and then weighs then according to the capital structure in order to calculate an
overall weighted cost of capital. The formula used is:
𝑊𝐴𝐶𝐶 = 𝐸
𝐷 + 𝐸∗ 𝑟K +
𝐷𝐷 + 𝐸
∗ 𝑟L ∗ (1 − 𝑡𝑎𝑥𝑟𝑎𝑡𝑒)
To derive at Lufthansa's WACC, the following sections will chronologically elaborate on the respective
elements of the formula above, beginning with the capital structure and then explaining the cost of equity, the
cost of debt and the applied tax rate.
Capital Structure: Every financing decision influences a company's capital structure due to which the relative
percentages of debt and equity are constantly in movement. As the applied capital structure determines the
discount factor for all future expected cash flows, it should be chosen is such a way which represents a
company's future target debt and equity weights (Petersen & Plenborg, 2012). While some companies chose
to determine and report a target capital structure, many also do not disclose information in this regard. In case
of availability, practitioners among financial advisers strongly advocate for use of the reported target capital
structure over the current debt-to-equity ratio (Bruner, Eades, Harris & Higgins, 1998). Lufthansa has reported
a target capital structure of 50:50. In order to check the feasibility of this target, appendix 32 shows the recent
historic development of Lufthansa’s capital structure, for which the equity was calculated through multiplying
the year-end share price with shares outstanding and the debt was obtained through the value of net interest-
bearing debt. While the target capital structure of 50:50 seems to be an optimistic long-term estimate, Petersen
& Plenborg's (2012) advocate for the use of the target structure. As the use of the target structure is also
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communicated as common practice among financial practitioners, its application in the calculation of
Lufthansa's WACC is reasonable.
Cost of Equity: The cost of equity is the next element required to calculate the WACC. Among many
possibilities to calculate this item, the two most commonly used models are CAPM and the slightly adapted
Fama-French-three-factor model (Koller et al., 2015). As the latter is based on CAPM, the main alteration lies
within the calculation of a company's systematic risk. In determining the WACC for the purpose of valuing a
company, Petersen & Plenborg (2012) advocate for the use of the original CAPM model. Thus, CAPM will be
applied to the case of Lufthansa and is calculated as follows:
𝑟K = 𝑟O +𝛽K ∗ (𝑟Q − 𝑟O)
Additionally, when a company operates in multiple countries of the world, its ability to generate future revenue
is dependent on the developments within these countries. As the demand for air travel is significantly correlated
with the economic wellbeing of a nation, default or financial distress can severely impact a carrier's demand
and revenue. Damodaran (2006) states that "for companies with substantial country risk exposure, either
because they are incorporated in emerging markets or because they have operating exposures in those markets,
it becomes critical that we adjust the cost of equity for the additional risk". As Lufthansa is a leading aviation
group and one of the most globally operating companies in the world, the group is especially exposed to
country specific risks and thus accounting for country specific risk is reasonable. The resulting formula through
which Lufthansa's cost of equity will be calculated is:
𝑟K = 𝑟O + 𝐶𝑜𝑢𝑛𝑡𝑟𝑦𝑠𝑝𝑒𝑐𝑖𝑓𝑖𝑐𝑟𝑖𝑠𝑘 + 𝛽K ∗ (𝑟Q − 𝑟O)
Risk-free rate: The risk free rate is the first item of the cost of equity which needs to be estimated. This
element represents an investor's alternative choice of investing risk free in the capital market. In order to
determine the current return on risk-less investment opportunities, an underlying asset is subject to two
constraints: it cannot have any default or re-investment risk (Damodaran, 1999). Due to these constraints only
the return generated from zero-coupon bonds of developed mature countries such as e.g. US, Denmark or
Germany qualify as an estimate of the current return on a risk-free asset. All corporate bonds are excluded due
to their indispensable chance of defaulting, while governments theoretically have ability to print the own
currency, a repayment of at least numerical promised amounts of money are guaranteed. The second constraint
of re-investment risk is bypassed through the zero-coupon bonds. As Lufthansa is a German company and
most of its operations are based at German airports, it seems natural to use the respective nation's bonds.
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According to Petersen & Plenborg (2012), the duration of the chosen bond shall approximately mirror the
duration of expected cash flows of the company. As Lufthansa has been operating since 1926, it is reasonable
to assume that the company will operate another 30 years. Thus, the spot rate of 0,953% has been retrieved for
the German 30-year government bond for the valuation date 30.12.2016 and will be used going forward. Critic
to using this rate may stem from the high volatility of government bonds throughout the recent years. The
fluctuations ranged from a spot rate above 3% in 2010 to ones below zero in 2016. An alternative to using the
spot rate given on the valuation date of this thesis could be the calculation of an average over multiple recent
years. However, as the future is unforeseeable due to political developments such as the Brexit and the US
presidential election, the spot rate on the valuation date is assumed to have priced in the most recent
information.
Country specific risk: In order to account for the country specific risk, a dataset has been retrieved from
Damodaran (2016b), in which the author lists 146 countries with their corresponding Moody’s ranking, the
resulting default spread and the total equity risk premium of the respective country. In order to extract country
specific risk from the given total equity risk premium, the US default spread is subtracted from the spreads of
all other countries. This is based on the assumption that the US it is a mature market with no default risk and
thus operations there should not impose country specific risk. Similarly developed countries like Denmark and
Australia consequentially also have a country risk premium of 0.0%. In a next step, regional averages for the
main geographical regions like Europe, North America, South America, Africa, Middle East, etc. have been
calculated. At last, Lufthansa's 2015 passenger revenue split by regions is used to calculate a regionally
weighted average of the company's corresponding country specific risk and is added to equation of the cost of
equity. The resulting country specific risk which is added to calculation of the cost of equity can be seen below
and adds up to 2,3%.
Figure 22: Calculation of Lufthansa's country specific risk Source: Damodaran, 2006 & 2016; own depiction
RegionsNo. of included
countrtiesRegional weighted averages of CRPs
Lufthansa regional % of passenger revenue
Weighted average of Lufthansa's CRP
Africa 23 7% 4%Asia 21 4% 18%Central and South America 19 5% 6%Middle East 13 3% 4%North America 2 0% 25%Western Europe 26 2,23% 44%Total 104 4,38% 100% 2,3%
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Systematic Risk (Beta): The next element needed to be estimated in order to calculate the discount factor is
Lufthansa's systematic risk, hence its Beta (β). The measure indicates the relationship between fluctuations of
the overall market and movements of the company's stock price. Thus, the first step in estimating the beta is
determining how to measure the overall market. This is commonly done through market indices. In accordance
with the analysis of historic stock performance in chapter 3 of this report, the DAX is chosen as an indicator
of the overall relevant market. DAX is Germany's leading index comprised of the 30 largest publically traded
companies and thus seems as an appropriate reflection of the overall market. A notable potential bias is that
Lufthansa is included in the index, due to which there is a direct relationship. Yet, the weight of Lufthansa in
the DAX was 0,75% in early 2016 (Firley, 2016), due to which a possible bias seems to be rather small.
Lufthansa's covariance with the market is calculated through retrieving and regressing five-year historic
monthly excess returns of Lufthansa and the DAX against each other. Monthly returns have been chosen over
daily, as a large portion of daily price fluctuations are due to market noise rather than trades based on
information. Also, using daily returns could potentially overstate the covariance between Lufthansa and the
market as the daily trade volumes may sometimes be too low. Damodaran (1999) refers to this as the non-
trading bias and suggests the usage of monthly returns in order to receive a cleaner covariance. Thus, the
calculated beta estimate is 0,844. In comparison, the reported beta from the Reuters database is 0,91. While
both are very close to each other, the average between both is build and serves as a base going forward.
The resulting beta estimate is then first unlevered and subsequently re-levered with the appropriate current
capital structure. For the process of unlevering, betas corresponding to the other FSNCs of the peer group have
been retrieved from Reuters database. All betas are then unlevered according to their respective capital
structures and an average asset beta is calculated across all firms. The capital structures of Lufthansa, KLM,
IAG and Delta are calculated with the respective end-of-day share prices on the 30.12.2016, the corresponding
number of shares outstanding and each companies total net-interest bearing debt, retrieved from the
reformulated financial statements. The resulting average asset beta of the four FSNCs is then re-levered with
Lufthansa's capital structure on the valuation date 30.12.2016 in order to derive at the company’s' re-levered
beta.
While the re-levered beta is by itself a viable estimate to proceed with in the WACC calculation, Damodaran
(1999) emphasizes the common practice among financial advisors to conduct post-regression beta adjustments.
The author argues that "over time, there is a tendency on the part of betas of all companies to move towards
one" (Damodaran, 1999). Accordingly, fairly simple techniques are used to satisfy the observed tendency, due
to which Bloomberg's beta adjustment formula shown below is applied to adjust Lufthansa's beta estimate.
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𝐵𝑙𝑜𝑜𝑚𝑏𝑒𝑟𝑔𝛽WLXYZ[KL = 𝛽\K]\KZZD^E ∗ (0,67) + 1,00 ∗ (0,33)
After adjusting the re-levered βregression the resulting systematic risk-factor for Lufthansa is 1,419. In
comparison, Lufthansa itself publishes an own calculated beta in its annual reports, which is 1,1 for the year
2015 (Lufthansa, 2016). As it is reasonable to assume that the developments throughout 2016 and especially
Lufthansa's growth through M&A have affected the company's systematic risk, this thesis proceeds with the
calculated beta estimate, which will result in a slightly more conservative valuation.
Market risk premium: The last element required in order to estimate Lufthansa's cost of equity is the market
risk premium. While the risk free rate is an investor's minimum expected return on a riskless investment, the
market risk premium equals the additional return which can be expected for investing in the market. Thus it is
calculated as the market return minus the risk free rate. As it is impossible to observe the future return of the
market, the estimates of two scholars are averaged. First, Fernandez, Ortiz and Acín (2016) have conducted a
survey asking finance professors, analysts and managers of companies about the market risk premiums they
apply for specific markets. According to their results a risk premium of 5,3% is appropriate for the German
market. Secondly, Damodaran (2016) estimates Germany's market risk premium to lie at 5,69%. Both
estimates are taken with equal weight into consideration and the average of 5,5% is used as the respective
market risk premium going forward.
Inflation risk premium: In addition to the country risk premium, it is common among practitioners in the
financial service industry to further adjust the cost of equity, due to risk of inflation in countries where
operations are pursued. Lufthansa's business is by nature multinational and revenues are affected by currency
exchange rate developments. Throughout 2015, changes in currency exchange rates decreased EBIT by €84m.
Nevertheless, despite a potential adequacy of such a risk adjustment, an additional risk premium is not added
to the cost of equity. This decision is made in order to avoid excessively increasing the WACC artificially. It
is assumed that the more conservative beta estimate and the country risk premium sufficiently cover the risks
in relation to potential economic downturns of countries in which Lufthansa operates.
Corporate tax rate: Lufthansa's corporate tax rate has been stable at 25% according to the company's yearly
annual reports from 2011-2015. As there are no indications of change, this tax rate is assumed to hold.
Cost of Debt: Lastly a company cost of debt resembles the net interest rate it is required to pay for the liabilities
it has accumulated from outside investors. The height of the return rate which lenders demand depends on the
probability of bankruptcy expressed through operational and financial risk. While the interest rate could
generally be retrieved from financial statements by the ratio of net financial expenses and net interest bearing
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debt, the lack of information regarding Lufthansa's carried forward interest and exact tax shield prevent
reliability of this method. Therefore, the groups probability of bankruptcy and corresponding estimate for the
cost of debt is based on published credit ratings from Moody's and S&P. Lufthansa's ratings from these two
agencies are Ba1 and BBB- respectively. Thus, both rating agencies presume Lufthansa to comprise
speculative elements and also account for the high leverage and implied credit risk identified in the financial
analysis. The corresponding cost of debt estimates are retrieved from New York Stern University (2016). While
Moody's ranking indicates a default spread over the risk free rate of 2,5%, S&P's rating corresponds to a 2,05%
additional spread. Adding the average of 2,28% to the used risk free rate of this reports, results in an estimated
cost of debt of 3,529% for Lufthansa. In comparison, the company itself published an applied rate of 3,45%
for the year 2015.
WACC conclusion: After the required elements of the WACC formula are estimated, the resulting WACC
for Lufthansa is 6,732%. As Lufthansa publishes an own estimate, a comparison is shown below. Between
2014 and 2015, the company did not re-adjust the WACC, due to which one main difference is the applied
risk-free rate, which has dropped significantly since 2014. In comparison, the two estimates differ by about
1%, which is caused through two aspects: First the higher beta of this report and secondly, a higher equity risk
premium through the addition of country specific risk. Having a rather high WACC will assume more cost of
capital to the company and hence a more conservative valuation. Overall the WACC estimated in this thesis
seems superior and more accurate as two years’ additional information were able to be included. All relevant
calculations can be seen in appendix 33 - appendix 39.
Figure 23: WACC calculation comparison Source: Lufthansa, 2016; own depiction
7.1.1. Free cash flow and enterprise value
After estimating the discount factor, the only remaining element in order to calculate the enterprise value is
the free cash flow. The entire calculation for the base case can be followed in appendix 42-43 and appendix
48. Beginning with the forecasted NOPAT, non-cash expenses like depreciation are added back. As according
to the annual reports of Lufthansa, aircrafts, spare parts, intangible assets and property, plant & equipment are
capitalized, these expenditures are deducted from the free cash flow. The approximation of capex is based on
changes to the respective previous year and the addition of that year’s depreciation. Further deductions from
the free cash flow are the changes in net working capital as well as changes in investments into other long term
Beta rf MRP CRP CoD CoE D/E WACCThesisestimate 1,42 0,95% 5,50% 2,29% 3,52% 11,04% 50:50 6,73%LHAownreporting 1,1 2,60% 5,20% 0,00% 3,40% 8,40% 50:50 5,90%
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assets. The FCFs develop in accordance with the implied strategic and financial analysis. While the company's
cost reduction initiatives for staff as well as efficiency improvements are expected to increase the EBIT margin
starting in 2016, partial benefits of the continued decrease in fuel prices pressure unit yields as savings are
forced to be passed on to customers. These effects result in a 2016 decrease of group revenue but increase in
efficiency. Moreover, strong additions to the fleet in 2017 through the continued rebranding of Germanwings
into Eurowings, the acquisition of Brussels Airlines and the added aircrafts from Air Berlin are expected to
strengthen Lufthansa's footprint in Germany, the carriers largest market in terms of traffic revenue. The
resulting large increase in capacity is assumed to result in a lower 2017 load factor as the company will not be
able to fill all additional seats during the first year. In combination with expected rising fuel prices and staff
costs normalizing, a slight decrease in NOPAT and FCF is expected. In the medium and long run, Lufthansa
is expected to fill the new seats betted, through which traffic revenue and EBIT slowly normalize in growth.
Figure 24: Valuation based on DCF model Source: own creation
Free Cash Flow Calculations 2016e 2017e 2018e 2019e 2020e 2021eyearsfromvaluationdate 1 2 3 4 5 6 NOPAT 1.469 1.124 1.405 1.598 1.823 1.830 +Depreciationandamortization 2.004 2.135 2.218 2.303 2.413 2.494 -CAPEXCapitalizednon-currentsassets(1.1) 18.152 20.168 21.620 21.763 22.246 23.228 Capitalizednon-currentassets(31.12) 20.168 21.620 21.763 22.246 23.228 23.695
Deltacapitalizednon-currentassets 2.016 1.452 143 483 983 467Depreciationandamortization 2.004 2.135 2.218 2.303 2.413 2.494 -TotalCAPEX 4.020 3.587 2.361 2.786 3.395 2.961non-currentassetsbeginning 1.313 946 990 1.038 1.078 1.125 non-currentassetsend 946 990 1.038 1.078 1.125 1.148
-Investmentsinotherlong-termassets -367 43 48 40 48 23-ChangeinworkingcapitalWorkingcapital(1.1) 363 74 79 82 85 89 WorkingCapital(31.12) 74 79 82 85 89 91 Deltaworkingcapital -289 4 4 3 4 2FreeCashFlow(FCF) 108 -375 1.211 1.072 789 1.339WACC 6,73%DCFValuation:PVFCF 101 -329 996 826 569PVForecastPhase 2.163 PVTerminalPhase 20.474 EnterpriseValue(EV) 22.637 DebtValue 13.983 EquityValue 8.654 -non-controllinginterest 24 ValueofCommonStock 8.630€ Commonstockprice 18,41€
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The resulting FCFs from these developments are divided into a forecast horizon and a terminal value, which
are then discounted respectively, according to the enterprise formula presented in the beginning of this section.
After subtracting minority interests as well as the market value of debt, which is estimated through the net-
interest bearing debt, the value of equity is derived. As last step, the equity value is divided by the total number
of shares outstanding on 30.12.2016. The resulting share price equals 18,41€, implying that the company's
share price of €12,27 on the valuation date was undervalued. The construction of a best and worst case scenario
provides a potential range of share prices depending on possible deviations in ASKs, load factor, unit yield,
fuel and staff cost. The different scenarios lead to a share price of 21,19€ in the best case and 14,10€ in the
worst case - these calculations can be seen in Appendix 44-50 or in the excel file referred to in the beginning
of this thesis.
.
7.2. EVA & Sensitivity analysis
A model used to value an enterprise is generally built upon many subjective assumptions as well as the
development of interrelated elements. Thus in order to test both, the correct construction of the model as well
as its sensitivity to specific estimations, the following section will first elaborate on the comparison of the
applied DCF model to an additionally built EVA valuation model, and subsequently elaborate on specifically
constructed data tables to analyze sensitivities.
7.2.1. EVA model
First, the construction of an EVA model after conducting a DCF valuation is a common approach to test the
underlying model's functionality. The reason is that both methods are built upon present value approaches and
therefore should result in equal values if certain conditions are met. Figure 25 below depicts the construction
of the EVA model based on the forecasted financial statements of Lufthansa.
The EVA valuation is calculated by the addition of the present values of a company's excess returns over its
cost of capital. If the EVA as well as the DCF model are built correctly, both result in the same estimated share
price (Petersen & Plenborg, 2012). In regards to the EVA, Lufthansa's economic added value for each
forecasted year is calculated through subtracting the company's estimated cost of capital from the NOPAT.
The respective cost of capital is estimated through the product of the established WACC and Lufthansa's
invested capital at the previous year's end. As indicated in the figure above, the resulting share price equals the
estimation calculated through the DCF. Consequentially, the model used in this report seems to be set up
mechanically correct.
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Figure 25: Valuation of Lufthansa based on the EVA-method Source: Own creation
7.2.2. Sensitivity Analysis
In order to attain Lufthansa's estimated share price of €18,41, the forecasts of the company's future performance
have been built on assumptions of which a slight change can by heavily affect the found share price. Which of
these assumptions exactly have an effect on the found value and how sensitive the found value is, is tested
through the following sensitivity analysis. For any investor, it is important to understand to which factors the
valuation estimate is sensible, as this gives him an impression of which elements’ development he needs to
observe closely in the future. Commonly such factors are the risk free rate, the beta or the global and regional
GDP developments. The sensitivity analysis of this sections is conducted on the base case scenario and the
following figures show data-tables which depict the sensitivity of the final share price when selected
assumptions are changed.
Figure 26: Sensitivity analysis WACC & terminal growth Source: own depiction
The table above shows that the model is highly sensitive towards the applied WACC, however less towards
the perpetuity growth rate. Applying WACCs between 5,7% and 7,7%, result in share prices varying from €9
to €33, while the impacts of changing terminal growth rates are less extreme. In order to further examine this
18 1,0% 1,5% 2,0% 2,5% 3,0%5,7% 26,62 29,43 32,99 37,66 44,046,2% 20,49 22,43 24,83 27,87 31,866,7% 15,45 16,79 18,41 20,41 22,967,2% 11,22 12,14 13,23 14,55 16,187,7% 7,64 8,25 8,97 9,82 10,85
Implied share pricePerpetual Growth Rate
WA
CC
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dependency, the applied discount rate is decomposed and figure 27 shows the effects on the share price if sole
changes in either the MRP or beta are implemented. Additionally, the sensitivity to the operating parameter
2016 fuel costs is depicted, as these developments also have a significant impact on the present value.
Figure 27: Sensitivity of MRP, Beta and 2016 oil price development Source: Own creation
The above outcomes show that the model is highly sensitive to both macro-economic factors as well as the
operational parameter. Especially striking is the valuation's sensitivity towards the MRP, as an increase of
0,25% triggers a roughly 12% change the resulting share price. This is especially notable for potential investors
as the MRP is one of the most non-observable or determinable factors and commonly only estimated through
surveys of practitioners and experts. Furthermore, a comparison between the beta estimated in this report and
the one published by Lufthansa reveals significant differences in implied company value. If the published 1,1
were applied the resulting share price would be roughly between €29,88 and €32,29. However, it is reasonable
that this strongly underestimates the company's risk. Further sensitivities are shown in appendix 51.
7.3. Multiple Analysis
In addition to the sensitivity tests, a multiples based valuation is conducted. The relative valuation will help in
evaluating how reasonable the DCF is and provide further insights into the company's expected future
performance. This kind of valuation is often included by practitioners, as the models can be set up quicker and
easier than present value analyses. Hence, analysts use them to get a quick overview of the company and the
market's opinion on the value of equity. However, as the model is purely based on periodic financials and hard
facts it is often seen as is rather simplistic and therefore rarely used stand-alone. As they are not subject to an
individual analyst's opinion, but based on observable data, this report will use the method as a tool to test the
1840,8% 0,95% 1840,8% 5,5% 1840,8% 1,0%3,50% 41,74 126,8% 1,02 34,88 89,5% -12,00% 23,24 26,3%3,75% 37,78 105,2% 1,07 32,29 75,4% -11,75% 22,64 23,0%4,00% 34,20 85,8% 1,12 29,88 62,3% -11,50% 22,03 19,7%4,25% 30,95 68,2% 1,17 27,64 50,2% -11,25% 21,43 16,4%4,50% 28,00 52,1% 1,22 25,55 38,8% -11,00% 20,82 13,1%4,75% 25,29 37,4% 1,27 23,59 28,2% -10,75% 20,22 9,8%5,00% 22,81 23,9% 1,32 21,76 18,2% -10,50% 19,62 6,6%5,25% 20,52 11,5% 1,37 20,03 8,8% -10,25% 19,01 3,3%5,50% 18,41 0,0% 1,42 18,41 0,0% -10,00% 18,41 0,0%5,75% 16,45 -10,6% 1,47 16,88 -8,3% -9,75% 17,80 -3,3%6,00% 14,63 -20,5% 1,52 15,43 -16,2% -9,50% 17,20 -6,6%6,25% 12,93 -29,8% 1,57 14,07 -23,6% -9,25% 16,60 -9,8%6,50% 11,35 -38,4% 1,62 12,77 -30,6% -9,00% 15,99 -13,1%6,75% 9,86 -46,4% 1,67 11,54 -37,3% -8,75% 15,39 -16,4%7,00% 8,47 -54,0% 1,72 10,38 -43,6% -8,50% 14,78 -19,7%7,25% 7,17 -61,1% 1,77 9,27 -49,7% -8,25% 14,18 -23,0%7,50% 5,94 -67,8% 1,82 8,21 -55,4% -8,00% 13,58 -26,3%
Sesitivity to 2016 fuel costs
2016
fuel
cos
t dev
elpm
ent
Sesitivity of MRP
MR
P
Bet
aImplied share priceSesitivity of Beta
Implied share price Implied share price
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DCF. Due to the relative approach, the selection of appropriate peers is essential in calculating meaningful
multiples. Players with differing business models or corporate structures should not be included as these
strongly falsify the outcome. Especially in the aviation industry, where business models range from Global
Full service network carrier to domestic point-to-point LCCs, including representative peers is of great
importance. As Lufthansa is one of the most complete aviation groups in the industry, pure LLCs such as
Ryanair and EasyJet, as well as extremely volatile or financially struggling companies such as Air Berlin are
excluded from the comparison set. The main criteria for selecting companies into the peer group are: 1) Being
a Full Service Network Carrier (FSNC), 2) global presence and 3) similar revenue size. The only two other
globally operating FSNCs are the corporate groups of IAG and KLM, which mirror Lufthansa's business model
the most. The core peer group is completed with the large North American Network Carriers Delta Air Lines,
American Airlines and United Continental.
In order to calculate the multiples and build the model, analyst's estimates of income statement items were
retrieved from the database Capital IQ. As the valuation date of this report is the 31st December, 2016, the
most recent and thus reliable data are Last-Twelve-Month estimate based on corporate quarterly reports
starting 2015Q4 until 2016Q3. As an equity valuation resembles expectations of future cash flow, Capital IQs
one-year forward estimate of all peers' revenue, EBITDA and Earnings are also retrieved and respective
multiples are calculated. After calculating Lufthansa's implied enterprise value, a weighted amount of net
interest bearing debt, cash, short term investments into securities and minority interest for the selected time
period from September 2015 - September 2016 are subtracted/added in order to arrive at an implied equity
value.
Figure 28: Relative valuation model Source: Capital IQ; Own creation
Lufthansa multiples
Company Name EV/ Revenue
EV/ EBITDA
EV/ EBIT
P/ EPS
EV/ 1y Revenue
(Capital IQ)
EV/ 1y EBITDA (Capital IQ)
1y P/E (Capital IQ)
Lufthansa 0,3x 2,1x 3,7x 3,2x 0,3x 2,3x 5,3x Peer Group multiples United 0,8x 4,2x 5,7x 9,3x 0,81x 4,83x 11,09x IAG Group 0,6x 3,5x 5,5x 6,5x 0,61x 3,49x 6,40x Delta Air Lines 1,0x 5,0x 6,3x 8,0x 1,02x 5,13x 10,02x American Airlines 1,0x 5,0x 6,3x 4,8x 1,00x 5,29x 10,42x Air France-KLM 0,3x 2,5x 6,3x 2,8x 0,26x 2,55x 3,57x
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Mean Equity Value Across Multiples Implied Equity Value Implied share price
High 18.997,4 40,5 Low 6.306,1 13,5 Mean (excl. Lufthansa) 14.141,5 30,2 Median (excl. Lufthansa) 15.553,3 33,2
The table above contains both enterprise multiples as e.g. current and forecasted EV/Revenues, EV/EBIT and
EV/EBITDA as well as Equity multiples like P/E and P/Forecasted Earnings, for both Lufthansa and the core
peer group. In general Lufthansa trades at significantly lower multiples than the average of its peers - for both
enterprise and equity multiples. This indicates that the company value is according to these metrics currently
below the general market valuation of a company in the aviation sector. Consequently, figure 28 shows that
the mean implied share price across all above metrics for Lufthansa is 30,2€ - significantly above the current
share price of 12,27€ on 30.12.2016. To put this into perspective a range of implied share prices based on the
highest, lowest, mean and median peer multiples is provided in figure 28. We can further see that even the
implied share price from the lower peer multiple is higher than the current share price. This also suggests that
Lufthansa is currently trading at a discount relatively to its peers.
Using the mean equity value across multiples gives a good overall impression of the underlying equity value,
however it does not take industry specific dynamics into account (Loth, 2007). Thus, in selecting the most
relevant multiple(s) to value Lufthansa by, two factors need to be considered. Firstly, the aviation industry is
characterized by its high fixed costs due to the high price of airplanes. This in turn causes significantly higher
depreciation, amortization and rent costs compared to other industries, which are mostly carried forward non-
cash items and can falsify valuations if they are included. Therefore, EV/EBITDA is a more relevant measure
as it excludes these items from the valuation and thus resembles airlines' operating performance more
realistically. Secondly, empirical studies by Liu, Nissim and Thomas (2002) have shown that because
valuations resemble expectations of future cash flow, forward-looking multiples are more accurate predictors
than historical ones. The use of forecasted rather than historic revenues and operating profits are further also
more in line with the valuation principles used in this report. Thus, the most accurate valuation of Deutsche
Lufthansa AG is expected when looking at the forward-looking EV/1year EBITDA multiple, as depicted in
figure 29 (and appendix 52).
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Figure 29: Implied share price through enterprise and pricing multiples Source: Capital IQ; own creation Enterprise Value Multiples Pricing Multiples Implied Share Price
EV/ Revenues
EV/ EBITDA
EV/ EBIT
EV/ 1y Revenue
(Capital IQ)
EV/ 1y EBITDA (Capital IQ)
P/EPS Forward P/E (Capital IQ)
High 64,10 € 35,42 € 24,68 € 63,88 € 33,94 € 36,02 € 25,63 € Low 12,39 € 15,40 € 20,66 € 12,93 € 13,90 € 10,64 € 8,24 €
Mean (excl. Lufthansa) 45,18 € 27,73 € 23,21 € 45,19 € 26,41 € 24,26 € 19,17 €
Median (excl. Lufthansa) 50,11 € 29,08 € 24,35 € 49,88 € 30,60 € 25,08 € 23,14 €
The relative valuation based on the enterprise multiple using one-year forecasted EBITDA, suggests a share
price for Lufthansa of 26,41€. Consequently, the relative valuation implies that Lufthansa is traded at a
discount relative to its peer group. The value is also very similar to the implied mean share price across
multiples, thus the implications regarding the range set by high, low and median multiples are the same.
The result of the relative valuation supports the general tendency of the DCF, however it implies a more
significant undervaluation than the present value model. Potential explanations as to why the outcomes of the
two models differ with each other and with the market's price can lie in either method. On the one hand,
multiple valuations are subject to short-cuts as purely static financial data is used, thus eventually it just misses
to use essential information. Also, the only operating inputs are from financial statements. As the aviation
industry is very volatile, short term trends in performance and critical events are not considered. On the other
hand, the subjective expectations of this report on which Lufthansa's cash flow valuation is based may be too
optimistic in comparison to the market's expectations or too conservative in comparison to the multiples
valuations - depending on where the actual true value lies. In contrast to the relative approach, the DCF method
is very sensitive to subjective assumptions and opinions of the analyst, which are not inevitably correct. Also,
small changes in the assumptions can have large effects on the implied share price, hence the calculated fair
value is not necessarily accurate.
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8. Airline's M&A rationals
Earlier in 2016, Lufthansa's chairman and CEO Carsten Spohr drew investors' attention as he declared that the
aviation group plans to participate in the much-needed consolidation of the European airline industry in order
for the players to withstand North American and Gulf-Coast competitors (Maushagen, 2016). Already years
before, Büttner & Burger (2008) have identified the company as the European carrier group with the best
starting position to drive consolidation in its market. These announcements are essential for investors, as his
ROI and ROE are largely determined by the difference in buying and selling price, disregarding any dividends
received throughout the holding period. The common focus in assessing realized return often lies on the selling
price and how true initial expectations became. However, the influence of the initial buying price is often
neglected. An investor's equity investment commonly goes hand in hand with the expectation that the
underlying company will increase its worth. While generally any speculations or rumors surrounding a
company are priced in by the market, it is difficult to quantify the market's attitude towards these rumors. One
speculation surrounding Lufthansa arose during the last quarter of 2016, which implied that the company
would acquire the financially struggling carrier Air Berlin. Since the companies unexpectedly agreed upon and
announced a wet-lease deal of 38 aircrafts in September, the media is torn between the implications that the
deal has on the initial acquisition speculations. While some analysts see the wet-lease as an alternative to
M&A, due which any previous merger considerations would be redundant, others publically argue for why the
deal is an initial cooperation in order to set the tone for a soon to follow takeover.
Thus, the following section of this report aims to clarify if the respective deal announced September 2016
impacts acquisition M&A speculations between Lufthansa and Air Berlin. Given that within the airline
industry, M&A “is (currently) seen as a game-changer and mandatory to survive in aviation markets“ (Merkert
& Morrell, 2012), the following section aims to support the preceding valuation by analyzing the potential Air
Berlin holds as an acquisition target for Lufthansa - both before and after the two companies engaged in a wet
lease in 2016. A clear explanation of the wet-lease details is provided and an assessment of how this deal
affects the credibility of existing M&A rumors.
8.1. Introduction to M&A within the airline industry
M&A is neither a new discipline in the world economy nor in the airline industry. Apart from the specific
acquisition expectations surrounding Lufthansa and Air Berlin, consolidation within the European airline
industry is generally anticipated by many analysts and expects. Figure 3 in section 2 has shown that
profitability among airlines in Europe is still strongly lacking behind players in North America, mainly due to
a more intense competition. These statistics are further supported by Merkert and Morrell (2012), who state
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that M&A is one of few ways for airlines to grow at enhanced speed and also often the most effective way for
surviving in such competitive markets.
Generally, motives to engage in mergers or acquisitions are of various nature, though can be split into one of
two categories: Revenue enhancing or exploitation of cost synergies. The first of which is often associated
with an increase in growth, consolidation or attractiveness. The second by eliminating overlapping
departments, better use of resources or tax benefits (Maruna & Morrell, 2010). Thus, in order to achieve either
of these effects on the bottom line, deals are commonly pursued in anticipation of more efficient combined
operations, useful R&D, entrance to new markets, a strategic fit or a poor former management (Koller et al.,
2015; Roberts et. al, 2010).
In regards to the European aviation market, consolidation and M&A activities have been highly regulated and
often prohibited in order to maintain a competitive environment and ensure low prices for consumers. The
industry was deregulated in 2004 when the EU passed a new Merger Regulation (EU COM, 2004b). Until
then, Chang & Hsu (2005) argue that the only way to reap merger related benefits but still operate within
national laws and ownership regulations set by the Air Services Agreements, was to form strategic alliances.
These enabled airlines to coordinate flight schedules, and develop tools to utilize shared operations. However,
it is also argued that strategic alliances were only the second best solution and never unfolded their full
potential. While reasons vary, Chan & Hsu (2005) point towards conflicts of interest between entities as the
main obstacles. After the deregulation in 2004, a wave of mergers began within the European aviation industry,
strongly driven by Lufthansa, which was involved in five out of the nine merger cases between 2004 and 2009
(appendix 53). The new guideline welcome consolidation, as long as the Europe-wide competition level does
not suffer and the living standard of Europeans is not damaged.
8.2. M&A motives for commercial airlines
Recent history has shown that motives for airline companies to pursue mergers or acquisitions fall into one of
two categories - revenue enhancement and cost efficiency. However, the airline industry follows unusual
dynamics compared to other industries due to a unique asset structure and a dependency on national regulations
due to governmentally owned infrastructures (e.g. airports). Hence, the motives for M&A can be determined
more precisely. Merkert & Morrell (2012) are two of few researchers who have conducted a study focusing
explicitly on the aviation industry and analyzing commercial airlines' historic M&A motives as well as their
experienced merger benefits and disadvantages. Given the industry's dynamics, some deals are pursued simply
due to operational reasons like buying into specific airports through acquiring a target which holds slots there,
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or to expand a network and acquire targets to be feeder airlines (Merkert & Morrell, 2012). A drawback is
however that the integration of an entire airline or even only acquired routes/slots has also proven to be as
complex as the aviation industry itself.
Figure 30: The six main motives for M&A in the airline industry Source: Merkert & Morell (2012); own depiction
Throughout their study, Merkert & Morell (2012) have identified six main rationales for commercial airlines
to pursue mergers or acquisitions - depicted in figure 30. This framework will be used as the foundation to
analyze the potential Air Berlin holds as an acquisition target for Lufthansa - both before and after the two
companies engaged in a wet lease in 2016.
A critic towards the use of the framework could be that it has been conducted throughout 2012 and can be
considered slightly old. However, the history has not shown any cogent changes to disprove that the European
aviation industry has developed relatively conservatively over the last 5 years. Furthermore, as the research is
one of few studies committed specifically to the airline industry, the benefits of precise implications are
preferred over more current studies.
1. Rational: Increased efficiency and reduced costs
Airlines tend to engage in M&A if a projected combined company shows the potential to operate more
efficiently or has reduced costs than the separated companies. Gains in efficiency are commonly achieved by
any effort which facilitates better asset utilization. In the case of airlines mergers, the most obvious areas of
action are the utilization of fleets and networks, the reduction in overlapping departments and the increase in
load factors. Additionally, most significant cost savings can be achieved through cut-backs of the two major
Airline M&A
rationals
Increased efficiency and reduced
costs
Airport Slots & facilities
Access to aircrafts
EliminateCompetition
1
2
3
4
5
6
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cost accounts: Labor and Fuel. However, these are both to a great extend out of an acquirers direct control,
because oil prices are determined by the market and labor forces are usually strongly unionized, hence
implementing new employment conditions after an acquisition are often not possible. In light of these
challenges, Merkert & Hensher (2011) have conducted a more in-depth research, examining the most
significant levers to increase a target airlines' efficiency. Specifically, the authors have analyzed multiple
operating factors and their influence on airlines' cost efficiency. The most significant factor in successfully
impacting the costs of airlines is the fleet mix and therefore the number of different aircraft families within a
company's fleet, which will be further explained below in the analysis of Air Berlin.
2. Rational: Increased market share and revenues
A second motive to engage in M&A is common revenue enhancement through increased market share. As an
airline's main revenue source is passenger traffic, any effort in either increasing flight frequency, capacity or
load factors can have positive bottom-line effects. If a target company can fill holes in an airlines route network,
effects such as improved scheduling, an expanded product portfolio or new pricing strategies can increase
traffic and revenues. However, if possible, most merger benefits obtained through effects related to this rational
can also be achieved through forming strategic alliances.
3. Rational: Eliminate competition
A common rational for M&A within any industry is the elimination of competitors. Decreasing the level of
competition at airports, on specific routes or even throughout whole markets can have drastic effects on an
acquirer’s market power to charge higher yields, optimized schedules and operate more efficiently. The
common challenge for merging companies often lies in determining crucial areas of network overlap.
Additionally, the airline industry may also be one of few in which one player's bankruptcy enables multiple
competitors to enter drastically increase the competitive environment. As particularly the competition at
airports is limited by the slots available, avoiding a carrier's bankruptcy can prevent the market entrance of
additional competitors.
4. Rational: Access to airport slots and facilities
Chapter three of this report has explained that flight scheduling, times of departure as well as arrival and the
route itself are the most relevant and important forms of product differentiation for airlines. Some routes
playing an essential role in connecting markets likes e.g. London & New York or Paris & Singapore and hence
can be worth up to $16 million (Morrell, 2007). Hence, depending on the airports where a target has operations,
which slots it owns and which routes it services, acquisitions could potentially be a cheaper alternative in
obtaining profitable routes. Depending on the targets size, this is also a common way to not only acquire
individual routes but even to expand a network by a whole new hub.
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5. Rational: Access to aircrafts
One to the hurdles for airlines to grow rapidly is that traffic is dependent on available capacity and the
ownership of aircrafts. Despite options to lease or charter from competitors, the lead times to receiving new
aircrafts are at least to 2-3 years after order placement. Therefore, expansions into new markets often go hand
in hand with a prior takeover, as aircrafts and capacity are added to a fleet faster.
6. Rational: More attractive to customers
Lastly, expanding operations into additional markets and improving connections can benefit the attractiveness
of a carrier. Operating globally and ensure presence among the providers of flights to wherever a customer
may need to travel, increases incentives as well as benefits of loyalty programs and makes it easier for
passengers to gather miles. As the comfort level during traveling is strongly influenced by available amenities
and perks, merged carriers have the potential to raise customer experiences through more frequent transition
flights, seamless connections and lounges at more airports.
Risks:
In addition to Merkert & Morrell's (2012) rationales, the framework is extended with potential risk factors,
pitfalls and hypothetical disadvantages airline mergers can contain. Regulations and the industry dynamics
impose hurdles during the post-merger integration process and can hinder the realization of benefits. A
common factor of resistance in the integration process stems from labor unions or the employees themselves.
As the negotiation power of worker unions varies strongly between airlines, employment conditions are
similarly various between carriers. Therefore, at least one party's staff may cause problems during the
integration process, as either job loss or worse conditions are feared. Furthermore, fundamental differences in
corporate culture arise especially between international mergers, as would in e.g. a North American and Gulf
carrier deal. Recent history has also shown that the post-merger integration of airlines can be a timely process,
potentially lasting multiple years as additional hubs or elimination of overlapping departments may be
involved. Especially mergers pursued for reasons of cost savings or efficiency gains require extensive due
diligence regarding the potential costs of realizing benefits and the expected duration. Hence, factors
influencing M&A risks are: Target size, corporate culture, governance, worker unions and specifics regarding
the exact deal motive.
8.2.1. Lufthansa acquisition history
Since the liberalization and deregulation of the European aviation industry in 2004, Lufthansa realized the
most financial deals of all players - five within only the first five years. In order to understand the rational with
which the company considers M&A, key facts of a few significant deals are shortly outlined in the following:
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Lufthansa and Swiss Airlines in 2005: Its hub airport in Zurich is a slot-coordinated airport with high barriers
to entry for new airlines. The deal imposed two main hurdles, firstly, the target Swiss Airlines had joined the
rival alliance of Lufthansa, OneWorld, imposing multiple cultural as well as contractual problems due to code
sharing agreements. Secondly, Lufthansa already had a strong presence at Zurich's airport and the carriers'
operations overlapped on 64 point-to-point routes. After a lengthy analysis the European Commission had
strong doubts regarding 12 routes on which anti-competitive effects were anticipated - forcing Lufthansa to
surrender slots. After the approval, Lufthansa was able to eliminate airport specific competition and increase
its Europe-wide market share.
Lufthansa and bmi in 2009: The Lufthansa and bmi merger in 2009 is a prime example for a carrier acquiring
access to an airport through buying a company and incorporating its slots -in this case at Heathrow airport in
London. In contrast to the acquisition of Swiss, the European Commission quickly decided that bmi had no
essential connection with neither Lufthansa nor other Star Alliance members. Therefore, the deal and resulting
in elimination of bmi was not feared to impede the competitive environment.
Lufthansa and Austrian Airlines in 2009: Another acquisition by Lufthansa in 2009 was with the loss
making carrier Austrian Airlines, preventing potential bankruptcy. As a carrier's slots are reallocated by the
airport to the higher bidder, Lufthansa prevented the market entrance of multiple competitors and secured its
market share in the German speaking regions. However, the Commission fist rejected the inquiry as potential
efficiency gains and passed on saving in the form of lower ticket prices for consumers did not out the
anticompetitive effects of the merger. (EU COM, 2009a). The deal was only approved after Lufthansa gave up
a small number of routes and proved that the inclusion of Austrian Airline's point-to-point services had positive
network as well as efficiency effects on Lufthansa's operations (EU Com, 2009a).
8.3. Analysis of an acquisition of Air Berlin
In order to analyze the potential Air Berlin holds as a target for Lufthansa, an understanding is needed regarding
how as well as where the two carriers compete and what their relationship is. Both companies are German
airlines with a strong home market presence and overlapping Europe-wide services for short-haul flights.
However, Air Berlin is not considered a competitor of the Lufthansa Group, but rather of the group's LLC
segment Eurowings (formerly "Germanwings"). The routes serviced by Air Berlin and Eurowings overlap to
great extent, especially within the German home market. Figure 31 shows the competitive landscape of the
German LLC segment in which the two airlines are also the dominant market leaders. Beneficial for both
carriers was that Germany's LLC sector reached a volume record high in 2015. The nation's Aerospace Center
("Deutsches Zentrum für Luft- und Raumfahrt") tracked 518 routes operated by LLCs flying into or within
Germany. While Air Berlin shows stabile growth throughout recent years, Eurowings (former "Germanwings")
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received a large number of routes through a corporate restructuring of the Lufthansa group in 2014, due to
which the LLC segment took over multiple inner-European routes from the Lufthansa airline
(http://www.wiwo.de/unternehmen/dienstleister/billigflieger-markt-germanwings-erstmals-vor-air-
berlin/11825192.html). Also the prompt rebranding of Germanwings after the plane crash in March 2015
prevented the company from experiencing losses due to reputational damages. Indicated in figure 31, the
remaining competitive environment is defined by the top 7 airlines controlling 95% of the market (German
Aerospace Center, 2016). Figure 31: Number of flights in LLC segment per carrier; Jan. 2015 vs. Jan 2016 Source: German Aviation Center 82016); own depiction
8.3.1. Air Berlin's potential as an M&A target
In order to evaluate the potential Air Berlin held as an acquisition target for Lufthansa and to subsequently
determine the impact of the wet-lease on their consideration as a merger candidate, the airline itself as well as
its fit to Lufthansa is analyzed an in light of each of Merkert and Morrell’s (2012) main M&A motives.
1. Increased efficiency
During the recent decade the European LLC segment has been one of the toughest environments to operate in
profitably. As an industry already based on small profit margins, the extreme fluctuations of oil prices and the
global impact of the financial crises have put great pressure on carrier's bottom lines. Especially Eurowings
has struggled to prove itself financially up until 2016. While the carrier has achieved strong growth rates and
seized significant market shares, the financial bourdon of overhead costs on group level have resulted in
significantly higher unit costs than those of competitors like Ryanair or EasyJet. Thus, in order for any merger
candidate to be considered, benefits regarding cost efficiency and the outlook for potential cost savings need
to be observable.
In light of the tough environment, not only Eurowings struggled with efficiency problems. Many mergers
1833 1700
393 342
103 88 50 39 80 35
18441725
635
339130 84 56 39 38 36
0
500
1.000
1.500
2.000
Vuelling Aer Lingus Norwegian Air BalticEasyjet flybeWizzRyanairAir BerlinEurowings
2016
2015
0,6% 1,5% 61,5% -0,9% 26,2% -4,5% 12,0% 0,0% 2,9%Growth -52,5%
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which were formed due to the prospect of efficiency gains or cost savings have struggled severely in actually
realizing these benefits (e.g. Air France -KLM). In recognition of these struggles, R. Merkert & D.A. Hensher
(2011) have conducted a more in depth analysis of this M&A rational, examining the operating data of 58
passenger airlines in order to determine the influential factors for cost efficiency. The findings conclude that
the fleet mix operated by a carrier is a key determinant of an airline's successful cost management. A fleet mix
is defined by the number of different aircraft families operated. The authors have found higher recorded unit
costs for those carriers, which own multiple types of aircrafts or vehicles from multiple manufacturers (e.g.
both Boing and Airbus planes) (Merkert & Hensher, 2011). Ackert (2012) supports this view, as she highlights
significant economic and logistical benefits of solely operating one aircraft type. The communality among
aircrafts in a fleet lowers operating costs as the overall downtime is reduced and asset utilization is increased.
Operating aircrafts of one family reduces the quantity and variety of spare parts needed and standardizes
maintenance procedures as well as cabin crew training and safety procedures. The correlation between
efficiency and fleet mix potentially explain why the more profitable LLC players such as Southwest and
Ryanair strictly maintain a one aircraft policy (Boing 737). Figure 32: Fleet mix of Eurowings and Air Berlin pre lease agreement Source: Planespotter, 2016; skift, 2016; own depiction
In light of Air Berlin's potential to improve Eurowings cost efficiency through a more homogeneous fleet mix,
figure 32 above shows the operated aircrafts of both carriers throughout 2016.Included in Eurowings' fleet are
already the 49 aircrafts, which are to be added in 2017 through acquisition of Brussels airlines. As the
acquisition of Brussels airlines was already in announced, prior to the wet-lease with Air Berlin these aircrafts
are considered in the rational (Schaal, 2016). Both carriers depict a heterogenic fleet mix with a dominance of
aircrafts from the A320 family. The figure shows that Eurowings focus on rapid growth has not allowed them
to be selective with the aircrafts added to its fleet, as over one fourth of the carrier's fleet mix is strongly
heterogenic. In comparison to LLC competitors following a one-aircraft-type policy, the fleet mix of both, Air
Berlin and Eurowings seem very inefficient. Despite the overlap A320 aircrafts, the remaining vehicles in each
of the players' fleets do not match, as both operate A330s, but Eurowings also flies regional Canadair CRJ-
79
80
15915
1429
11
0 11
1
16 17
0
17 17
Eurowings* Air Berlin Combined
A3320** A330 Canadair CRJ-900 B737*** Bombardier
233127
106
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900, while Air Berlin operates many Boing 373s and Bombadier aircrafts. Hence, a full acquisition of Air
Berlin would result in a more heterogeneous fleet mix as the share of A320s would decrease from 75% to 68%.
Accordingly, in terms of efficiency acquiring Air Berlin as a whole would only decrease operational efficiency.
2. Increased market share and revenue
The underlying incentives of acquiring Air Berlin due to this motive are the ability to better align schedules as
well as routes. A seamless network creates opportunities to bundle services and could enable Eurowings to
capture a larger portion of revenue as well as to improve the company's pricing strategy. While Merkert &
Morell's (2012) indicate that most of these benefits can also be achieved through strategic alliances, the fact
that Lufthansa is a member of Star Alliance and Air Berlin of OneWorld, excludes this possibility between the
two carriers. Hence a merger is the only way to reap these benefits.
As shown in figure 32, an acquisition of Air Berlin would lift the company to be the clear no. 3 in the market
in terms of fleet size. With 233 aircrafts, Eurowings would only trail Ryanair (357 jets) and EasyJet (256) and
clearly distance themselves from the remaining smaller carriers. The consolidation and elimination of a
competitor especially at popular European and German airports would enable carriers to charge higher prices
and increase their pressured profit margins. Furthermore, an increase in fleet size and number of passengers
transported can also benefit the company's cost efficiency. One of reasons why Eurowings trails its competitors
in terms of unit costs is the bourdon of high fixed costs on group level. A larger fleet size would enable the
subsidiary to distribute costs across more operations, enabling effects of economies of scale.
3. Eliminate competition & 4. Access to airport slots
Competition within the European as well as the German aviation industry is commonly known as intense. With
Air Berlin and Lufthansa as the largest players of their home market, their overlap on routes and rivalry for
profitable slots is strong. The competition between the two is mainly concentrated at airports where both
players operate, thus in Düsseldorf, Berlin, Hamburg, Munich and Cologne. Figure 33 below shows the most
frequently flown routes within Germany and the respective frequencies with which both players service these
routes per week. These are Düsseldorf – Munich, Hamburg – Munich, Frankfurt – Berlin, Munich – Berlin
und Cologne/Bonn – Munich. The two carriers are dominant market leaders on these routes with a combined
total of more than 1.300 flights per week.
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Figure 33: Flight frequency on Germany's main air transportation routes in 2013; Lufthansa vs. Air Berlin Measure: Number of flights per average December week Source: Handelsblatt Research Institute (2014); own depiction
An acquisition of Air Berlin based on the two carriers' competition within their home market would fulfill
multiple purposes. Firstly, Lufthansa could eliminate its strongest rival within Germany and immensely
strengthen its market power at important hub airports. Following an acquisition, flight frequency could be
reduced in favor of improving load factors and raising productivity on theses business routes. If Eurowings
were to take over the routes, a potential efficiency gain could further benefit its unit costs. The lower level of
competitiveness also enables revenue enhancements through increased yields and a stronger footprint in the
carrier's home market. Secondly, even more important than improving the competitive situation, Lufthansa
would prevent LLCs such as Ryanair and EasyJet to simultaneously enter the market in case of Air Berlin's
bankruptcy. Since the company's IPO in 2006 Air Berlin has only had one year with financial profitability and
has costed its major shareholder Etihad $1,27bn in losses throughout the last three years. Etihad's plan to use
Air Berlin as a feeder airline for its global network has failed with the company planning on stopping any form
of funding in the future (Weiss & Kirchfeld, 2016). If Etihad puts its threat into effect and freezes future
funding, it is unlikely that Air Berlin could keep up operations. In this case, previously owned start and landing
slots would be reallocated by airports and most likely in a way that fosters competition. Thus, acquiring Air
Berlin would eliminate a direct competitor, but more importantly prevent multiple LLCs such as Wizz, Condor,
Ryanair or EasyJet to claim profitable routes and enter the competition.
5. Access to aircrafts
After announcing the rebranding of Germanwings into Eurowings, Lufthansa expressed its ambitions to
quickly grow its newly formed LLC segment into the third largest European player. Initially, one of the most
problematic hurdles in the process has been the access to a sufficient number of aircrafts. Despite options to
lease or charter vehicles from other players, the lead times to receiving new aircrafts are estimate to be a
minimum of 2-3 years after order placement. Furthermore, the group's orderbook for new aircrafts regarding
2017, 2018 and 2019 is already multiple times as high as the years before. As explained in rational 2 of this
section, acquiring the fleet of Air Berlin would bypass this hurdle and automatically lift Eurowings fleet into
the aspired range. However, while the benefits for additional access to aircrafts mirror those expressed in
rational 2, the drawbacks and concerns mirror those expressed in rational 1. Obtaining Air Berlin's fleet would
Frankfurt <-> Berlin Hamburg <-> Munich Munich <-> Berlin Düsseldorf <-> Munich Cologne/Bonn <-> Munich
Lufthansa 218 182 172 154 126
Air Berlin 66 92 130 114 70
218
182 172154
126
6692
130114
70
0
50
100
150
200
250
Lufthansa
Air Berlin
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meet growth aspirations, however the tradeoff lies within cost efficiency as the resulting fleet mix would
increase in heterogeneity and hence put even more pressure on the already above average unit price of
Eurowings.
6. More attractive to customer
In cases where airline mergers result in the target being incorporated so that the brand does not continue to
exist, brand reputation and customer attractiveness are not a deciding factor (Merkert & Morrell, 2012). While
acquiring Air Berlin could have indirect influence customer attractiveness through improved product offerings
or more seamless routes, this rational is not seen as deciding as the operations would be incorporated by
Eurowings and the brand eliminated.
Risks:
While occasionally the motives for airlines to mergers can be as simple as acquiring slots at specific airports
(IGA/bmi at Heathrow) or to expand a route network (Air France/KLM) (Merkert & Morrell, 2012)
successfully post-merger integrating companies can be as complex as the aviation industry itself. Multiple
studies have shown that mergers disappoint more often than not due to poor integration efforts. Regardless of
the means of measurement (stock price, growth, revenues, cost efficiency), the largest proportion of mergers
fall short of targets. As reasons can be specific and various, the following examines the three most relevant
risks as well as hurdles for a potential acquisition of Air Berlin. Due to the nature of the risks, they are assumed
to be relevant for both pre- and post wet lease scenarios.
Firstly, the regulatory concern from competition authorities. As Lufthansa has already dealt with competition
authorities in multiple of its prior mergers outlined in section 8.4 of this report, a potential acquisition of Air
Berlin is expected to be no different. Approval of airlines mergers are dealt with on a case-by-case basis and
consider on the one hand the effects on the resulting route network and on the other hand the resulting level of
competition on routes involved (Iatrou & Oretti, 2016). It is almost certain that a full acquisition of Air Berlin
will receive push back and will not be approved as in full. The questions of interest are how many routes and
which one in particular will authorities demand Lufthansa to give up in order to receive approval. A beneficial
factor for Lufthansa, is that authorities generally consider if a potential target will survive on its own (Iatrou
& Oretti, 2016). As bankruptcy of Germany's second largest airline will impact the society and economy
through job loss, decrease in competition, loss of services and ultimately lower consumer's living standard,
Etihad's resistance to further fund the struggling carrier could be beneficial for Lufthansa in potential
negotiations.
Secondly, cross boarder challenges as in the case of Alitalia/KLM (2000) typically impose severely hurdles to
the post-merger integration process. These factors are often defined by cultural, political and language
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differences (Iatrou & Oretti, 2016). As both companies originate from Germany, operate in the same
environment and have a largely similar domestic labor force, the risks associated from these obstacles are low.
However, future collaborations can also be affected by alliance memberships. A prospect of future cooperation
is often considered smoother between companies which have already cooperated, as both trust as well as
compatibility of operations have already been established. Despite Lufthansa's and Air Berlin's affiliation to
competing alliances, the intercultural similarities are assumed to provide only small hurdles in the integration
process.
Thirdly, labor issues resemble one of the largest difficulties for airline mergers (Iatrou & Oretti, 2016). The
staff is a key factor in creating or destroying value for airlines and is measured on multiple levels. The first
level is the general acceptance of the merger. Employee satisfaction after mergers strongly depends on the
development of individuals working conditions due to the fusion of contract schemes and if these either
improve or deteriorate. The second level is worker unionization. Air Berlin’s employees are strongly
unionized, similarly to those of Lufthansa. Since 2012 the company has been in the news repeatedly due to
ongoing conflicts with worker unions. During this time period, pilots have gone on strikes 29 days, causing an
estimated 14.900 flights with 1,8m passengers to be cancelled. Also, staff unions of target companies have
historically prevented multiple deals, at least since the Iberia/BA merger in which the labor force was a massive
hurdle during the integration process. As labor costs are by far one of the highest cost elements and the largest
internal factor pressuring a carrier’s profitability, any airline merger should show potential to improve this cost
element through eliminating redundancies and lowering staff costs (Merkert and Morrell, 2012). Considering
Lufthansa's history with labor unions and the fact that only agreements with the pilots are outstanding until
labor-related issues are momentarily put aside, it is questionable if the group is willing to risk incorporating an
additional unionized labor force.
9. Impact of 2016 wet lease with Air Berlin on acquisition consideration
9.1. Overview of deal
In the end of September 2016, The Deutsche Lufthansa AG and Air Berlin PLC signed an agreement by which
38 aircrafts from Air Berlin are to be wet-leased to Lufthansa. Beginning with the delivery of the first aircraft
in February 2017, the contract is signed over a period of six years. The announcement entails that Lufthansa
intends to use 33 of the aircrafts for its Eurowings' fleet and operate the remaining 5 through its subsidiary
Austrian Airlines. On December 16th 2016 the deal went into the next phase as the execution and rebranding
was initiated, leaving the deal only conditional to receiving approval from the governing institution, the
German "Bundeskartellamt" (Air Berlin, 2016b). The final assessment if the deal meets regulatory
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requirements had not been published by the end of 2016, however analysts expect the unconditional approval
early in 2017 as the aircrafts' lease have a limited duration.
Further entailed in the deal are multiple specifics regarding the division of operational procedures between Air
Berlin in Lufthansa. Accordingly, Air Berlin remains owner of the aircraft implying the responsibility for
maintenance, insurance and overhead services (Air Berlin, 2016b). As compensation, Air Berlin is receiving
$1,2bn from Lufthansa, which is paid over the entire duration of the contract. Despite the compensation, Air
Berlin remains responsible to provide pilots, on board crew, maintenance, aircraft insurance and administrative
services. In turn, Eurowings and Austrian Airlines take over the financial accountability. The two Lufthansa
subsidiaries will rebrand the aircrafts and take over expenses such as fuel, catering, ticket sale, airport fees for
the slots as well as taxes. The deal relieves Air Berlin from multiple financial losses and liabilities (N-TV,
2016).
The question arises which intention both players follow and why they have initiated this deal. For Air Berlin,
the lease of 38 A320 aircrafts to its competitor Lufthansa is only a small part in a far-reaching current
restructuring. The carrier is additionally reducing its fleet by another 33 aircrafts through spinning off the joint
ventures with Nikki and Tuifly. Air Berlin's fleet will be reduced to a total of 75 aircrafts of which 17 are of
the A330 family, 40 A320s and 18 Q400 turboprops (Schlappig, 2015). In light of a new corporate strategy
and with a fleet only half the size of before, Air Berlin is able to thin down its staff overhead by laying off
1.200 employees. The intention for the future is to abandon the concept of servicing randomly selected leisure
destinations and focus on becoming a European high-yield network carrier. Thus, after completing all
anticipated deals, the company will retreat from the airports Hamburg, Paderborn, Cologne, Frankfurt and
Leipzig (N-TV, 2016). Thus, the intended strategy aiming at high-yield business travel within Germany as
well as to and from Italy, Scandinavia and Eastern Europe will be solely pursued from the airports Düsseldorf
and Berlin. The only German destinations will be in Stuttgart, Munich and Nurnberg. Additionally, the
company kept selected profitable long-haul routes to North America which will continue to be operated. The
public market and analyst opinion towards the restructuring has overall been positive. Analysts have rewarded
the company for formulating and expressing a vision regarding its future for the first time in several years.
Concerning Lufthansa, the company strongly benefits from the deal, as its main role lies in taking over
additional aircrafts. The largest benefit is that through leasing the aircrafts, Lufthansa avoids Air Berlin
engaging in a deal with a direct competitor such as Ryanair or EasyJet. Thus it preventing rivals to gain
excessive growth and market share. Secondly, the 33 aircrafts allocated to Eurowings, strongly lift the
subsidiaries fleet size without almost any additional financial risks. Through the inclusion, Eurowings has
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achieved its goal of becoming the thirst largest European LLC much faster than expected (Thomson Reuters,
2016). Specifically, the airports at which Lufthansa takes over routes additional routes from Brussels Airlines
and Air Berlin are Hamburg (increase of 11 routes year-round; 12 seasonal), Stuttgart (11 & 13), Zurich (12
& 15), Cologne (10 & 6), and Munich (13 & 26). However, regarding the aircrafts and slots leased from Air
Berlin, it is important to note that Lufthansa does not have ownership rights. The company is purely operating
them - currently for a length of at least 6 years. Nevertheless, the retreat of Air Berlin from these airports, even
if it is only these 6 years, will still have great impact on the competitive environment for both Lufthansa and
its respective subsidiaries.
9.2. Effect of the lease agreement on acquisition rationales
The wet-lease agreement between Air Berlin and Lufthansa impacts Air Berlin's above assessed potential as
an acquisition target for Lufthansa on multiple levels. Based on the 6 different acquisition rationales, Air
Berlin's attractiveness prior to the lease agreement lied in the slots the company held, its ability to increase
Lufthansa's market share and the provision of additional aircrafts. Considering Air Berlin's extensive corporate
restructuring, including e.g. the spin-off of Niki, the company's attractiveness for Lufthansa has likely changed.
Thus, the analysis below will follow the identical framework as before in order to asses Air Berlin's current
attractiveness as an acquisition target for Lufthansa.
Increased efficiency
In terms of efficiency, Air Berlin's fleet had limited attractiveness for Lufthansa, as an inclusion of the all
assets would have caused more heterogeneity among Eurowings' aircrafts. As the dominantly operated aircraft
family was the A320 a full acquisition would have caused the share of A320s to decrease from 75% to 68%
and thus implying negative efficiency implications for the LLC's operations. Consequently, the agreement to
solely lease A320s, results in a significantly improved fleet mix of Eurowings. As greater homogeneity of a
fleet is correlated with efficiency enhancements, Eurowings is taking necessary steps in closing the profitability
gap between itself and the leading competitors Ryanair and EasyJet. Simultaneously to the lease-agreement,
Air Berlin sold 33 further aircrafts through the spinoff of its joint ventures with Nikki and Tuifly.
Consequently, Air Berlin's current ability to further improve Eurowings efficiency lies in its effects on the
LLC's fleet homogeneity.
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Figure 34: Fleet mix of Eurowings and Air Berlin post lease agreement Source: Schlappig, 2015; Own creation
The carrier's remaining fleet for 2017 has a size of 75 aircrafts, including 17 Airbus A330 aircraft, 40 A320
family aircraft, 18 Q400 turboprop aircraft. With 40 A320s out of 75 aircrafts, about half of the remaining
company would fit into the Eurowings fleet mix. While Eurowings is currently divesting the often too large
A330s, the 17 additional aircrafts of Air Berlin are of questionable attractiveness. Nevertheless, as one quarter
of the remaining fleet raises severe doubts towards the attractiveness. Eurowings was up until the lease-
agreement Lufthansa's only subsidiary with a growth strategy, thus the aircrafts will unlikely be allocated to
other carriers. Furthermore, Ackert (2012) has found that the secondary market prospects for aircrafts has
significantly decreased over time. Small aircrafts not from either of the leading manufacturers, Airbus or
Boing, tend to be less marketable and have lower value retention. Thus, Lufthansa would either need to sell
the undesirable vehicles potentially below market value or include operate them under Eurowings and accept
potential drawbacks in efficiency. However, the subsidiary achieved the main growth targets of being the third
largest European LLC through the acquisition of Brussel Airlines and the lease-agreement. As mentioned
above, it is obligatory for Eurowings' efforts to focus on unit cost reduction and narrowing the profitability gap
between itself and the leading competitors. Hence, the disadvantages of creating a more heterogeneous fleet
would outweigh the benefits of growth through additional aircrafts.
Increased market share & Access to aircrafts
Due to the financial transactions conducted in late 2016, Eurowings is facing a strong multi-brand integration
challenge through integrating aircrafts from Air Berlin and Brussels Airlines. With 139 aircrafts, the carrier
has clearly grown to the third largest European carrier behind Ryanair (357 jets) and EasyJet (256 aircrafts).
Prior to the acquisition deals, the low cost segment was Lufthansa's branch with a growth strategy. However,
due to achieved growth targets, multi-brand integration and the Germanwings rebranding, Eurowings is
currently likely to refrain from further acquisitions. The group's network carriers' strategies and especially the
Lufthansa brand are not growth oriented, but rather focus on improvements in efficiency as well as customer
112
40
152
15
1732
11
0 11
1
0 1
0
18 18
Eurowings* Air Berlin Combined
A320** A330 Canadair CRJ-900 B737*** Q400 Turboprop
22475
139
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experience. Hence, through the occupation with brand integration and absent growth strategies, Lufthansa's
motivation to increase market share or gain access to Air Berlin's fleet is most likely low.
Eliminate competition & Access to airports & facilities
Section 8.4 outlines how Air Berlin holds a specific degree of potential as an acquisition target as it would
provide Eurowings access to large German airports, extend the carriers domestic network, eliminate a
competitor and prevent other rivals from entering. However, the lease agreement has already captured many
of these benefits and Air Berlin's restructuring has further impacted its current attractiveness for Lufthansa.
The LLC has leased all landing slots at the airports in Hamburg, Paderborn, Cologne, Frankfurt and Leipzig
to Brussels Airline and Eurowings. Thus of the five most frequently serviced German routes, where Lufthansa
and Air Berlin were the main competitors, the lease agreement has eliminated Air Berlin from 3 of these,
strongly increasing Lufthansa's market share.
Consequently, in regards to this rational, Air Berlin's attractiveness for Lufthansa depends on the group's desire
to service Cologne/Bonn – Munich and Munich – Berlin. the first of which, is a route Eurowings begins to
service starting 2017, thus eliminating competition and gaining more slots would benefit the market position.
The second however connects airports which Eurowings does not serve and also the group's network carriers
are not considering growth. While an acquisition would favor the Lufthansa airline, the group has express the
strategy for its network carriers to concentrate operations on its hub airports in order to decrease overhead
costs and increase efficiency on group level. Furthermore, the restructuring efforts of Air Berlin have also
decreased the companies default probability. This dampens the acquisition rational of preventing rival carriers
to bidding for landing slots in case of bankruptcy. Overall, through the lease-agreement Air Berlin does not
compete with Lufthansa on many routes any more, through which it holds little potential to be a target
Lufthansa would acquire in order to eliminate competition or receive specific airport slots.
More attractive to customers
As stated above, the brand Air Berlin and the company's operations would be incorporated by Eurowings and
the brand would be eliminated. In cases where the targets brand does not continue to exist, brand reputation
and customer attractiveness are not a deciding factor.
Consequently, the lease-agreement has already fulfilled motives for Lufthansa to acquire Air Berlin. Firstly, a
large portion of the only desirable aircraft type in Air Berlin's fleet is now already in possession, increasing
Eurowings' fleet homogeneity and thus potentially increasing the carrier's future efficiency. Secondly, a
competitor at multiple domestically important airports has been eliminated and a hypothetical growth
opportunity for Ryanair as well as EasyJet has been abolished. Lastly, Eurowings has grown and will likely
establish itself as the third largest player. While an acquisition shows slight potential driven by the rationales
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increased efficiency and access to airport slots, the overall remaining assets of Air Berlin after its restructuring
efforts in 2016 do not provide lucrative incentives for Lufthansa to consider M&A.
Figure 35: Attractiveness to acquire Air Berlin evaluated per rational; scale 0-5 Source: Own creation
10. Conclusion
The ultimate goal of this report is to provide the marginal investor with a thorough strategic as well as financial
analysis of the Lufthansa group enabling a recommendation whether to buy, sell or hold the stock of Deutsche
Lufthansa AG on 30.12.2016. Beginning with an industry analysis, this report has shown that the fragmented
and highly competitive environment for European carriers is one of the main reasons these players trail North
American airlines in their ability to generate profits. After experiencing financial struggles throughout 2014,
the Lufthansa group inaugurated a new CEO and introduced a new corporate strategy. One of the main changes
was the shift of focus towards the European LLC market. Since then a predominant share of the total
investments and available capital have been allocated to growing the Eurowings brand. Executed through the
rebranding of Germanwings, the takeover of Brussels Airlines and the wet-lease with Air Berlin, Eurowings
will operate as the third largest European LLC player as of 2017, strongly increasing the group's footprint in
its domestic market Germany.
The financial analysis has revealed that the company's returns resemble the industry's typical volatility. Further
analysis has revealed that labor related costs have historically been the main reason for the carrier's lack in
efficiency compared to its peer group. However, throughout 2015 and 2016, wage agreements have been
0
1
2
3
4
5Increased efficiency
Increased market share and revenue
Eliminate competition
Access to airport slots and facilities
Access to aircrafts
More attractive to customer
Before wet lease
After wet lease
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reached with the worker unions ver.di and UFO, which comprise 30,00 ground staff employees and a
predominant share of the group's cabin crew employees. The collective labor agreements are expected to
decrease costs in relation to salaries, pensions and benefits as of 2017. Together with accompanying efficiency
enhancing initiatives, the group-wide EBIT margin is expected to improve as of 2016. Nonetheless, partial
benefits of the continued decrease in fuel prices are expected to pressure unit yields as fuel cost savings are
forced to be passed on to customers, resulting in a short term decrease in group wide revenues. The carrier's
aircraft renewal program as well as the large additions to the fleet are further expected to cause a slightly
diminishing 2017 load factor. However, in the medium and long run, Lufthansa is expected to fill the added
seats better, due to which traffic revenue and EBIT will normalize in growth.
The applied DCF-valuation model has derived at an estimation for the Deutsche Lufthansa AG's fair share
price of 18,41€. As the stock is trading for 12,27€ on the valuation date, this report suggests that the market
currently undervalues Lufthansa's stock. The model's result has been triangulated by comparing the results
with an additionally applied EVA model, a sensitivity analysis as well as a relative valuation based on
multiples. The sanity check through the EVA model has validated the valuation mechanics. The result of the
relative valuation through forward-looking EV/EBITDA multiples supports the general tendency of the DCF,
however it implies a more significant undervaluation than the present value model. Potential explanations as
to why the outcomes of the two models differ with each other and with the market's price can lie in either
method. The sensitivity analysis has identified that the valuation result is especially sensible to estimated
components of the WACC such as carrier's the beta as well as the applied market risk premium. Also the
estimation of how the observed 2016 oil price developments translates into actual total fuel costs, including
hedging effects, have a large effect on the overall implied valuation result.
Because consolidation of the European market is heavily awaited and rumors of Lufthansa planning to acquire
Air Berlin are currently publically discussed, it has been reasoned that an additional qualitative analysis of the
potential strategic and synergetic fit between these two German companies is relevant for the marginal
investor. Section 8 and 9 of this report outline that Air Berlin resembles limited strategic as well as synergetic
fit. The further analyses of the carrier's potential as acquisition target both before and after the wet-lease have
revealed that through the transfer of the 38 A320 aircrafts, the only previously attractive assets for Lufthansa
have already been received. Thus, from a strategic as well as synergetic perspective, any further acquisition
rumors have been reasoned to be non-credible.
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Page ½ I
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12. Appendix
List of Figures Source: Own creation
Figure 1: Value of the global airline industry (2011 - 2015) .................................................... 8
Figure 2: Leading airlines worldwide in December 2015, based on revenue passenger
kilometers (in billions) ................................................................................................................. 9
Figure 3: System average fuel price (US Carriers) and fuel spot price 2009 – 2015 ........... 11
Figure 4: Top 20 European airlines ......................................................................................... 14
Figure 5: Herfindahl-Hirschman Index by region .................................................................. 15
Figure 6: Regional forecasted 2016 profit margins vs HHI ................................................... 15
Figure 7: Segmentation of the European and German airline market ................................. 16
Figure 8: Lufthansa's business segments and respective share of revenue .......................... 18
Figure 9: Performance of the Lufthansa share 2015-2016 relative to peer group and DAX;
indexed 01.01.2015 ..................................................................................................................... 21
Figure 10: SWOT analysis of Deutsche Lufthansa AG .......................................................... 26
Figure 11: Du Pont Model ......................................................................................................... 32
Figure 12: Peer group return on equity (2010-2015) .............................................................. 33
Figure 13: Peer group return on invested capital(2010-2015) ............................................... 34
Figure 14: Peer group profit margins (2011 - 2015) ............................................................... 35
Figure 15: Peer group EBITDA margins (2011 - 2015) .......................................................... 35
Figure 16: Peer group comparison of traffic revenue, ASKs and load factor ...................... 37
Figure 17: Operational drivers of labor expenses to revenue, 2015 ...................................... 39
Figure 18: Peer group current ratios (2010-2015) .................................................................. 40
Figure 19: Peer group financial leverage (2010-2015) ............................................................ 41
Figure 20: Revenue growth in comparison to GDP and Iata estimates ................................ 43
Figure 21: Oil price projections and fuel cost estimates ........................................................ 48
Figure 22: Calculation of Lufthansa's country specific risk .................................................. 52
Figure 23: WACC calculation comparison .............................................................................. 55
Figure 24: Valuation based on DCF model ............................................................................. 56
Figure 25: Valuation of Lufthansa based on the EVA-method ............................................. 58
Figure 26: Sensitivity analysis WACC & terminal growth .................................................... 58
Figure 27: Sensitivity of MRP, Beta and 2016 oil price development ................................... 59
Figure 28: Relative valuation model ........................................................................................ 60
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Page ½ IX
Figure 29: Implied share price through enterprise and pricing multiples .......................... 62
Figure 30: The six main motives for M&A in the airline industry ....................................... 65
Figure 31: Number of flights in LLC segment per carrier; Jan. 2015 vs. Jan 2016 ............ 69
Figure 32: Fleet mix of Eurowings and Air Berlin pre lease agreement .............................. 70
Figure 33: Flight frequency on Germany's main air transportation routes in 2013;
Lufthansa vs. Air Berlin ............................................................................................................ 72
Figure 34: Fleet mix of Eurowings and Air Berlin post lease agreement ............................. 77
Figure 35: Attractiveness to acquire Air Berlin evaluated per rational; scale 0-5 .............. 79
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Page ½ X
Appendix 1: Regional overall capacity growth vs GDP growth Source: Oliver Wyman (2016); Planestats.com
Appendix 2: Lufthansa Strategy „7to1- Our way Forward“ Source: Lufthansa, 2016
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Page ½ XI
Appendix 3: The setup of the Lufthansa Group: three strong pillars Source: Lufthansa, 2016
Appendix 4: Performance of the Lufthansa share 2015, indexed 01.01.2015, relative to peer group and DAX Source: Bloomberg; own depiction
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Page ½ XII
Appendix 5: Performance of the Lufthansa share 2016, indexed 01.01.2016, relative to peer group and DAX Source: Bloomberg; own depiction
Appendix 6: Performance of the Lufthansa share 2015-2016, indexed 01.01.2016, relative to European peer group Source: Bloomberg; own depiction
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Page ½ XIII
Appendix 7: Lufthansa analytical income statement Source: Relevant annual reports, own depiction
Analytical Income Statement
For the Fiscal Period Ending Dec-31-2011 Dec-31-2012 Dec-31-2013 Dec-31-2014 Dec-31-2015 Currency EUR EUR EUR EUR EUR Marginal tax rate 25% 25% 25% 25% 25%
TrafficRevenue 23.779 24.793 24.565 24.388 25.322
OtherRevenue 4.955 5.342 5.463 5.623 6.734
TotalRevenue 28.734 30.135 30.028 30.011 32.056
Fuel -6.276 -7.392 -7.058 -6.751 -5.784
Rawmaterials -2.127 -2.157 -2.212 -2.252 -2.670
Sellingandadminexpenses -8.189 -8.284 -8.082 -8.068 -8.983
Staffcosts -6.678 -6.741 -7.350 -7.335 -8.075
Otheroperatingincome 2.324 2.785 2.042 1.890 2.832
Otheroperatingexpenses -5.293 -4.885 -4.753 -5.088 -6.106
TotalCostsofGoodsSold -26.239 -26.674 -27.413 -27.604 -28.786
GrossProfit 2.495 3.461 2.615 2.407 3.270
Resultfromequityinvestments 71 94 125 121 121
EBITDA 2.566 3.555 2.740 2.528 3.391
Depreciation,amortisationandimpairment -1.722 -1.839 -1.766 -1.528 -1.715
EBIT 844 1.716 974 1.000 1.676
Taxasreported -157 -91 -219 -105 -304
Tax shield -72 -93 -86,5 -64 -42,5
NOPAT 615 1.532 669 831 1.330
interestincome 190 168 162 159 186
interestexpenses -478 -540 -508 -415 -356
Otherfinancialitems -110 -48 -83 -564 520
Taxshieldoninterest 72 93 87 64 43
NetFinancialResult -326 -327 -343 -756 393
Discontinuedoperations -285 36 0 0 0
NetEarningsaftertax 4 1.241 326 75 1.722
Minorityinterest -17 -13 -13 -20 -24
NetProfit -13 1.228 313 55 1.698
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Page ½ XIV
Appendix 8: Lufthansa analytical balance sheet Source: Relevant annual reports, own depiction
Analytical Balance SheetBalance Sheet as of: 2011 2012 2013 2014 2015Currency in mEUROperationalAssetsCurrentassetsInventories 887 639 641 700 761Tradereceivablesandotherreceivables 3.111 3.595 3.577 3.995 4.389Deferredchargesandprepaidexpenses 2.838 151 146 147 158Effectiveincometaxreceivables 727 101 72 122 85TotalCurrentAssets 7.563 4.486 4.436 4.964 5.393Non-CurrentassetsIntangibleassetswithanindefiniteusefullife 1.191,0 1.193,0 1.188,0 1.197,0 1.235,0 Otherintangibleassets 384,0 375,0 381,0 390,0 422,0 Aircraftandreserveengines 11.592,0 11.838,0 12.354,0 13.572,0 14.591,0 Repairablesparepartsforaircraft 840,0 899,0 959,0 1.083,0 1.388,0 Property,plantandotherequipment 2.118,0 2.081,0 2.058,0 2.109,0 2.173,0 Investmentsaccountedforusingtheequitymethod 394,0 400,0 458,0 445,0 520,0 Deferredchargesandprepaidexpenses 24,0 25,0 16,0 11,0 12,0 Effectiveincometaxreceivables 60,0 52,0 39,0 31,0 19,0 Deferredtaxassets 33,0 755,0 622,0 1.489,0 1.200,0 TotalNon-CurrentAssets 16.636 17.618 18.075 20.327 21.560TotalOperatingAssets 24.199 22.104 22.511 25.291 26.953
OperationalLiabilitiesCurrentLiabilitiesOther provisions 818,0 894,0 861,0 953,0 1.075,0 Liabilities from unused flight documents 2.359,0 2.612,0 2.635,0 2.848,0 2.901,0 Advanced payments received, deferred income and other non-financial liabilities 939,0 933,0 961,0 924,0 918,0 Effective income tax obligations 71,0 107,0 247,0 228,0 136,0 TotalCurrentLiabilities 4.187 4.546 4.704 4.953 5.030Non-CurrentLiabilitiesOther provisions 578,0 582,0 581,0 601,0 526,0 Advance payments received, deferred income and other non-financial liabilities 1.156,0 1.163,0 1.187,0 1.179,0 1.223,0 Deferred tax liabilities 364,0 94,0 146,0 239,0 346,0 TotalNon-CurrentLiabilities 2.098 1.839 1.914 2.019 2.095Totalnon-interestbearingdebt 6.285 6.385 6.618 6.972 7.125Investedcapital(netoperatingassets) 17.914 15.719 15.893 18.319 19.828
FinancialLiabilitiesTotalEquity 8.044 4.839 6.108 4.031 5.845CurrentandNon-CurrentfinancialliabilitiesPension provisions 2.165,0 5.844,0 4.718,0 7.231,0 6.626,0 Borrowings 5.808,0 5.947,0 4.823,0 5.364,0 5.031,0 Other financial liabilities 128,0 198,0 148,0 136,0 121,0 Derivative financial instruments 55,0 150,0 426,0 719,0 307,0 Borrowings 616,0 963,0 1.514,0 594,0 1.339,0 trade payables and other financial liabilities 4.227,0 4.231,0 4.546,0 4.635,0 4.847,0 Derivative financial instruments 37,0 2,0 183,0 766,0 1.221,0 Liabilities related to assets held for sale 716,0 26,0 Interest-bearingdebt 13.752 17.335 16.358 19.471 19.492
FinancialassetsDerivativefinancialinstruments 144 215 460 456 440Securities 620 3.530 3.146 1.785 1.994Cashandcashequivalents 1.127 1.436 1.550 953 1.099Assetsheldforsale 110 71 89 10Otherequityinvestments 898,0 413,0 500,0 776,0 201,0 Non-currentsecurities 134,0 19,0 20,0 10,0 15,0 Loansandreceivables 616,0 464,0 491,0 515,0 516,0 Derivativefinancialinstruments 343,0 268,0 335,0 599,0 1.234,0 Interest-bearingassets 3.882 6.455 6.573 5.183 5.509Net-interest-bearingdebt 9.870 10.880 9.785 14.288 13.983Investedcapital 17.914 15.719 15.893 18.319 19.828
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Page ½ XV
Appendix 9: KLM analytical income statement Source: Relevant annual reports, own depiction
Analytical Income StatementFor the Fiscal Period Ending
Dec-31-2011 Dec-31-2012 Dec-31-2013 Dec-31-2014 Dec-31-2015Currency EUR EUR EUR EUR EURMarginal tax rate 25% 25% 25% 25% 25%
TrafficRevenue 24.363,0 25.423,0 25.520,0 24.912,0 26.059,0
OtherRevenue 39,0 16,0 10,0 18,0 3,0 TotalRevenue 24.402 25.439 25.530 24.930 26.062
Aircraftfuel (6.438,0) (7.278,0) (6.897,0) (6.629,0) (6.183,0) Charteringcosts (571,0) (551,0) (455,0) (438,0) (430,0) Landingfeesandenroutecharges (1.818,0) (1.832,0) (1.839,0) (1.840,0) (1.947,0) Catering (577,0) (591,0) (589,0) (591,0) (655,0) Handlinghargesandotheroperatingcosts (1.342,0) (1.368,0) (1.405,0) (1.476,0) (1.536,0) Aircraftmaintenancecosts (1.172,0) (1.131,0) (1.303,0) (1.729,0) (2.372,0) Commercialanddistributioncosts (847,0) (866,0) (852,0) (870,0) (896,0) Otherexternalexpenses (1.904,0) (1.706,0) (1.744,0) (1.598,0) (1.663,0) Saleriesandrelatedcosts (7.460,0) (7.662,0) (7.482,0) (7.316,0) (7.852,0) taxesotherthanincomecosts (191,0) (184,0) (186,0) (169,0) (167,0) Otherincomeandexpenses 110,0 73,0 (10,0) 188,0 1.113,0 Aircraftoperatingleasecosts (848,0) (949,0) (913,0) (873,0) (1.027,0) Salesofaircraftequipment 16,0 8,0 (12,0) 0 (6,0) salesofsubsidiaries 1,0 97,0 7,0 185,0 224,0 Othernon-currentincomeandexpenses (144,0) (500,0) (352,0) 695,0 81,0 TotalCOGS -23.185 -24.440 -24.032 -22.461 -23.316EBITDA 1.217 999 1.498 2.469 2.746
Amortization,depreciationandprovisions (1.697,0) (1.730,0) (1.725,0) (1.718,0) (1.631,0) EBIT -480 -731 -227 751 1.115
Taxasreported 245,0 (17,0) (957,0) (195,0) (43,0) Tax shield 0 (109,0) (120,3) (111,5) (93,3) NOPAT -235 -857 -1.304 445 979
interestincome 92,0 83,0 77,0 76,0 63,0 interestexpense(Costoffinncialdebt) (463,0) (436,0) (481,0) (446,0) (373,0) Foreignexchangegainslosses (116,0) 64,0 74,0 (199,0) (360,0) Changeinfairvalueoffinancialassetsandliabilities (66,0) 63,0 57,0 (92,0) (178,0) Otherfinancialincomeandexpenses 2,0 17,0 (28,0) (68,0) (67,0) Shareofprofitsofassociates (19,0) (66,0) (211,0) (39,0) (30,0) Taxshield 0 109 120 112 93NetFinancialResult -570 -166 -392 -657 -852
Netincomefromdiscontinuedoperations 0 (197,0) (122,0) (4,0) 0 NetEarningsaftertax -805 -1.220 -1.818 -216 127
Minorityinterest (4,0) (5,0) (9,0) (9,0) (9,0) NetProfit -809 -1.225 -1.827 -225 118
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Page ½ XVI
Appendix 10: KLM analytical balance sheet Source: Relevant annual reports, own depiction
Analytical Balance SheetBalance Sheet as of: 2011 2012 2013 2014 2015Currency in mEUROperationalAssetsCurrentassetsGoodwill 426,0 252,0 237,0 243,0 247,0 Intangible assets 774,0 842,0 896,0 1.009,0 1.018,0 Flight equipment 10.689,0 10.048,0 9.391,0 8.728,0 8.743,0 Other property, plant and equipment 2.055,0 1.932,0 1.819,0 1.750,0 1.670,0 Investments in equity associates 422,0 383,0 177,0 139,0 118,0 Deferred tax assets 1.143,0 1.151,0 436,0 1.042,0 702,0 Other non-current assets 168,0 152,0 113,0 243,0 295,0 TotalCurrentAssets 15.677 14.760 13.069 13.154 12.793Non-CurrentassetsInvetories 585,0 521,0 511,0 538,0 532,0 Trade accounts receivables 1.774,0 1.859,0 1.775,0 1.728,0 1.800,0 Other current assets 995,0 828,0 822,0 961,0 1.138,0 Income tax receivables 10,0 11,0 23,0 TotalNon-CurrentAssets 3.364 3.219 3.131 3.227 3.470TotalOperatingAssets 19.041 17.979 16.200 16.381 16.263
OperationalLiabilitiesCurrentLiabilitiesProvisions 156,0 555,0 670,0 731,0 742,0 Trade payables 2.599,0 2.219,0 2.369,0 2.444,0 2.395,0 Deferred revenue on ticket sales 1.885,0 2.115,0 2.371,0 2.429,0 2.515,0 Frequent flyer programs 784,0 770,0 755,0 759,0 760,0 Current tax liabilities 6,0 3,0 2,0 0 0 Other current liabilities 2.386,0 2.474,0 2.332,0 3.330,0 3.567,0
TotalCurrentLiabilities 7.816 8.136 8.499 9.693 9.979Non-CurrentLiabilitiesOther provisions 0 0 0 1.404,0 1.513,0 Deferred tax liabilities 466,0 431,0 178,0 14,0 11,0 Other non-current liabilitie 321,0 384,0 397,0 536,0 484,0 TotalNon-CurrentLiabilities 787 815 575 1.954 2.008Totalnon-interestbearingdebt 8.603 8.951 9.074 11.647 11.987Investedcapital(netoperatingassets) 10.438 9.028 7.126 4.734 4.276
FinancialLiabilitiesTotalEquity 6.094 4.980 2.290 -653 273CurrentandNon-CurrentfinancialliabilitiesPension provisions 2.061,0 2.287,0 3.102,0 2.119,0 1.995,0 Long-term debt 9.228,0 9.565,0 8.596,0 7.994,0 7.060,0 Liabilities relating to assets held for sale 0 0 58,0 0 0 Current portion of long-term debt 1.174,0 1.434,0 2.137,0 1.885,0 2.017,0 Bank overdrafts 157,0 257,0 166,0 249,0 3,0 Interest-bearingdebt 12.620 13.543 14.059 12.247 11.075
FinancialassetsPension assets 3.217,0 3.470,0 2.454,0 1.409,0 1.773,0 Other financial assets 2.015,0 1.665,0 1.963,0 1.502,0 1.224,0 Assets held for sale 10,0 7,0 91,0 3,0 4,0 Other short-term financial assets 751,0 933,0 1.031,0 787,0 967,0 Cash and cash equivalents 2.283,0 3.420,0 3.684,0 3.159,0 3.104,0 Interest-bearingassets 8.276 9.495 9.223 6.860 7.072Net-interest-bearingdebt 4.344 4.048 4.836 5.387 4.003Investedcapital 10.438 9.028 7.126 4.734 4.276
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Page ½ XVII
Appendix 11: IAG analytical income statement Source: Relevant annual reports, own depiction
Analytical Income StatementFor the Fiscal Period Ending Dec-31-
2011Dec-31-
2012Dec-31-
2013Dec-31-
2014Dec-31-
2015Currency EUR EUR EUR EUR EURMarginal tax rate 25% 25% 25% 25% 25%TrafficRevenue 14.672,0 16.589,0 17.231,0 18.817,0 21.374,0 OtherRevenue 1.431,0 1.528,0 1.338,0 1.353,0 1.484,0 TotalRevenue 16.103 18.117 18.569 20.170 22.858
Staffcosts (3.799,0) (4.579,0) (4.221,0) (4.585,0) (4.905,0) Fuel,oilcostsandemissionscharges (5.088,0) (6.101,0) (5.945,0) (5.987,0) (6.031,0) Handling,cateringandotheroperatingcosts (1.522,0) (1.805,0) (1.932,0) (2.063,0) (2.371,0) Landingfeesanden-routecharges (1.175,0) (1.278,0) (1.422,0) (1.555,0) (1.882,0) Engineeringandotheraircraftcosts (1.074,0) (1.285,0) (1.252,0) (1.276,0) (1.395,0) Property,ITandothercosts (903,0) (1.006,0) (927,0) (927,0) (1.033,0) Sellingcosts (740,0) (837,0) (785,0) (859,0) (912,0) Aircraftoperatingleasecosts (375,0) (425,0) (499,0) (551,0) (659,0) Currencydifferences (14,0) 0 (45,0) (221,0) (45,0) Totaloperatingexpenses -14.690 -17.316 -17.028 -18.024 -19.233EBITDA 1.413 801 1.541 2.146 3.625
Depreciation,amortisationandimpairment (969,0) (1.414,0) (1.014,0) (1.117,0) (1.307,0) EBIT 444 -613 527 1.029 2.318
Taxasreported 40,0 112,0 (76,0) 175,0 (285,0) Taxbenefitsthroughfinancing (33,8) (52,8) (67,5) (51,3) (63,0) NOPAT 450 -554 384 1.153 1.970
Financecosts (220,0) (264,0) (301,0) (237,0) (294,0) Fincneincome 85,0 53,0 31,0 32,0 42,0 Netcurrencyretranslationcharges (8,0) 9,0 12,0 (27,0) (56,0) Lossesonderivativesnotqualifyingforhdgeaccounting (12,0) (12,0) 43,0 (49,0) (170,0) Netgainrelatedtoavailable-for-salefinancialassets (19,0) (1,0) 2,0 93,0 5,0 shareofprofitsininvestmentsaccountedforusingtheequitymethod 7,0 17,0 (8,0) 2,0 6,0 Lossonsaleofproperty,plantandequipmentandinvestments 81,0 7,0 (26,0) (11,0) (38,0) Netfinancingchargerelatingtopensions 184,0 (266,0) (53,0) (4,0) (12,0) Gainonbargainpurchase 0 73,0 0 0 0 Taxbenefitsthroughfinancing 33,8 52,8 67,5 51,3 63,0 NetFinancialResult 132 -331 -233 -150 -454
Netincomefromdiscontinuedoperations 0 (38,0) (4,0) 0 0 NetEarningsaftertax 582 -923 147 1.003 1.516
Minorityinterest (20,0) (20,0) (25,0) (21,0) (21,0) NetProfit 562 -943 122 982 1.495
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Page ½ XVIII
Appendix 12: IAG analytical balance sheet Source: Relevant annual reports, own depiction
Analytical Balance SheetBalance Sheet as of: 2011 2012 2013 2014 2015Currency in mEUROperationalAssetsCurrentassetsInventories 400,0 400,0 411,0 520,0 424,0 Tradereceivables 1.175,0 1.175,0 1.196,0 1.196,0 1.252,0 Othercurrentassets 445,0 445,0 631,0 1.235,0 602,0 Currenttaxreceivable 0 0 0 79,0 9,0 TotalCurrentAssets 2.020 2.020 2.238 3.030 2.287Non-CurrentassetsProperty,plantandequipment 9.584,0 9.584,0 10.228,0 13.672,0 11.784,0 Intangibleassets 1.724,0 1.724,0 2.196,0 3.246,0 2.438,0 Investmentsaccountedforusingtheequitymethod 165,0 165,0 25,0 41,0 27,0 Deferredtaxassets 497,0 497,0 501,0 723,0 769,0 Othernon-currentassets 71,0 71,0 197,0 365,0 188,0 TotalNon-CurrentAssets 12.041 12.041 13.147 18.047 15.206TotalOperatingAssets 14.061 14.061 15.385 21.077 17.493
OperationalLiabilitiesCurrentLiabilitiesTradeandotherpayables 5.377,0 5.377,0 6.793,0 3.803,0 3.281,0 Deferredrevenueonticketsales 0 0 0 4.374,0 3.933,0 Currenttaxpayable 157,0 157,0 11,0 124,0 57,0 Provisionsforliabilitiesandcharges 352,0 352,0 398,0 605,0 504,0 TotalCurrentLiabilities 5.886 5.886 7.202 8.906 7.775Non-CurrentLiabilitiesDeferredtaxliability 1.274,0 814,0 884,0 419,0 278,0 Provisionsforliabilitiesandcharges 1.244,0 1.244,0 1.796,0 2.049,0 1.967,0 Otherlong-termliabilities 384,0 384,0 225,0 223,0 226,0 TotalNon-CurrentLiabilities 2.902 2.442 2.905 2.691 2.471Totalnon-interestbearingdebt 8.788 8.328 10.107 11.597 10.246Investedcapital(netoperatingassets) 5.273 5.733 5.278 9.480 7.247
FinancialLiabilitiesTotalEquity 5.686 4.312 4.216 5.534 3.793CurrentandNon-CurrentfinancialliabilitiesInterest-bearinglong-termborrowings 4.304,0 4.304,0 4.535,0 7.498,0 5.904,0 Employeebenefitobligations 277,0 1.497,0 738,0 858,0 1.324,0 Derivativefinancialinstruments 55,0 55,0 66,0 282,0 359,0 Currentportionoflong-termborrowings 579,0 579,0 587,0 1.132,0 713,0 Derivativefinancialinstruments 64,0 64,0 528,0 1.328,0 1.313,0 Interest-bearingdebt 5.279 6.499 6.454 11.098 9.613
FinancialassetsAvailable-for-salefinancialassets 466,0 466,0 1.092,0 74,0 84,0 Employeebenefitassets 1.317,0 703,0 458,0 957,0 855,0 Derivativefinancialinstruments 37,0 37,0 35,0 62,0 80,0 Non-currentassetsheldforsale 18,0 18,0 12,0 5,0 18,0 Derivativefinancialinstruments 119,0 119,0 135,0 198,0 178,0 Othercurrentinterest-bearingdeposits 1.758,0 1.758,0 2.092,0 2.947,0 3.416,0 Cashandcashequivalents 1.977,0 1.977,0 1.541,0 2.909,0 1.528,0 Interest-bearingassets 5.692 5.078 5.365 7.152 6.159Net-interest-bearingdebt -413 1.421 1.089 3.946 3.454Investedcapital 5.273 5.733 5.305 9.480 7.247
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Page ½ XIX
Appendix 13: Delta analytical income statement Source: Relevant annual reports, own depiction
Analytical Income Statement
For the Fiscal Period Ending Dec-31-
2011 Dec-31-
2012 Dec-31-
2013 Dec-31-
2014 Dec-31-
2015 Currency EUR EUR EUR EUR EUR
Marginal tax rate 25% 25% 25% 25% 25%
TrafficRevenue 31.821,3 33.395,7 34.645,1 36.761,1 36.580,2
OtherRevenue 5.109,2 5.170,2 5.080,8 5.687,6 6.228,2
TotalRevenue 36.930 38.566 39.726 42.449 42.808
Salariesandrelatedcosts 7.250,4 7.641,7 8.119,1 8.539,8 9.229,7
Aircraftfuelandrelatedtaxes 10.233,0 10.674,8 9.882,8 12.271,2 6.882,3
Regionalcarriersexpense 5.752,8 5.938,9 5.962,1 5.507,8 4.460,3
Aircraftmaintenancematerialsandoutsiderepairs 1.856,3 2.056,1 1.947,7 1.922,5 1.943,5
Contractedservices 1.726,9 1.647,0 1.751,1 1.839,4 1.943,5
Passengercommissionsandothersellingexpenses 1.769,0 1.672,2 1.685,9 1.787,9 1.758,4
Landingfeesandotherrents 1.347,2 1.405,1 1.482,9 1.516,6 1.570,2
Profitsharing 277,6 391,2 532,2 1.141,1 1.567,0
Passengerservice 758,3 769,8 801,4 851,9 917,1
Aircraftrent 313,4 286,1 219,8 245,0 262,9
Restructuringandother 254,5 475,4 422,8 753,0 36,8
Other 1.712,2 1.674,3 1.598,6 1.889,9 2.101,3
TotalCostsofGoodsSold 33.252 34.632 34.406 38.266 32.673
0 0 0 0 0
GrossProfit 3.679 3.933 5.319 4.183 10.135
0 0 0 0 0
Resultfromequityinvestments 0 0 0 0 0
EBITDA 3.679 3.933 5.319 4.183 10.135
0 0 0 0 0
Depreciationandamortization 1.601,7 1.645,9 1.743,7 1.862,6 1.929,9
EBIT 2.077 2.287 3.576 2.320 8.205
0 0 0 0 0
Taxasreported 89,4 (16,8) 8.427,3 (434,4) (2.767,0)
Taxbenefitsthroughfinancing (236,9) (213,5) (224,0) (170,9) (126,5)
NOPAT 1.930 2.057 11.779 1.715 5.312
0 0 0 0 0
Interestexpense,net (947,6) (854,0) (896,0) (683,6) (505,9)
Amortizationofdebtdiscount,net (203,0) (203,0) 0 0 0
Lossonextinguishmentofdebt (71,5) (124,1) 0 0 0
Miscellaneous,net (46,3) (28,4) (22,1) (509,0) (172,5)
Taxbenefitsthroughfinancing 236,9 213,5 224,0 170,9 126,5
NetFinancialResult -1.031 -996 -694 -1.022 -552
0 0 0 0 0
Discontinuedoperations 0 0 0 0 0
NetEarningsaftertax 898 1.061 11.085 693 4.760
0 0 0 0 0
Minorityinterest 0 0 0 0 0
NetProfit 898 1.061 11.085 693 4.760
Appendix 14: Delta analytical balance sheet
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Page ½ XX
Source: Relevant annual reports, own depiction Analytical Balance Sheet
Balance Sheet as of: 2011 2012 2013 2014 2015 Currency in mEUR
OperationalAssets
Currentassets
Short-terminvestments 1.007,5 1.007,5 1.008,6 1.279,9 1.540,7
Accountsreceivable,netofanallowanceforuncollectible 1.643,8 1.780,5 1.692,2 2.415,8 2.124,4
Fuelinventory 176,7 651,0 742,5 561,6 398,6
Hedgemarginreceivable 0 0 0 972,8 125,2
Expendablepartsandsuppliesinventories,netofan 386,0 424,9 375,5 334,4 334,4
Deferredincometaxes,net 484,8 486,9 1.825,8 0 0
Prepaidexpensesandother 1.314,6 1.413,5 1.386,1 737,2 837,2
TotalCurrentAssets 5.013 5.764 7.031 6.302 5.361
Non-Currentassets
PropertyandEquipment,Net: 21.268,5 21.783,9 22.983,9 23.062,7 24.230,1
Goodwill 10.300,3 10.300,3 10.300,3 10.300,3 10.300,3
Identifiable intangibles, netof accumulatedamortization
of
4.996,6 4.920,9 4.898,8 4.841,0 5.112,3
Deferredincometaxes,net 0 0 5.250,1 7.987,7 5.212,2
Othernoncurrentassets 1.053,8 1.148,5 1.370,4 973,9 1.501,8
TotalNon-CurrentAssets 37.619 38.154 44.803 47.166 46.357
TotalOperatingAssets 42.633 43.918 51.834 53.467 51.717
OperationalLiabilities
CurrentLiabilities 0 0 0 0 0
Airtrafficliability 3.659,9 3.887,1 4.335,1 4.518,1 4.735,8
Accountspayable 1.682,7 2.411,5 2.418,9 2.757,6 2.884,8
Frequentflyerdeferredrevenue 1.944,6 1.899,4 1.957,2 1.661,7 1.719,5
Taxespayable 624,7 615,2 707,8 0 0
Fuelcardobligation 334,4 478,5 633,1 0 0
Otheraccruedliabilities 1.629,1 1.186,3 1.179,0 2.237,0 1.373,5
TotalCurrentLiabilities 9.875 10.478 11.231 11.174 10.714
Non-CurrentLiabilities 0 0 0 0 0
Frequentflyerdeferredrevenue 2.839,6 2.763,9 2.691,3 2.736,5 2.362,1
Deferredincometaxes,net 2.132,8 2.152,8 0 0 0
Othernoncurrentliabilities 1.492,4 1.734,3 1.799,5 2.238,0 1.988,8
TotalNon-CurrentLiabilities 6.465 6.651 4.491 4.975 4.351
Totalnon-interestbearingdebt 16.340 17.129 15.722 16.149 15.065
Investedcapital(netoperatingassets) 26.293 26.789 36.112 37.319 36.653
FinancialLiabilities
TotalEquity -1.468 -2.241 12.245 9.269 11.411
CurrentandNon-Currentfinancialliabilities 0 0 0 0 0
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Currentmaturitiesoflong-termdebtandcapitalleases 2.044,5 1.711,1 1.627,0 1.245,2 1.643,8
Accruedsalariesandrelatedbenefits 1.437,7 1.766,9 2.025,6 2.383,2 3.360,2
Hedgederivativesliability 0 0 0 2.915,3 2.714,4
Long-termdebtandcapitalleases 12.459,5 11.654,9 10.301,4 8.915,3 7.115,8
Pension,postretirementandrelatedbenefits 14.934,1 16.832,5 13.032,7 15.920,6 14.571,3
Interest-bearingdebt 30.876 31.965 26.987 31.380 29.406
Financialassets
Cashandcashequivalents 2.794,4 2.540,9 2.991,0 2.195,9 2.074,0
Restrictedcash,cashequivalentsandshort-term 320,8 394,4 128,3 0 0
Hedgederivativesasset 0 0 0 1.133,7 2.089,7
Interest-bearingassets 3.115 2.935 3.119 3.330 4.164
Net-interest-bearingdebt 27.761 29.030 23.867 28.050 25.242
Investedcapital 26.293 26.789 36.112 37.319 36.653
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Appendix 15: Air Berlin analytical income statement Source: Relevant annual reports, own depiction
Analytical Income StatementFor the Fiscal Period Ending
Dec-31-2011 Dec-31-2012 Dec-31-2013 Dec-31-2014 Dec-31-2015Currency in millions EUR EUR EUR EUR EURMarginal tax rate 25% 25% 25% 25% 25%Flightrevenue 4.006,7 3.815,5 3.808,2 3.709,4 Groundandotherservices 273,0 305,8 323,5 343,9 Duty-free/in-flightsales 32,0 25,5 28,4 28,4 Revenue 4.227,32 4.311,68 4.146,79 4.160,15 4.081,76
Gainondisposalfrequentflyerplan,net 184,4 0 0 0 Incomefromindemnitiesreceived 33,2 34,4 0 0 Gainondisposaloflong-termassets,net 33,1 11,3 0 30,1 Incomefromsubleases 2,8 4,0 0 0 Incomefrominsuranceclaims 1,6 0,9 2,9 2,0 Other 9,1 9,2 8,8 18,8 Otheroperatingincome 10,11 264,19 59,75 11,64 50,82
Expensesformaterialsandservices 3.304,5 3.288,8 3.174,5 3.124,4 3.064,3 Personnelexpenses 475,4 488,8 488,2 524,5 589,3 Otheroperatingexpenses 618,5 654,0 690,6 719,8 740,0 TotalCostsofGoodsSold 4.398,51 4.431,57 4.353,24 4.368,61 4.393,55
EBITDA -161,08 144,30 -146,69 -196,82 -260,97
Depreciation 85,94 74,15 85,19 96,95 45,98 EBIT -247,02 70,15 -231,88 -293,77 -306,95
Taxasreported (61,6) 10,0 (10,3) 2,2 (16,0) Taxbenefitsthroughfinancing (182,3) (190,4) (201,9) (238,9) (222,4) NOPAT -490,85 -110,23 -444,10 -530,49 -545,35
Interestexpensesoninterest-bearingliabilities (76,4) (86,9) (96,5) (86,5) Otherfinancialexpenses (0,9) (1,0) 3,2 3,5 Financialexpenses (82,7) (77,2) (87,9) (99,7) (89,9) Interestincomeonfixeddeposits 0,4 0,2 0,4 0,1 Interestincomeonloansandreceivables 0,2 0,0 0,1 0,0 OtherFinancialincome 0,5 6,9 3,7 0,9 Financialincome 1,1 7,1 4,2 1,0 Resultonforeignexchangeandderivatives,net (39,0) 2,6 6,8 9,9 (31,5) Taxbenefitsthroughfinancing 182,3 190,4 201,9 238,9 222,4 Netfinancingcosts 60,56 116,80 127,95 153,29 101,93
Shareofatequityinvestments,netoftax 0,10 0,25 0,64 0,53 -3,21 Resultfortheperiod -420,40 6,81 -315,51 -376,67 -446,64
Minorityinterst - - - 9,36 24,33 Netincome -420,40 6,81 -315,51 -386,03 -470,97
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Appendix 16: Air Berlin analytical balance sheet Source: Relevant annual reports, own depiction
Analytical Balance SheetBalance Sheet as of: 2011 2012 2013 2014 2015Currency in mEUROperationalAssetsCurrentassetsInventories 45.524,0 49.867,0 53.043,0 64.929,0 64.654,0 Tradeandotherreceivables 375.122,0 451.736,0 406.027,0 396.483,0 387.894,0 Deferredexpenses 42.598,0 46.571,0 46.620,0 47.936,0 50.856,0 TotalCurrentAssets 463.244 548.174 505.690 509.348 503.404Non-CurrentassetsIntangibleassets 396.008,0 421.044,0 415.893,0 408.798,0 405.031,0 Property,plantandequipment 818.915,0 597.890,0 497.846,0 302.176,0 182.956,0 Tradeandotherreceivables 79.188,0 79.770,0 115.301,0 85.303,0 56.273,0 Deferredtaxaseet 0 28.666,0 17.063,0 16.835,0 0 Deferredexpenses 53.112,0 47.597,0 55.744,0 49.117,0 52.768,0 TotalNon-CurrentAssets 1.347.223 1.174.967 1.101.847 862.229 697.028TotalOperatingAssets 1.810.467 1.723.141 1.607.537 1.371.577 1.200.432
OperationalLiabilitiesCurrentLiabilitiesTaxliabilites 2.726,0 4.514,0 3.716,0 3.266,0 2.507,0 Provisions 2.525,0 14.234,0 25.777,0 42.350,0 47.426,0 Tradeandotherpayables 423.421,0 426.778,0 440.967,0 446.290,0 511.344,0 Deferredincome 72.619,0 28.718,0 22.957,0 19.654,0 42.996,0 Advancedpaymentsreceived 335.259,0 365.625,0 428.928,0 396.432,0 373.913,0 TotalCurrentLiabilities 836.550 839.869 922.345 907.992 978.186Non-CurrentLiabilitiesProvisions 7.161,0 9.153,0 4.356,0 6.095,0 6.203,0 Tradeandotherpayabales 55.922,0 70.357,0 72.405,0 37.201,0 54.406,0 Deferredtaxliabilities 39.700,0 30.786,0 29.707,0 23.817,0 21.666,0 TotalNon-CurrentLiabilities 102.783 110.296 106.468 67.113 82.275Totalnon-interestbearingdebt 939.333 950.165 1.028.813 975.105 1.060.461Investedcapital(netoperatingassets) 871.134 772.976 578.724 396.472 139.971
FinancialLiabilitiesTotalEquity 105.181 130.175 -186.064 -415.388 -799.386CurrentandNon-CurrentfinancialliabilitiesInterest-bearingliabilitiesduetoaircraftfinancing 471.775,0 267.044,0 178.391,0 89.961,0 28.748,0 Interest-bearingliabilities 470.193,0 621.066,0 605.265,0 639.967,0 980.877,0 Negativemarketvalueofderivatives 11.021,0 531,0 577,0 93,0 0 Interest-bearingliabilitiesduetoaircraftfinancing 53.123,0 158.946,0 76.863,0 109.758,0 23.323,0 Interest-bearingliabilites 57.504,0 51.084,0 158.542,0 223.714,0 10.181,0 Negativemarketvalueofderivatives 17.521,0 38.601,0 23.098,0 240.548,0 114.217,0 Interest-bearingdebt 1.081.137 1.137.272 1.042.736 1.304.041 1.157.346
FinancialassetsPositivemarketvalueofderivatives 0 0 105,0 8,0 0 Netdefinedbenefitasset 2.206,0 4.015,0 3.455,0 709,0 176,0 Atequityinvestments 184,0 4.847,0 6.666,0 6.762,0 2.848,0 Positivemarketvalueofderivatives 73.187,0 12.467,0 14.350,0 82.467,0 26.311,0 Assetsheldforsale 0 145.206,0 30.309,0 142.806,0 23.419,0 Cashandcashequivalent 239.607,0 327.936,0 223.063,0 259.229,0 165.235,0 Interest-bearingassets 315.184 494.471 277.948 491.981 217.989Net-interest-bearingdebt 765.953 642.801 764.788 812.060 939.357Investedcapital 871.134 772.976 578.724 396.672 139.971
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Appendix 17: Ryanair analytical income statement Source: Relevant annual reports, own depiction
Analytical Income Statement
For the Fiscal Period Ending Dec-31-
2011 Dec-31-
2012 Dec-31-
2013 Dec-31-
2014 Dec-31-
2015 Currency EUR EUR EUR EUR EUR Marginal tax rate 25% 25% 25% 25% 25%
Scheduledrevenues 2.827,9 3.504,0 3.819,8 3.789,5 4.260,3
Ancillaryrevenues 801,6 886,2 1.064,2 1.247,2 1.393,7
TotalRevenue 3.630 4.390 4.884 5.037 5.654
Fuelcosts (1.227,0) (1.593,6) (1.885,6) (2.013,1) (1.992,1)
Airportandhandlingcharges (491,8) (554,0) (611,6) (617,2) (712,8)
Routecharges (410,6) (460,5) (486,6) (522,0) (547,4)
Staffcosts (376,1) (415,0) (435,6) (463,6) (502,9)
Marketing,distributionandother (154,6) (180,0) (197,9) (192,8) (233,9)
Maintenance,materialsandrepairs (93,9) (104,0) (120,7) (116,1) (134,9)
Aircraftrentals (97,2) (90,7) (98,2) (101,5) (109,4)
Icelandicvolcanicashrelatedcost (12,4) 0 0 0 0
TotalCostsofGoodsSold -2.864 -3.398 -3.836 -4.026 -4.233
EBITDA 766 992 1.048 1.010 1.421
Depreciation (277,7) (309,2) (329,6) (351,8) (377,7)
EBIT 488 683 718 659 1.043
Taxasreported (46,3) (72,6) (81,6) (68,6) (115,7)
Taxbenefitsthroughfinancing (16,7) (16,2) (18,0) (16,7) (14,1)
NOPAT 425 594 619 573 913
Financeexenses (93,9) (109,2) (99,3) (83,2) (74,2)
Financeincome 27,2 44,3 27,4 16,5 17,9
Foreignexchange(loss)/gain (0,6) 4,3 4,6 (0,5) (4,2)
Gainondisposalofproperty,plantandequipment 0 10,4 0 0 0
Taxonnetfinancialexpenses 16,7 16,2 18,0 16,7 14,1
NetFinancialResult -51 -34 -49 -51 -46
Discontinuedoperations 0 0 0 0 0
NetEarningsaftertax 375 560 569 523 867
Minorityinterest 0 0 0 0 0
NetProfit 375 560 569 523 867
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Appendix 18: Ryanair analytical balance sheet Source: Relevant annual reports, own depiction
Analytical Balance Sheet
Balance Sheet as of: 2011 2012 2013 2014 2015 Currency in mEUR
OperationalAssets
Currentassets
Invetories 2,7 2,8 2,7 2,5 2,1
Othershort-termfinancialassets 99,4 64,9 67,7 124,2 138,7
Currenttax 0,5 9,3 0 1,1 0,8
Tradeaccountsreceivables 50,6 51,5 56,1 58,1 60,1
TotalCurrentAssets 153 129 127 186 202
Non-Currentassets
Property,plantandequipment 4.933,7 4.925,2 4.906,3 5.060,3 5.471,1
Intangibleassets 46,8 46,8 46,8 46,8 46,8
TotalNon-CurrentAssets 4.981 4.972 4.953 5.107 5.518
TotalOperatingAssets 5.134 5.101 5.080 5.293 5.720
OperationalLiabilities
CurrentLiabilities
Tradepayables 150,8 181,2 138,3 150,0 196,5
Accruedexensesandotherliabilities 1.224,3 1.237,2 1.341,4 1.561,2 1.938,2
Currenttax 0 0 0,3 0 0
TotalCurrentLiabilities 1.375 1.418 1.480 1.711 2.135
Non-CurrentLiabilities
Provisions 89,6 103,2 135,9 133,9 180,8
Deferredtax 267,7 319,4 346,5 368,6 462,3
TotalNon-CurrentLiabilities 357 423 482 503 643
Totalnon-interestbearingdebt 1.732 1.841 1.962 2.214 2.778
Investedcapital(netoperatingassets) 3.401 3.260 3.117 3.079 2.942
FinancialLiabilities
TotalEquity 2.954 3.307 3.273 3.286 4.035
CurrentandNon-Currentfinancialliabilities
Currentmaturitisofdebt 336,7 368,4 399,9 467,9 399,6
Derivatievefinancialinstruments 125,4 28,2 31,8 95,4 811,7
Derivativefinancialinstruments 8,3 53,6 50,1 43,2 73,4
Othercreditors 126,6 146,3 127,8 90,4 55,8
Non-currentmaturitiesofdebt 3.312,7 3.256,8 3.098,4 2.615,7 4.032,0
Interest-bearingdebt 3.910 3.853 3.708 3.313 5.373
Financialassets
Availableforsalefinancialassets 114,0 149,7 221,2 260,3 371,0
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Page ½ XXVI
Derivativefinancialinstruments 23,9 3,3 5,1 0,4 554,5
Derivativefinancialinstruments 383,8 231,9 78,1 17,7 744,4
Restrictedcash 42,9 35,1 24,7 13,3 6,7
Financialassets 869,4 772,2 2.293,4 1.498,3 3.604,6
Cashandcashequivalents 2.028,3 2.708,3 1.240,9 1.730,1 1.184,6
Interest-bearingassets 3.462 3.901 3.863 3.520 6.466
Net-interest-bearingdebt 447 -47 -155 -208 -1.093
Investedcapital 3.401 3.260 3.117 3.078 2.942
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Appendix 19: Peer group total operating assets in €m (2011-2015) Source: Relevant annual reports, own depiction
Appendix 20: Trend analysis of Lufthansa's analytical income statements from 2011-2015 Source: Relevant annual reports, own depiction
0
20.000
40.000
60.000
2011 2012 2013 2014 2015
Peeraverage LHA KLM IAG Delta AirBelrin Ryanair
Analytical Income Statement 2011 2012 2013 2014 2015Currency EUR EUR EUR EUR EURMarginal tax rate 25% 25% 25% 25% 25%TrafficRevenue 100% 104% 103% 103% 106%OtherRevenue 100% 108% 110% 113% 136%Otheroperatingincome 100% 120% 88% 81% 122%TotalRevenue 100% 106% 103% 103% 112%
Fuel 100% 118% 112% 108% 92%Rawmaterials 100% 101% 104% 106% 126%Sellingandadminexpenses 100% 101% 99% 99% 110%Staffcosts 100% 101% 110% 110% 121%Otheroperatingexpenses 100% 92% 90% 96% 115%TotalCostsofGoodsSold 100% 103% 103% 103% 111%
GrossProfit 100% 139% 105% 96% 131%
Resultfromequityinvestments 100% 132% 176% 170% 170%EBITDA 100% 139% 107% 99% 132%
Depreciation 100% 107% 103% 89% 100%EBIT 100% 203% 115% 118% 199%
Operatingtaxes 100% 58% 139% 67% 194%NOPAT 100% 249% 109% 135% 216%
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Appendix 21: Common-size analysis of Lufthansa's analytical income statements from 2011-2015 Source: Relevant annual reports, own depiction
Analytical Income StatementFor the Fiscal Period Ending
Dec-31-2011 Dec-31-2012 Dec-31-2013 Dec-31-2014 Dec-31-2015 AverageCurrency EUR EUR EUR EUR EURMarginal tax rate 25% 25% 25% 25% 25%
TrafficRevenueOtherRevenueTotalRevenue 100,0% 100,0% 100,0% 100,0% 100,0% 100,0%
Fuel -21,8% -24,5% -23,5% -22,5% -18,0% -22,1%Rawmaterials -7,4% -7,2% -7,4% -7,5% -8,3% -7,6%Sellingandadminexpenses -28,5% -27,5% -26,9% -26,9% -28,0% -27,6%Staffcosts -23,2% -22,4% -24,5% -24,4% -25,2% -23,9%Otheroperatingincome 8,1% 9,2% 6,8% 6,3% 8,8% 7,9%Otheroperatingexpenses -18,4% -16,2% -15,8% -17,0% -19,0% -17,3%TotalCostsofGoodsSold -91,3% -88,5% -91,3% -92,0% -89,8% -90,6%
GrossProfit 8,7% 11,5% 8,7% 8,0% 10,2% 9,4%
Resultfromequityinvestments 0,2% 0,3% 0,4% 0,4% 0,4% 0,4%EBITDA 8,9% 11,8% 9,1% 8,4% 10,6% 9,8%
Depreciation -6,0% -6,1% -5,9% -5,1% -5,4% -5,7%EBIT 2,9% 5,7% 3,2% 3,3% 5,2% 4,1%
Taxasreported -0,5% -0,3% -0,7% -0,3% -0,9% -0,6%Tax shield -0,3% -0,3% -0,3% -0,2% -0,1% -0,2%NOPAT 2,1% 5,1% 2,2% 2,8% 4,1% 3,3%
interestincome 0,7% 0,6% 0,5% 0,5% 0,6% 0,6%interestexpenses -1,7% -1,8% -1,7% -1,4% -1,1% -1,5%Otherfinancialitems -0,4% -0,2% -0,3% -1,9% 1,6% -0,2%Taxshieldoninterest 0,3% 0,3% 0,3% 0,2% 0,1% 0,2%NetFinancialResult -1,1% -1,1% -1,1% -2,5% 1,2% -0,9%
Discontinuedoperations -1,0% 0,1% 0,0% 0,0% 0,0% -0,2%NetEarningsaftertax 0,0% 4,1% 1,1% 0,2% 5,4% 2,2%
Minorityinterest -0,1% 0,0% 0,0% -0,1% -0,1% -0,1%NetProfit 0,0% 4,1% 1,0% 0,2% 5,3% 2,1%
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Appendix 22: Lufthansa historic regional revenue, passenger, ASK, RASK and load factor developments Source: Lufthansa, 2016
Appendix 23: Peer Group Quick Ratios (2010-2015) Source: Own creation; all relevant annual reports
0,0
0,2
0,4
0,6
0,8
1,0
2011 2012 2013 2014 2015
Peeraverage LHA KLM IAG Delta AirBerlin Ryanair
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Appendix 24: Financial calculation including Net working capital Source: Own creation; all relevant annual reports
Lufthansa 2011 2012 2013 2014 2015 Average
Short-term
Currentratio 97% 100% 88% 75% 72% 0,86
Quickratio 50% 88% 76% 61% 60% 0,7
NWCTurnover 8,5 -502,3 -112,0 2728,3 88,3 442,2
Liquiditycycle 43 -1 -3 0 4 9
Long-term
Financialleverage 2,5 4,9 3,8 6,6 4,6 4,5
Interestcoverageratio 2,9 4,6 2,8 3,9 9,9 4,8
KLM 2011 2012 2013 2014 2015 Average
Short-term
Currentratio 0,7 0,8 0,7 0,6 0,6 0,7
Quickratio 0,6 0,6 0,6 0,5 0,5 0,6
NWCTurnover 3,1 3,8 5,6 7,2 9,3 5,8
Liquiditycycle 118 95 65 51 39 74
Long-term
Financialleverage 3,5 4,5 10,1 -36,6 84,5 13,2
Interestcoverageratio 3,3 2,8 3,7 6,7 8,9 5,1
IAG 2011 2012 2013 2014 2015 Average
Short-term
Currentratio 0,9 0,9 0,7 0,8 0,8 0,8
Quickratio 0,8 0,8 0,6 0,6 0,6 0,7
NWCTurnover -4,2 -4,7 -3,7 -3,4 -4,2 -4,0
Liquiditycycle -88 -78 -98 -106 -88 -91
Long-term
Financialleverage 3,8 5,4 5,9 6,1 7,9 5,8
Interestcoverageratio 10,5 3,8 5,7 10,5 14,4 9,0
Delta 2011 2012 2013 2014 2015 Average
Short-term
Currentratio 0,6 0,6 0,7 0,5 0,5 0,6
Quickratio 0,4 0,3 0,3 0,3 0,2 0,3
NWCTurnover -7,6 -8,2 -9,5 -8,7 -8,0 -8,4
Liquiditycycle -48 -45 -39 -42 -46 -44
Long-term
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Page ½ XXXI
Financialleverage -32,2 -21,9 3,5 5,1 3,9 -8,3
Interestcoverageratio 3,9 4,6 5,9 6,1 20,0 8,1
Air Berlin 2011 2012 2013 2014 2015 Average
Short-term
Currentratio 0,8 0,9 0,7 0,7 0,6 0,7
Quickratio 0,6 0,7 0,5 0,4 0,5 0,6
NWCTurnover -11,3 -14,8 -10,0 -10,4 -8,6 -11,0
Liquiditycycle -32 -25 -37 -35 -42 -34
Long-term
Financialleverage 19,2 16,0 -11,1 -3,1 -2,0 3,8
Interestcoverageratio 0,0 0,0 0,0 0,0 0,0 0,0
Ryanair 2011 2012 2013 2014 2015 Average
Short-term
Currentratio 1,9 2,1 2,0 1,5 1,7 1,8
Quickratio 1,2 1,5 0,7 0,8 0,4 0,9
NWCTurnover -3,0 -3,4 -3,6 -3,3 -2,9 -3,2
Liquiditycycle -123 -107 -101 -111 -125 -113
Long-term
Financialleverage 1,9 1,7 1,7 1,7 2,0 1,8
Interestcoverageratio 11,5 15,3 14,6 15,1 25,2 16,3
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Appendix 25: Analyst forecasts and weighted average of regional ASK growth Source: World bank, 2016; Boin, 2016; Marketline, 2016; FAA, 2016; Own depiction
World bank GDP development 2016 2017 2018 2019 2020long termEurope 1,6% 1,5% 1,4% 1,5% 1,3% 1,2%NorthAmerica* 1,6% 2,2% 2,1% 1,9% 1,7% 1,6%SouthAmerica -1,4% 1,2% 2,3% 2,6% 2,2% 1,9%Asia/Pacific 6,3% 6,2% 6,1% 6,1% 5,5% 5,0%MiddleEast 2,7% 3,1% 3,3% 3,4% 3,4% 3,4%Africa 1,5% 2,9% 3,6% 3,7% 3,7% 3,7%Totalavergae 2,1% 2,9% 3,1% 3,2% 0,18 0,17
* As of 2017, the U.S. forecasts do not Source: World Bank (2016)Boing Market Outlook 2016E 2017E 2018E 2019E 2020E long termEurope 3,8% 2,6%NorthAmerica* 3,8% 2,6%SouthAmerica 2,2% 4,8%Asia/Pacific 8,2% 7,6%MiddleEast 13,9% 10,1%Africa 6,2% 4,7%Totalavergae 6,4% 5,4%
Source: Boing, Market Outlook fact sheet, 2016MarketLine 2016E 2017E 2018E 2019E 2020E long termEurope 2,8% 4,1% 4,6% 3,4% 2,5% 1,8%NorthAmerica* 2,3% 3,1% 3,1% 3,1% 3,1% 1,9%SouthAmerica 0,7% 4,2% 5,8% 7,0% 7,2% 4,1%Asia/Pacific 7,2% 7,6% 8,0% 8,2% 8,4% 7,0%MiddleEast/Africa 7,4% 8,5% 9,3% 9,8% 10,4% 8,3%Totalavergae 4,1% 5,5% 6,2% 6,3% 6,3% 4,6%
Source: MarketLine (2016)FAA 2016E 2017E 2018E 2019E 2020E long termPessimistiv 2,50% 0,75% 1,50% 1,75% 2,50% 2,25%Baseline 2,50% 2,65% 2,80% 2,60% 2,50% 2,45%Optimistic 2,50% 3,60% 4,00% 2,90% 2,50% 2,55%Source: FAA (2016)weighted average base 2016 2017 2018 2019 2020 2021 /long termEurope 2,7% 2,7% 3,0% 2,5% 1,9% 1,5%America 1,5% 3,0% 3,3% 3,7% 5,2% 3,0%Asia/Pacific 7,2% 7,1% 7,0% 7,2% 6,9% 6,0%MiddleEast/Africa 6,7% 6,2% 4,0% 6,2% 9,4% 7,7%
Totalavergae 4,5% 4,8% 4,3% 4,9% 5,9% 4,5%
ASK
fore
cast
sSu
mm
ary
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Page ½ XXXIII
Appendix 26: ASK growth forecasts and resulting actual ASK estimates for the base, best and worst case scenarios Source: Own creation
own estimateHistoricaverages
ASKs 2016 2017 2018 2019 2020 2021Europe 92.851 95.555 98.476 100.253 101.845 103.309 America 95.740 97.962 100.290 102.718 105.688 106.900 AsiaPacific 65.973 68.264 70.183 72.842 75.523 77.300 MiddleEast/afirca 23.885 24.068 24.329 24.758 25.202 25.755 Total 278.448 285.849 293.278 300.570 308.258 313.264
Regional ASK growth in % 2016 2017 2018 2019 2020 2021Europe 0,4% 1,0% 2,9% 3,1% 1,8% 1,6% 1,4%America 4,0% 1,9% 2,3% 2,4% 2,4% 2,9% 1,1%Asia/Pacific 1,6% 2,9% 3,5% 2,8% 3,8% 3,7% 2,4%MiddleEast/Africa -3,5% -0,1% 0,8% 1,1% 1,8% 1,8% 2,2%Totalavergae 0,6% 1,5% 2,8% 2,8% 2,4% 2,5% 1,6%
Forecastvaluedrivers
Base Case
own estimateHistoricaverages
ASKs 2016 2017 2018 2019 2020 2021Europe 93.678 96.984 100.337 102.248 103.872 105.400 America 96.961 100.392 104.183 107.851 112.048 115.611 AsiaPacific 66.550 69.285 72.203 75.010 77.771 80.405 MiddleEast/afirca 24.364 24.871 25.240 25.710 26.428 27.017 Total 281.553 291.532 301.963 310.819 320.119 328.432
Regional ASK growth in % 2016 2017 2018 2019 2020 2021Europe 0,4% 1,9% 3,5% 3,5% 1,9% 1,6% 1,5%America 4,0% 3,2% 3,5% 3,8% 3,5% 3,9% 3,2%Asia/Pacific 1,6% 3,8% 4,1% 4,2% 3,9% 3,7% 3,4%MiddleEast/Africa -3,5% 1,9% 2,1% 1,5% 1,9% 2,8% 2,2%Totalavergae 0,6% 2,2% 3,7% 3,7% 2,9% 2,9% 2,5%
Best Case
Forecastvaluedrivers
own estimateHistoricaverages
ASKs 2016 2017 2018 2019 2020 2021Europe 93.034 95.155 97.652 99.136 100.381 101.757 America 96.022 98.507 100.814 102.970 106.634 107.785 AsiaPacific 65.331 67.395 69.336 71.766 73.450 75.130 MiddleEast/afirca 23.646 23.914 24.069 24.425 24.945 25.426 Total 278.034 284.971 291.871 298.297 305.410 310.097
Regional ASK growth in % 2016 2017 2018 2019 2020 2021Europe 0,4% 1,2% 2,3% 2,6% 1,5% 1,3% 1,4%America 4,0% 2,2% 2,6% 2,3% 2,1% 3,6% 1,1%Asia/Pacific 1,6% 1,9% 3,2% 2,9% 3,5% 2,3% 2,3%MiddleEast/Africa -3,5% -1,1% 1,1% 0,6% 1,5% 2,1% 1,9%Totalavergae 0,6% 1,1% 2,6% 2,6% 2,1% 2,3% 1,5%
Worst Case
Forecastvaluedrivers
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Page ½ XXXIV
Appendix 27: Load factor growth forecasts for the base, best and worst case scenarios Source: Own creation
own estimateHistoricaverages
Passenger Load factor** 2016 2017 2018 2019 2020 2021Europe 76,1% 74,6% 74,8% 74,8% 75,6% 75,6%America 83,8% 83,4% 83,5% 83,5% 83,6% 83,6%Asia/Pacific 82,6% 82,8% 82,9% 82,9% 83,1% 83,1%MiddleEast/Africa 75,3% 75,6% 76,3% 76,3% 76,5% 76,6%Totalavergae 79,5% 79,1% 79,4% 79,4% 79,7% 79,7%
Regional Load factor growth 2016 2017 2018 2019 2020 2021Europe 1,2% -0,5% -2,0% 0,3% 0,04% 1,0% 0,02%America 0,1% -0,1% -0,5% 0,1% 0,1% 0,1% 0,0%Asia/Pacific 0,4% 0,0% 0,2% 0,2% 0,0% 0,2% 0,02%MiddleEast/Africa 0,8% -1,0% 0,3% 1,0% 0,03% 0,2% 0,2%Totalavergae 0,6% -0,4% -0,5% 0,4% 0,0% 0,4% 0,1%
Forecastvaluedrivers
Base Case
own estimateHistoricaverages
Passenger Load factor** 2016 2017 2018 2019 2020 2021Europe 76,5% 75,7% 76,2% 76,4% 77,2% 77,3%America 83,8% 83,4% 83,5% 83,5% 83,6% 83,7%Asia/Pacific 82,6% 82,8% 82,9% 83,2% 83,4% 83,4%MiddleEast/Africa 75,3% 75,6% 76,3% 76,5% 76,6% 76,8%Totalavergae 79,6% 79,4% 79,7% 79,9% 80,2% 80,3%
Regional Load factor growth 2016 2017 2018 2019 2020 2021Europe 1,2% 0,0% -1,0% 0,6% 0,3% 1,0% 0,1%America 0,1% -0,1% -0,5% 0,1% 0,1% 0,1% 0,1%Asia/Pacific 0,4% 0,0% 0,2% 0,2% 0,3% 0,2% 0,1%MiddleEast/Africa 0,8% -1,0% 0,3% 1,0% 0,2% 0,2% 0,2%Totalavergae 0,6% -0,3% -0,3% 0,5% 0,2% 0,4% 0,1%
Best Case
Forecastvaluedrivers
own estimateHistoricaverages
Passenger Load factor** 2016 2017 2018 2019 2020 2021Europe 76,1% 74,6% 74,7% 74,7% 75,1% 75,2%America 83,8% 83,4% 83,5% 83,5% 83,6% 83,6%Asia/Pacific 82,6% 82,8% 82,9% 82,9% 83,1% 83,1%MiddleEast/Africa 75,3% 75,6% 76,3% 76,3% 76,5% 76,6%Totalavergae 79,5% 79,1% 79,4% 79,4% 79,6% 79,6%
Regional Load factor growth 2016 2017 2018 2019 2020 2021Europe 1,2% -0,5% -2,0% 0,1% 0,0% 0,6% 0,0%America 0,1% -0,1% -0,5% 0,1% 0,1% 0,1% 0,0%Asia/Pacific 0,4% 0,0% 0,2% 0,2% 0,0% 0,2% 0,0%MiddleEast/Africa 0,8% -1,0% 0,3% 1,0% 0,0% 0,2% 0,1%Totalavergae 0,6% -0,4% -0,5% 0,4% 0,0% 0,3% 0,0%
Worst Case
Forecastvaluedrivers
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Page ½ XXXV
Appendix 28: Unit yield growth forecasts and resulting actual unit yield estimates for the base, best and worst case scenarios Source: Own creation
own estimateHistoricaverages
Pricing in € 2016 2017 2018 2019 2020 2021Europe 0,14 0,15 0,15 0,15 0,15 0,15Amercia 0,08 0,09 0,09 0,09 0,09 0,09AsiaPacific 0,07 0,07 0,07 0,08 0,08 0,08MiddleEast/Africa 0,09 0,09 0,09 0,09 0,09 0,09Totalaverage 0,096 0,099 0,100 0,102 0,103 0,104
Growth in Pricing in % 2016 2017 2018 2019 2020 2021Europe -0,5% -2,00% 3,0% 1,0% 0,5% 1,4% 0,2%Amercia 2,8% -2,70% 3,0% 3,0% 2,1% 1,9% 0,2%AsiaPacific -2,6% -5,0% 2,5% 2,0% 2,5% 1,0% 0,9%MiddleEast/Africa -1,0% -3,3% 2,5% 1,7% 1,6% 1,0% 1,3%Totalaverage -0,3% -3,3% 2,8% 1,9% 1,7% 1,3% 0,7%
Forecastvaluedrivers
Base Case
own estimateHistoricaverages
Pricing in € 2016 2017 2018 2019 2020 2021Europe 0,142 0,146 0,147 0,15 0,15 0,15Amercia 0,08 0,09 0,09 0,09 0,09 0,09AsiaPacific 0,07 0,07 0,07 0,08 0,08 0,08MiddleEast/Africa 0,09 0,09 0,09 0,09 0,09 0,09Totalaverage 0,096 0,098 0,100 0,101 0,102 0,102
Growth in Pricing in % 2016 2017 2018 2019 2020 2021Europe -0,5% -2,00% 2,70% 0,70% 0,20% 1,10% -0,10%Amercia 2,8% -3,00% 2,70% 2,70% 1,80% 1,60% -0,10%AsiaPacific -2,6% -5,30% 2,20% 1,70% 2,20% 0,70% 0,64%MiddleEast/Africa -1,0% -3,60% 2,20% 1,40% 1,30% 0,70% 1,00%Totalaverage -0,3% -3,5% 2,5% 1,6% 1,4% 1,0% 0,4%
Best Case
Forecastvaluedrivers
own estimateHistoricaverages
Pricing in € 2016 2017 2018 2019 2020 2021Europe 0,142 0,15 0,15 0,15 0,15 0,15Amercia 0,08 0,09 0,09 0,09 0,09 0,09AsiaPacific 0,07 0,07 0,07 0,08 0,08 0,08MiddleEast/Africa 0,09 0,09 0,09 0,09 0,09 0,09Totalaverage 0,096 0,099 0,100 0,102 0,103 0,104
Growth in Pricing in % 2016 2017 2018 2019 2020 2021Europe -0,5% -2,0% 3,0% 1,0% 0,5% 1,4% 0,2%Amercia 2,8% -2,7% 3,0% 3,0% 2,1% 1,9% 0,2%AsiaPacific -2,6% -5,0% 2,5% 2,0% 2,5% 1,0% 0,9%MiddleEast/Africa -1,0% -3,3% 2,5% 1,7% 1,6% 1,0% 1,3%Totalaverage -0,3% -3,3% 2,8% 1,9% 1,7% 1,3% 0,7%
Worst Case
Forecastvaluedrivers
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Page ½ XXXVI
Appendix 29: Base case estimates of essential growth rates Source: Own creation
Appendix 30: Best case estimates of essential growth rates Source: Own creation
Appendix 31: Worst case estimates of essential growth rates Source: Own creation
Essential growth rates 2011 2012 2013 2014 2015
Revenue 5,52% 1,33% -0,83% 4,85% 2,72%Fuel 17,78% -4,52% -4,35% -14,32% -1,35%Staff 0,94% 9,03% -0,20% 10,09% 3,26%
Growthparameters
historicAverage11-15
Essential growth rates E2016 E2017 E2018 E2019 E2020 E2021
Revenue -1,71% 4,58% 4,81% 3,84% 4,41% 2,01%Fuel -10,00% 18,00% 5,23% 4,00% 4,42% 2,56%Staff -1,00% 2,00% 2,00% 2,00% 2,00% 2,01%
Growthparameters
Forecastvaluedrivers
Essential growth rates E2016 E2017 E2018 E2019 E2020 E2021
Revenue -0,59% 5,62% 5,56% 4,13% 4,49% 2,63%Fuel -10,00% 17,60% 5,57% 4,33% 5,97% 2,63%Staff -2,00% 2,00% 3,50% 4,16% 4,50% 2,63%
Forecastvaluedrivers
Growthparameters
Essential growth rates E2016 E2017 E2018 E2019 E2020 E2021
Revenue -1,77% 4,34% 4,52% 3,56% 4,08% 1,91%Fuel -10,00% 18,00% 4,52% 3,58% 4,09% 1,91%Staff 0,00% 2,00% 2,00% 2,00% 2,00% 1,91%
Forecastvaluedrivers
Growthparameters
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Page ½ XXXVII
Appendix 32: Lufthansa capital structure development (2011-2015) Source: Relevant annual reports, own depiction
Appendix 33: Lufthansa Beta calculation Source: Relevant annual reports, own depiction; Damodaran (1999)
Covariance with market
CoVarLufthansa 0,002
MarketVariance(DAX) 0,003
Beta 0,844
Regression output Lufthansa - DAX Coefficients P-value
Intercept -0,005 0,607
XVariable1 0,844 0,000
Beta adjustments Lufthansa KLM IAG Delta
Retrievedbeta(Reuters) 0,910 0,940 1,170 0,860
Ownregresssion 0,844 / / /
Averagebetas 0,877 0,940 1,170 0,860
Debt 13.983€ 4.003€ 3.454€ 24.001€
Equity 6.768€ 2.226€ 16.472€ 39.480€
D/Eratio 2,07 1,80 0,21 0,61
Unleveredbetas 0,286 0,336 0,967 0,535
Averageassetbeta 0,531
Re-leveraging Lufthansa
D/Eratio 2,07
AverageAssetBeta 0,53
ReleveredBeta 1,6281
70%62% 58%
69% 67,39%
30%38% 42%
31% 32,61%
0%
20%
40%
60%
80%
2011 2012 2013 2014 2015
D/EV E/EV
_____________________________________________________________________________
Page ½ XXXVIII
Smoothing factor Lufthansa
Bloombergformula 0,66*relevered+0,33*1
LufthansafinalBeta 1,4188
Appendix 34: Lufthansa risk free rate calculation Source: investing , 2016, own depiction
Risk-free rate (rf) Lufthansa
Indicatorofrate 30-YGermanGovernmentBondon30.12.2016
Moodysrating AAA
Riskfreerate 0,953%
Source: https://www.investing.com/rates-bonds/germany-30-year-bond-yield-historical-
data
Appendix 35: Lufthansa cost of debt calculation Source: stated beneath
Cost of Debt - Lutfhansa Moody SP
RatingsforLHA Ba1 BBB-
Respectivespread 2,50% 2,05%
AverageSpread 2,275%
Source:http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/ratings.htm
Comments:thereisnospreadforBBBratings,hencethemeanbetweenBBBandBB+isused
_____________________________________________________________________________
Page ½ XXXIX
Appendix 36: Lufthansa corporate tax Source: Lufthansa, 2016
Corporate tax rate in Germany according to LHA
taxrate 25,00%
Source:LHAannualreport2011-2015
Appendix 37: Market risk premium - MRP Source: Relevant annual reports, own depiction; Damodaran (1999)
Market risk premium Germany
Fernandezimpliedriskpreimum 5,30%
Damodaranimpliedriskpremium 5,69%
AverageMRP 5,495%
Appendix 38: Lufthansa total cost of equity calculation Source: own depicition
Cost of Equity Lufthansa
Beta 1,419
Risk-freerate 0,95%
EMRP 5,50%
countryriskpremium 2,29%
CostofEquity 11,043%
Appendix 39: Lufthansa WACC calculation Source: own depiction
WACC-calculations Lufthansa
Costofdebt 3,23%
Costofequity 11,04%
Debtratio 50,00%
Equityratio 50,00%
Taxrate 25,00%
WACC 6,732%
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Page ½ XL
Appendix 40: Forecasted elements of the analytical income statement Source: own depiction
Averag
eFo
reca
stin
g e
lem
ents
E20
16
E20
17
E20
18
E20
19
E20
20
E20
21
Fina
ncialvalue
driv
ers
Grow
thdriv
ers
Revenu
egrow
th2,72%
-1,71%
4,58%
4,81%
3,87%
4,42%
2,01%
Passen
gerR
even
ue/Totalre
venu
e71,36%
71,36%
71,36%
71,36%
71,36%
71,36%
71,36%
Specialcostg
rothra
tes
Fuelco
stgrowth
-1,35%
-10,00
%17,50%
5,23%
4,00%
4,42%
2,56%
Staffcostsgrowth
4,97%
-1,00%
2,00%
2,00%
2,00%
2,00%
2,01%
Specialcoste
lemen
tsFuelco
sts
6.652
5.206
6.117
6.436
6.694
6.990
7.169
Staffcosts
7.236
7.994
8.154
8.317
8.484
8.653
8.827
Co
stdriv
ers(margins)
Fuel/Totalre
venu
e22,08%
16,72%
18,78%
18,86%
18,88%
18,88%
18,99%
Rawm
aterials/To
talreven
ue7,55%
7,55%
7,55%
7,55%
7,55%
7,55%
7,55%
Sellingand
Adm
inco
sts/To
talreven
ue27,56%
27,56%
27,56%
27,56%
27,56%
27,56%
27,56%
Staffcost/To
talreven
ue23,94%
25,67%
25,04%
24,37%
23,93%
23,38%
23,38%
Othe
rope
ratin
gincome/To
talreven
ue7,85%
7,85%
7,85%
7,85%
7,85%
7,85%
7,85%
Othe
rope
ratin
gexpe
nses/Totalre
venu
e17,29%
17,29%
17,29%
17,29%
17,29%
17,29%
17,29%
Forecastvaluedriv
ers
_____________________________________________________________________________
Page ½ XLI
Appendix 41: Forecasted elements of the analytical balance sheet Source: own depitction
Averag
eFo
reca
stin
g e
lem
ents
E20
16
E20
17
E20
18
E20
19
E20
20
E20
21
Investmen
tdriv
ers
Aircrafts
/reven
ue42,30%
49,00%
50,60%
48,00%
47,00%
47,00%
47,00%
Repaira
blesparepartsforaircraft/aircraft
8,02%
8,02%
8,02%
8,02%
8,02%
8,02%
8,02%
Intangibleassets/revenu
e5,27%
5,27%
5,27%
5,27%
5,27%
5,27%
5,27%
PPE/revenu
e6,99%
6,99%
6,99%
6,99%
6,99%
6,99%
6,99%
Othe
rnon
-currentassets
4,34%
4,34%
4,34%
4,34%
4,34%
4,34%
4,34%
Non-curren
tassets/revenu
e62,31%
16,60%
16,60%
16,60%
16,60%
16,60%
16,60%
NWCdecompo
sedinto:
Inventories/revenu
e2,41%
2,41%
2,41%
2,41%
2,41%
2,41%
2,41%
tradereceivables/revenu
e12,33%
12,33%
12,33%
12,33%
12,33%
12,33%
12,33%
Othe
rcurrentassets/revenu
e0,80%
0,76%
0,76%
0,76%
0,76%
0,76%
0,76%
Curren
tadvancedpaym
ents/reven
ue3,10%
2,86%
2,86%
2,86%
2,86%
2,86%
2,86%
Non-curren
tadvancedpaym
ents/reven
ue3,92%
3,92%
3,92%
3,92%
3,92%
3,92%
3,92%
Liabilitiesfromunu
sedflightd
ocum
ents/reven
ue8,84%
8,84%
8,84%
8,84%
8,84%
8,84%
8,84%
Othe
rcurrentliabilitie
s/revenu
e3,56%
3,56%
3,56%
3,56%
3,56%
3,56%
3,56%
Othe
rnon
-currentliabilitie
s/revenu
e6,61%
6,61%
6,61%
6,61%
6,61%
6,61%
2,37%
Forecastvaluedriv
ers
_____________________________________________________________________________
Page ½ XLII
Appendix 42: Lufthansa's forecasted analytical income statement base case Source: own depiction
Analytical Income Statement 2011 2012 2013 2014 2015 E2016 E2017 E2018 E2019 E2020 E2021
TrafficRevenue 23.779 24.793 24.565 24.388 25.322 - - - - - -OtherRevenue 4.955 5.342 5.463 5.623 6.734 - - - - - -Netrevenue 28.734 30.135 30.028 30.011 32.056 31.509 32.954 34.541 35.876 37.461 38.214
Fuel -6.276 -7.392 -7.058 -6.751 -5.784 -5.206 -6.117 -6.436 -6.694 -6.990 -7.169Rawmaterials -2.127 -2.157 -2.212 -2.252 -2.670 -2.380 -2.489 -2.608 -2.709 -2.829 -2.886Sellingandadminexpenses -8.189 -8.284 -8.082 -8.068 -8.983 -8.685 -9.083 -9.520 -9.888 -10.325 -10.533Staffcosts -6.678 -6.741 -7.350 -7.335 -8.075 -7.994 -8.154 -8.317 -8.484 -8.653 -8.827Otheroperatingincome 2.324 2.785 2.042 1.890 2.832 2.474 2.588 2.712 2.817 2.942 3.001Otheroperatingexpenses -5.293 -4.885 -4.753 -5.088 -6.106 -5.449 -5.699 -5.973 -6.204 -6.478 -6.608TotalCostsofGoodsSold -26.239 -26.674 -27.413 -27.604 -28.786 -27.238 -28.953 -30.143 -31.162 -32.333 -33.022
GrossProfit 2.495 3.461 2.615 2.407 3.270 4.271 4.001 4.398 4.715 5.128 5.192
Resultfromequityinvestments 71 94 125 121 121 111 116 121 126 132 134EBITDA 2.566 3.555 2.740 2.528 3.391 4.160 3.885 4.276 4.589 4.996 5.058
Depreciation -1.722 -1.839 -1.766 -1.528 -1.715 -1.989 -2.132 -2.146 -2.194 -2.291 -2.337EBIT 844 1.716 974 1.000 1.676 2.171 1.753 2.130 2.395 2.705 2.721
Taxasreported -157 -91 -219 -105 -304 -543 -438 -533 -599 -676 -680Taxshield -100 -105 -107 -205 88 -160 -171 -172 -176 -184 -188NOPAT 588 1.520 648 690 1.460 1.469 1.144 1.425 1.620 1.845 1.853
interestincome 190 168 162 159 186 - - - - - -interestexpenses -478 -540 -508 -415 -356 - - - - - -Otherfinancialitems -110 -48 -83 -564 520 -638 -683 -689 -705 -736 -751NetFinancialResult -398 -420 -429 -820 350 -638 -683 -689 -705 -736 -751Taxshieldoninterest -100 -105 -107 -205 88 -160 -171 -172 -176 -184 -188NetFinancialResultaftertax -498 -525 -536 -1.025 438 -798 -854 -862 -881 -920 -939Discontinuedoperations -285 36 0 0 0 0 0 0 0 0 0NetEarningsaftertax -195 1.031 112 -335 1.897 671 290 564 738 925 914
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Page ½ XLIII
Appendix 43: Lufthansa's forecasted analytical balance sheet base case Source: own depiction
Analytical Balance sheet 2011 2012 2013 2014 2015 2016e 2017e 2018e 2019e 2020e 2021eOperationalBalancesheetside -1,71% 4,58% 4,81% 3,84% 4,41% 2,01%
Non-currentassetsIntangibleassetswithanindefiniteusefullife&otherintangables1.575 1.568 1.569 1.587 1.657 1.662 1.738 1.821 1.892 1.975 2.015
Aircraft,reserveengines,repairablespareparts&PPE14.550 14.818 15.371 16.764 18.152 20.168 21.620 21.763 22.246 23.228 23.695
Investmentsaccountedforusingtheequitymethod&Deferredcharges418 425 474 456 532 - - - - - -
Deferredtaxassets 33 755 622 1.489 1.200 - - - - - -
Effectiveincometaxreceivables 60 52 39 31 19 - - - - - -
Othernon-currentassets - - - - - 1.367 1430 1499 1557 1625 1.658
Totalnon-currentassets 16.636 17.618 18.075 20.327 21.560 23.197 24.788 25.083 25.694 26.829 27.368Non-currentprovisionsandliabilitiesOtherprovisions 578 582 581 601 526 - - - - - -
Deferredtaxliabilities 364 94 146 239 346 - - - - - -
Advancepaymentsreceived,deferredincomeandothernon-financialliabilities1.156 1.163 1.187 1.179 1.223 - - - - - -
Non-currentliabilities - - - - - 2.082 2.178 2.283 2.371 2.475 2.525
Totalnon-currentliabilities 2.098 1.839 1.914 2.019 2.095 2.082 2.178 2.283 2.371 2.475 2.525TotalFixedAssets 14.538 15.779 16.161 18.308 19.465 21.115 22.610 22.800 23.323 24.353 24.843CurrentassetsInventories 887 639 641 700 761 759 794 832 865 903 921
Tradereceivablesandotherreceivables 3.111 3.595 3.577 3.995 4.389 3.887 4.065 4.260 4.425 4.621 4.714
Deferredchargesandprepaidexpenses 2.838 151 146 147 158 239 250 263 273 285 290
Effectiveincometaxreceivables 727 101 72 122 85 - - - - - -
Totalcurrentassets 7.563 4.486 4.436 4.964 5.393 4.885 5.109 5.355 5.562 5.808 5.925CurrentprovisionsandliabilitiesOtherprovisions&incometaxobligtions 818 894 861 953 1.075 - - - - - -
Effectiveincometaxobligations 71 107 247 228 136 - - - - - -
Advancedpaymentsreceived,deferredincomeandothernon-financialliabilities939 933 961 924 918 902 944 989 1.027 1.073 1.094
Liabilitiesfromunusedflightdocuments 2.359 2.612 2.635 2.848 2.901 2.785 2.913 3.053 3.171 3.311 3.378
provisionsandallincometaxobligations - - - - - 1.123 1.174 1.231 1.279 1.335 1.362
Totalcurrentliabilities 4.187 4.546 4.704 4.953 5.030 4.810 5.031 5.273 5.477 5.719 5.834TotalWorkingCapital 3.376 -60 -268 11 363 74 79 82 85 89 91InvestedCapital 17.914 15.719 15.893 18.319 19.828 21.189 22.688 22.883 23.409 24.443 24.934
FinancialBalancesheetsideEquity 8.044 4.839 6.108 4.031 5.845Non-currentprovisionsandliabilitiesPensionprovisions 2.165 5.844 4.718 7.231 6.626
Financialliabilities 6.424 6.910 6.337 5.958 6.370
Totalnon-currentinterest-bearingprovisionsandliabilities8.589 12.754 11.055 13.189 12.996Non-currentassetsOtherinvestments 1.519 1.025 1.386 1.930 1.900
Financialassets
Totalnon-currentinterest-bearingassets 1.519 1.025 1.386 1.930 1.900Netnon-currentinterest-bearingprovisionsandliabilities7.070 11.729 9.669 11.259 11.096CurrentprovisionsandliabilitiesFinancialliabilities 5.071 4.429 4.694 4.797 4.968
Liabilitiesinconjunctionwithassetsheldforsale 92 152 609 1.485 1.528
Totalcurrentinterest-bearingprovisionsandliabilities5.163 4.581 5.303 6.282 6.496CurrentassetsFinancialassets 620 3.530 3.146 1.785 1.994
Cashandcashequivalents 1.127 1.436 1.550 953 1.099
Loansreceivable 616 464 491 515 516
Totalcurrentinterest-bearingassets 2.363 5.430 5.187 3.253 3.609Netcurrentinterest-bearingprovisionsandliabilities2.800 -849 116 3.029 2.887Netfinancialobligations 9.870 10.880 9.785 14.288 13.983 14.171 15.174 15.304 15.656 16.347 16.676Overallfunding 17.914 15.719 15.893 18.319 19.828
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Page ½ XLIV
Appendix 44: Lufthansa's forecasted analytical income statement best case Source: own depiction
Analytical Income Statement 2011 2012 2013 2014 2015 E2016 E2017 E2018 E2019 E2020 E2021
TrafficRevenue 23.779 24.793 24.565 24.388 25.322 - - - - - -
OtherRevenue 4.955 5.342 5.463 5.623 6.734 - - - - - -
Netrevenue 28.734 30.135 30.028 30.011 32.056 31.868 33.659 35.533 37.012 38.676 39.692
Fuel -6.276 -7.392 -7.058 -6.751 -5.784 -5.206 -6.122 -6.463 -6.743 -7.145 -7.333
Rawmaterials -2.127 -2.157 -2.212 -2.252 -2.670 -2.407 -2.542 -2.683 -2.795 -2.921 -2.998
Sellingandadminexpenses -8.189 -8.284 -8.082 -8.068 -8.983 -8.784 -9.277 -9.794 -10.201 -10.660 -10.940
Staffcosts -6.678 -6.741 -7.350 -7.335 -8.075 -7.914 -8.072 -8.354 -8.702 -9.093 -9.332
Otheroperatingincome 2.324 2.785 2.042 1.890 2.832 2.502 2.643 2.790 2.906 3.037 3.117
Otheroperatingexpenses -5.293 -4.885 -4.753 -5.088 -6.106 -5.511 -5.820 -6.145 -6.400 -6.688 -6.864
TotalCostsofGoodsSold -26.239 -26.674 -27.413 -27.604 -28.786 -27.318 -29.190 -30.648 -31.935 -33.470 -34.350
GrossProfit 2.495 3.461 2.615 2.407 3.270 4.551 4.469 4.885 5.077 5.206 5.343
Resultfromequityinvestments 71 94 125 121 121 112 118 125 130 136 139
EBITDA 2.566 3.555 2.740 2.528 3.391 4.439 4.351 4.760 4.947 5.070 5.203
Depreciation -1.722 -1.839 -1.766 -1.528 -1.715 -2.012 -2.178 -2.208 -2.263 -2.365 -2.427
EBIT 844 1.716 974 1.000 1.676 2.427 2.173 2.552 2.684 2.705 2.776
Taxasreported -157 -91 -219 -105 -304 -607 -543 -638 -671 -676 -694
Taxshield -100 -105 -107 -205 88 -161 -175 -177 -182 -190 -195
NOPAT 588 1.520 648 690 1.460 1.659 1.455 1.737 1.831 1.839 1.887
interestincome 190 168 162 159 186 - - - - - -
interestexpenses -478 -540 -508 -415 -356 - - - - - -
Otherfinancialitems -110 -48 -83 -564 520 -646 -698 -709 -727 -760 -780
NetFinancialResult -398 -420 -429 -820 350 -646 -698 -709 -727 -760 -780
Taxshieldoninterest -100 -105 -107 -205 88 -161 -175 -177 -182 -190 -195
NetFinancialResultaftertax -498 -525 -536 -1.025 438 -807 -873 -886 -909 -950 -975
Discontinuedoperations -285 36 0 0 0 0 0 0 0 0 0NetEarningsaftertax -195 1.031 112 -335 1.897 852 583 851 922 888 912
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Page ½ XLV
Appendix 45: Lufthansa's forecasted analytical balance sheet best case Source: own depiction
Analytical Balance sheet 2011 2012 2013 2014 2015 2016e 2017e 2018e 2019e 2020e 2021eOperationalBalancesheetside -0,59% 5,62% 5,56% 4,13% 4,49% 2,63%
Non-currentassetsIntangibleassetswithanindefiniteusefullife&otherintangables1.575 1.568 1.569 1.587 1.657 1.681 1.775 1.874 1.952 2.040 2.093
Aircraft,reerveengines,repairablespareparts&PPE 14.550 14.818 15.371 16.764 18.152 20.398 22.083 22.388 22.950 23.982 24.612
Investmentsaccountedforusingtheequitymethod&Deferredcharges418 425 474 456 532 - - - - - -
Deferredtaxassets 33 755 622 1.489 1.200 - - - - - -
Effectiveincometaxreceivables 60 52 39 31 19 - - - - - -
Othernon-currentassets - - - - - 1.383 1460 1542 1606 1678 1.722
Totalnon-currentassets 16.636 17.618 18.075 20.327 21.560 23.461 25.318 25.804 26.507 27.699 28.427Non-currentprovisionsandliabilitiesOtherprovisions 578 582 581 601 526 - - - - - -
Deferredtaxliabilities 364 94 146 239 346 - - - - - -
Advancepaymentsreceived,deferredincomeandothernon-financialliabilities1.156 1.163 1.187 1.179 1.223 - - - - - -
Non-currentliabilities - - - - - 2.106 2.224 2.348 2.446 2.556 2.623
Totalnon-currentliabilities 2.098 1.839 1.914 2.019 2.095 2.106 2.224 2.348 2.446 2.556 2.623TotalFixedAssets 14.538 15.779 16.161 18.308 19.465 21.355 23.094 23.456 24.061 25.143 25.804CurrentassetsInventories 887 639 641 700 761 768 811 856 892 932 956
Tradereceivablesandotherreceivables 3.111 3.595 3.577 3.995 4.389 3.931 4.152 4.383 4.565 4.770 4.896
Deferredchargesandprepaidexpenses 2.838 151 146 147 158 242 256 270 281 294 302
Effectiveincometaxreceivables 727 101 72 122 85 - - - - - -
Totalcurrentassets 7.563 4.486 4.436 4.964 5.393 4.940 5.219 5.509 5.738 5.996 6.154CurrentprovisionsandliabilitiesOtherprovisions&incometaxobligtions 818 894 861 953 1.075 - - - - - -
Effectiveincometaxobligations 71 107 247 228 136 - - - - - -
Advancedpaymentsreceived,deferredincomeandothernon-financialliabilities939 933 961 924 918 913 964 1.018 1.060 1.108 1.137
Liabilitiesfromunusedflightdocuments 2.359 2.612 2.635 2.848 2.901 2.817 2.975 3.141 3.271 3.418 3.508
provisionsandallincometaxobligations - - - - - 1.136 1.200 1.266 1.319 1.378 1.415
Totalcurrentliabilities 4.187 4.546 4.704 4.953 5.030 4.865 5.138 5.424 5.650 5.904 6.059TotalWorkingCapital 3.376 -60 -268 11 363 75 80 85 88 92 95InvestedCapital 17.914 15.719 15.893 18.319 19.828 21.430 23.174 23.540 24.150 25.236 25.899
FinancialBalancesheetsideEquity 8.044 4.839 6.108 4.031 5.845Non-currentprovisionsandliabilitiesPensionprovisions 2.165 5.844 4.718 7.231 6.626
Financialliabilities 6.424 6.910 6.337 5.958 6.370
Totalnon-currentinterest-bearingprovisionsandliabilities8.589 12.754 11.055 13.189 12.996Non-currentassetsOtherinvestments 1.519 1.025 1.386 1.930 1.900
Financialassets
Totalnon-currentinterest-bearingassets 1.519 1.025 1.386 1.930 1.900Netnon-currentinterest-bearingprovisionsandliabilities 7.070 11.729 9.669 11.259 11.096CurrentprovisionsandliabilitiesFinancialliabilities 5.071 4.429 4.694 4.797 4.968
Liabilitiesinconjunctionwithassetsheldforsale 92 152 609 1.485 1.528
Totalcurrentinterest-bearingprovisionsandliabilities 5.163 4.581 5.303 6.282 6.496CurrentassetsFinancialassets 620 3.530 3.146 1.785 1.994
Cashandcashequivalents 1.127 1.436 1.550 953 1.099
Loansreceivable 616 464 491 515 516
Totalcurrentinterest-bearingassets 2.363 5.430 5.187 3.253 3.609Netcurrentinterest-bearingprovisionsandliabilities 2.800 -849 116 3.029 2.887Netfinancialobligations 9.870 10.880 9.785 14.288 13.983 14.333 15.499 15.744 16.151 16.877 17.321Overallfunding 17.914 15.719 15.893 18.319 19.828
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Page ½ XLVI
Appendix 46: Lufthansa's forecasted analytical income statement worst case Source: own depiction
Analytical Income Statement 2011 2012 2013 2014 2015 E2016 E2017 E2018 E2019 E2020 E2021
TrafficRevenue 23.779 24.793 24.565 24.388 25.322 - - - - - -OtherRevenue 4.955 5.342 5.463 5.623 6.734 - - - - - -Netrevenue 28.734 30.135 30.028 30.011 32.056 31.493 32.863 34.350 35.580 37.035 37.743
Fuel -6.276 -7.392 -7.058 -6.751 -5.784 -5.206 -6.143 -6.420 -6.650 -6.922 -7.055Rawmaterials -2.127 -2.157 -2.212 -2.252 -2.670 -2.378 -2.482 -2.594 -2.687 -2.797 -2.850Sellingandadminexpenses -8.189 -8.284 -8.082 -8.068 -8.983 -8.680 -9.058 -9.467 -9.807 -10.208 -10.403Staffcosts -6.678 -6.741 -7.350 -7.335 -8.075 -8.075 -8.237 -8.401 -8.569 -8.741 -8.908Otheroperatingincome 2.324 2.785 2.042 1.890 2.832 2.473 2.581 2.697 2.794 2.908 2.964Otheroperatingexpenses -5.293 -4.885 -4.753 -5.088 -6.106 -5.446 -5.683 -5.940 -6.153 -6.404 -6.527TotalCostsofGoodsSold -26.239 -26.674 -27.413 -27.604 -28.786 -27.312 -29.021 -30.126 -31.072 -32.163 -32.778
GrossProfit 2.495 3.461 2.615 2.407 3.270 4.181 3.842 4.224 4.508 4.871 4.965
Resultfromequityinvestments 71 94 125 121 121 111 115 121 125 130 133EBITDA 2.566 3.555 2.740 2.528 3.391 4.071 3.727 4.103 4.383 4.741 4.832
Depreciation -1.722 -1.839 -1.766 -1.528 -1.715 -1.988 -2.126 -2.134 -2.176 -2.265 -2.308EBIT 844 1.716 974 1.000 1.676 2.083 1.601 1.969 2.207 2.477 2.524
Taxasreported -157 -91 -219 -105 -304 -521 -400 -492 -552 -619 -631Taxshield -100 -105 -107 -205 88 -159 -170 -171 -175 -182 -185NOPAT 588 1.520 648 690 1.460 1.402 1.030 1.305 1.481 1.676 1.708
interestincome 190 168 162 159 186 - - - - - -interestexpenses -478 -540 -508 -415 -356 - - - - - -Otherfinancialitems -110 -48 -83 -564 520 -638 -682 -685 -699 -728 -742NetFinancialResult -398 -420 -429 -820 350 -638 -682 -685 -699 -728 -742Taxshieldoninterest -100 -105 -107 -205 88 -159 -170 -171 -175 -182 -185NetFinancialResultaftertax -498 -525 -536 -1.025 438 -797 -852 -857 -874 -910 -927Discontinuedoperations -285 36 0 0 0 0 0 0 0 0 0NetEarningsaftertax -195 1.031 112 -335 1.897 605 178 448 607 766 780
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Page ½ XLVII
Appendix 47: Lufthansa's forecasted analytical income statement base case Source: own depiction
Analytical Balance sheet 2011 2012 2013 2014 2015 2016e 2017e 2018e 2019e 2020e 2021eOperationalBalancesheetside -1,77% 4,34% 4,52% 3,56% 4,08% 1,91%
Non-currentassetsIntangibleassetswithanindefiniteusefullife&otherintangables1.575 1.568 1.569 1.587 1.657 1.661 1.733 1.811 1.876 1.953 1.990
Aircraft,reerveengines,repairablespareparts&PPE14.550 14.818 15.371 16.764 18.152 20.158 21.561 21.642 22.062 22.964 23.403
Investmentsaccountedforusingtheequitymethod&Deferredcharges418 425 474 456 532 - - - - - -
Deferredtaxassets 33 755 622 1.489 1.200 - - - - - -
Effectiveincometaxreceivables 60 52 39 31 19 - - - - - -
Othernon-currentassets - - - - - 1.366 1426 1490 1544 1607 1.638
Totalnon-currentassets 16.636 17.618 18.075 20.327 21.560 23.185 24.719 24.944 25.482 26.524 27.031Non-currentprovisionsandliabilitiesOtherprovisions 578 582 581 601 526 - - - - - -
Deferredtaxliabilities 364 94 146 239 346 - - - - - -
Advancepaymentsreceived,deferredincomeandothernon-financialliabilities1.156 1.163 1.187 1.179 1.223 - - - - - -
Non-currentliabilities - - - - - 2.081 2.172 2.270 2.351 2.447 2.494
Totalnon-currentliabilities 2.098 1.839 1.914 2.019 2.095 2.081 2.172 2.270 2.351 2.447 2.494TotalFixedAssets 14.538 15.779 16.161 18.308 19.465 21.104 22.548 22.674 23.131 24.076 24.537CurrentassetsInventories 887 639 641 700 761 759 792 828 857 892 909
Tradereceivablesandotherreceivables 3.111 3.595 3.577 3.995 4.389 3.885 4.054 4.237 4.389 4.568 4.655
Deferredchargesandprepaidexpenses 2.838 151 146 147 158 239 250 261 270 281 287
Effectiveincometaxreceivables 727 101 72 122 85 - - - - - -
Totalcurrentassets 7.563 4.486 4.436 4.964 5.393 4.882 5.095 5.326 5.516 5.742 5.852CurrentprovisionsandliabilitiesOtherprovisions&incometaxobligtions 818 894 861 953 1.075 - - - - - -
Effectiveincometaxobligations 71 107 247 228 136 - - - - - -
Advancedpaymentsreceived,deferredincomeandothernon-financialliabilities939 933 961 924 918 902 941 984 1.019 1.061 1.081
Liabilitiesfromunusedflightdocuments 2.359 2.612 2.635 2.848 2.901 2.784 2.905 3.036 3.145 3.273 3.336
provisionsandallincometaxobligations - - - - - 1.122 1.171 1.224 1.268 1.320 1.345
Totalcurrentliabilities 4.187 4.546 4.704 4.953 5.030 4.808 5.017 5.244 5.432 5.654 5.762TotalWorkingCapital 3.376 -60 -268 11 363 74 78 82 85 88 90InvestedCapital 17.914 15.719 15.893 18.319 19.828 21.178 22.626 22.756 23.215 24.165 24.627
FinancialBalancesheetsideEquity 8.044 4.839 6.108 4.031 5.845Non-currentprovisionsandliabilitiesPensionprovisions 2.165 5.844 4.718 7.231 6.626
Financialliabilities 6.424 6.910 6.337 5.958 6.370
Totalnon-currentinterest-bearingprovisionsandliabilities8.589 12.754 11.055 13.189 12.996Non-currentassetsOtherinvestments 1.519 1.025 1.386 1.930 1.900
Financialassets
Totalnon-currentinterest-bearingassets1.519 1.025 1.386 1.930 1.900Netnon-currentinterest-bearingprovisionsandliabilities7.070 11.729 9.669 11.259 11.096CurrentprovisionsandliabilitiesFinancialliabilities 5.071 4.429 4.694 4.797 4.968
Liabilitiesinconjunctionwithassetsheldforsale92 152 609 1.485 1.528
Totalcurrentinterest-bearingprovisionsandliabilities5.163 4.581 5.303 6.282 6.496CurrentassetsFinancialassets 620 3.530 3.146 1.785 1.994
Cashandcashequivalents 1.127 1.436 1.550 953 1.099
Loansreceivable 616 464 491 515 516
Totalcurrentinterest-bearingassets 2.363 5.430 5.187 3.253 3.609Netcurrentinterest-bearingprovisionsandliabilities2.800 -849 116 3.029 2.887Netfinancialobligations 9.870 10.880 9.785 14.288 13.983 14.164 15.132 15.219 15.526 16.161 16.470Overallfunding 17.914 15.719 15.893 18.319 19.828
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Page ½ XLVIII
Appendix 48: Lufthansa's DCF free cash flow calculation base case Source: own depiction
Free Cash Flow Calculations 2016e 2017e 2018e 2019e 2020e 2021eyearsfromvaluationdate 1 2 3 4 5 6 NOPAT 1.469 1.124 1.405 1.598 1.823 1.830 +Depreciationandamortization 2.004 2.135 2.218 2.303 2.413 2.494 -CAPEXCapitalizednon-currentsassets(1.1) 18.152 20.168 21.620 21.763 22.246 23.228 Capitalizednon-currentassets(31.12) 20.168 21.620 21.763 22.246 23.228 23.695
Deltacapitalizednon-currentassets 2.016 1.452 143 483 983 467Depreciationandamortization 2.004 2.135 2.218 2.303 2.413 2.494 -TotalCAPEX 4.020 3.587 2.361 2.786 3.395 2.961non-currentassetsbeginning 1.313 946 990 1.038 1.078 1.125 non-currentassetsend 946 990 1.038 1.078 1.125 1.148
-Investmentsinotherlong-termassets -367 43 48 40 48 23-ChangeinworkingcapitalWorkingcapital(1.1) 363 74 79 82 85 89 WorkingCapital(31.12) 74 79 82 85 89 91 Deltaworkingcapital -289 4 4 3 4 2FreeCashFlow(FCF) 108 -375 1.211 1.072 789 1.339+Taxsavingsduetotax-deductibledebtTotalCashFlow(TCF) 108 -375 1.211 1.072 789 1.339Netinterest-bearingprovisionsandliabilities(1.1) 13.983 14.171 15.174 15.304 15.656 16.347 Netinterest-bearingprovisionsandliabilities(31.12) 14.171 15.174 15.304 15.656 16.347 16.676 +Deltainterest-bearingprovisionsandliabilities 188 1.003 130 352 692 329 -netfinancialexpenses 638- 683- 689- 705- 736- 751- FlowtoEquity(FTE) -342 -56 651 719 744 916WACC 6,73%DCFValuation:PVFCF 101 -329 996 826 569PVForecastPhase 2.163 PVTerminalPhase 20.474 EnterpriseValue(EV) 22.637 DebtValue 13.983 EquityValue 8.654 -non-controllinginterest 24 ValueofCommonStock 8.630€ Commonstockprice 18,41€
90,4%
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Page ½ XLIX
Appendix 49: Lufthansa's DCF free cash flow calculation best case Source: own depiction
Free Cash Flow Calculations 2016e 2017e 2018e 2019e 2020e 2021eyearsfromvaluationdate 1 2 3 4 5 6NOPAT 1.659 1.455 1.737 1.831 1.839 1.887+Depreciationandamortization 2.004 2.135 2.218 2.303 2.413 2.494-CAPEXCapitalizednon-currentsassets(1.1) 18.152 20.398 22.083 22.388 22.950 23.982Capitalizednon-currentassets(31.12) 20.398 22.083 22.388 22.950 23.982 24.612
Deltacapitalizednon-currentassets 2.246 1.685 306 561 1.032 630Depreciationandamortization 2.004 2.135 2.218 2.303 2.413 2.494-TotalCAPEX 4.249 3.820 2.524 2.864 3.445 3.124
non-currentassetsbeginning 1.313 957 1.011 1.067 1.112 1.162non-currentassetsend 957 1.011 1.067 1.112 1.162 1.192
-Investmentsinotherlong-termassets -356 54 56 44 50 31
-ChangeinworkingcapitalWorkingcapital(1.1) 363 75 80 85 88 92WorkingCapital(31.12) 75 80 85 88 92 95Deltaworkingcapital -288 5 4 4 4 2
FreeCashFlow(FCF) 57 -288 1.370 1.222 752 1.224
+Taxsavingsduetotax-deductibledebtTotalCashFlow(TCF) 57 -288 1.370 1.222 752 1.224
Netinterest-bearingprovisionsandliabilities(1.1) 13.983 14.333 15.499 15.744 16.151 16.877Netinterest-bearingprovisionsandliabilities(31.12) 14.333 15.499 15.744 16.151 16.877 17.321+Deltainterest-bearingprovisionsandliabilities 350 1.166 245 407 726 443-netfinancialexpenses 646- 698- 709- 727- 760- 780-FlowtoEquity(FTE) -239 180 906 902 719 887
WACC 6,73%DCFValuation:PVFCF 53 -253 1.127 941 543
PVForecastPhase 2.412PVTerminalPhase 21.528EnterpriseValue(EV) 23.940DebtValue 13.983EquityValue 9.957-non-controllinginterest 24ValueofCommonStock 9.933€Commonstockprice 21,19€
89,9%
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Page ½ L
Appendix 50: Lufthansa's DCF free cash flow calculation worst case Source: own depiction
Free Cash Flow Calculations 2016e 2017e 2018e 2019e 2020e 2021eyearsfromvaluationdate 1 2 3 4 5 6NOPAT 1.402 1.030 1.305 1.481 1.676 1.708+Depreciationandamortization 2.004 2.135 2.218 2.303 2.413 2.494-CAPEXCapitalizednon-currentsassets(1.1) 18.152 20.158 21.561 21.642 22.062 22.964Capitalizednon-currentassets(31.12) 20.158 21.561 21.642 22.062 22.964 23.403
Deltacapitalizednon-currentassets 2.006 1.403 82 420 902 439Depreciationandamortization 2.004 2.135 2.218 2.303 2.413 2.494-TotalCAPEX 4.009 3.538 2.300 2.722 3.315 2.933non-currentassetsbeginning 1.313 946 987 1.032 1.069 1.112non-currentassetsend 946 987 1.032 1.069 1.112 1.134
-Investmentsinotherlong-termassets -367 41 45 37 44 21-ChangeinworkingcapitalWorkingcapital(1.1) 363 74 78 82 85 88WorkingCapital(31.12) 74 78 82 85 88 90Deltaworkingcapital -289 4 4 3 3 2FreeCashFlow(FCF) 52 -418 1.175 1.021 726 1.246+Taxsavingsduetotax-deductibledebtTotalCashFlow(TCF) 52 -418 1.175 1.021 726 1.246Netinterest-bearingprovisionsandliabilities(1.1) 13.983 14.164 15.132 15.219 15.526 16.161Netinterest-bearingprovisionsandliabilities(31.12) 14.164 15.132 15.219 15.526 16.161 16.470+Deltainterest-bearingprovisionsandliabilities 181 968 87 307 635 309-netfinancialexpenses 638- 682- 685- 699- 728- 742-FlowtoEquity(FTE) -405 -131 577 629 633 813WACC 6,73%DCFValuation:PVFCF 49 -367 967 787 524PVForecastPhase 1.960PVTerminalPhase 18.657EnterpriseValue(EV) 20.617DebtValue 13.983EquityValue 6.634-non-controllinginterest 24ValueofCommonStock 6.610€Commonstockprice 14,10€
90,5%
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Page ½ LI
Appendix 51: Sensitivity analysis of base case Source: own depiction
22.637 2,6% 3,1% 3,6% 4,1% 4,6% 18,41 3,5% 4,5% 5,5% 6,5% 7,5%5,7% 32.084 35.248 39.892 47.367 61.403 -0,05% 55,64 37,10 24,83 16,11 9,616,2% 27.343 29.304 32.007 35.974 42.361 0,45% 48,12 32,25 21,44 13,61 7,696,7% 23.753 24.998 26.639 28.901 32.222 0,95% 41,74 28,00 18,41 11,35 5,947,2% 20.942 21.736 22.749 24.084 25.925 1,45% 36,27 24,25 15,69 9,28 4,327,7% 18.681 19.181 19.802 20.593 21.636 1,95% 31,52 20,92 13,23 7,40 2,83
18 1,0% 1,5% 2,0% 2,5% 3,0% #DIV/0! 1,0% 1,5% 2,0% 2,5% 3,0%5,7% 26,62 29,43 32,99 37,66 44,04 5,7% 9,0x 8,3x 8,3x 9,0x 11,3x6,2% 20,49 22,43 24,83 27,87 31,86 6,2% 7,7x 7,3x 7,3x 7,7x 9,0x6,7% 15,45 16,79 18,41 20,41 22,96 6,7% 6,7x 6,5x 6,5x 6,7x 7,5x7,2% 11,22 12,14 13,23 14,55 16,18 7,2% 6,0x 5,8x 5,8x 6,0x 6,5x7,7% 7,64 8,25 8,97 9,82 10,85 7,7% 5,4x 5,3x 5,3x 5,4x 5,7x
0 1,0% 1,5% 2,0% 2,5% 3,0%5,7% 87% 88% 90% 92% 94%6,2% 85% 86% 88% 89% 91%6,7% 83% 84% 85% 86% 88%7,2% 82% 82% 83% 84% 85%7,7% 80% 80% 81% 82% 82%
18 0,92 1,17 1,419 1,67 1,924,5% 52,92 38,42 28,00 20,15 14,045,0% 46,35 32,60 22,81 15,48 9,805,5% 40,70 27,64 18,41 11,54 6,246,0% 35,77 23,35 14,63 8,17 3,216,5% 31,44 19,61 11,35 5,26 0,59
WA
CC
Implied Share priceBeta
MR
P
Implied Enterprise Value Implied share pricePerpetual Growth Rate MRP
WA
CC
risk
free
rate
Implied share price Implied Enterprise Value / 2016 EBITDAPerpetual Growth Rate Perpetual Growth Rate
WA
CC
WA
CC
PV of Terminal Value % of Enterprise ValuePerpetual Growth Rate
1840,8% 0,95% 1840,8% 5,5% 1840,8% 1,0%3,50% 41,74 126,8% 1,02 34,88 89,5% -12,00% 23,24 26,3%3,75% 37,78 105,2% 1,07 32,29 75,4% -11,75% 22,64 23,0%4,00% 34,20 85,8% 1,12 29,88 62,3% -11,50% 22,03 19,7%4,25% 30,95 68,2% 1,17 27,64 50,2% -11,25% 21,43 16,4%4,50% 28,00 52,1% 1,22 25,55 38,8% -11,00% 20,82 13,1%4,75% 25,29 37,4% 1,27 23,59 28,2% -10,75% 20,22 9,8%5,00% 22,81 23,9% 1,32 21,76 18,2% -10,50% 19,62 6,6%5,25% 20,52 11,5% 1,37 20,03 8,8% -10,25% 19,01 3,3%5,50% 18,41 0,0% 1,42 18,41 0,0% -10,00% 18,41 0,0%5,75% 16,45 -10,6% 1,47 16,88 -8,3% -9,75% 17,80 -3,3%6,00% 14,63 -20,5% 1,52 15,43 -16,2% -9,50% 17,20 -6,6%6,25% 12,93 -29,8% 1,57 14,07 -23,6% -9,25% 16,60 -9,8%6,50% 11,35 -38,4% 1,62 12,77 -30,6% -9,00% 15,99 -13,1%6,75% 9,86 -46,4% 1,67 11,54 -37,3% -8,75% 15,39 -16,4%7,00% 8,47 -54,0% 1,72 10,38 -43,6% -8,50% 14,78 -19,7%7,25% 7,17 -61,1% 1,77 9,27 -49,7% -8,25% 14,18 -23,0%7,50% 5,94 -67,8% 1,82 8,21 -55,4% -8,00% 13,58 -26,3%
Sesitivity to 2016 fuel costs
2016
fuel
cos
t dev
elpm
ent
Sesitivity of MRP
MR
P
Bet
a
Implied share priceSesitivity of Beta
Implied share price Implied share price
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Page ½ LII
Appendix 52: Multiple valuation core group Source: Capital IQ, 2016
Lufthansa multiples
Company Name EV/Revenue
EV/EBITDA
EV/EBIT
P/EPS
EV/1y Revenue
(Capital IQ)
EV/1y EBITDA (Capital IQ)
1y P/E (Capital IQ)
Lufthansa 0,3x 2,1x 3,7x 3,2x 0,3x 2,3x 5,3x
Peer Group multiples
Company Name EV/Revenue
EV/EBITDA
EV/EBIT
P/EPS
EV/1y Revenue
(Capital IQ)
EV/1y EBITDA (Capital IQ)
1y P/E (Capital IQ)
United 0,8x 4,2x 5,7x 9,3x 0,81x 4,83x 11,09xIAG Group 0,6x 3,5x 5,5x 6,5x 0,61x 3,49x 6,40xDelta Air Lines 1,0x 5,0x 6,3x 8,0x 1,02x 5,13x 10,02xAmerican Airlines 1,0x 5,0x 6,3x 4,8x 1,00x 5,29x 10,42xAir France-KLM 0,3x 2,5x 6,3x 2,8x 0,26x 2,55x 3,57x
Summary Multiples
EV/Revenues
EV/EBITDA
EV/EBIT
EV/1y Revenue
(Capital IQ)
EV/1y EBITDA (Capital IQ)
P/EPSForward P/E (Capital IQ)
High 1,0x 5,0x 6,3x 1,0x 5,3x 9,3x 11,1xLow 0,3x 2,5x 5,5x 0,3x 2,6x 2,8x 3,6xMean (excl. Lufthansa) 0,7x 4,0x 6,0x 0,7x 4,3x 6,3x 8,3xMedian (excl. Lufthansa) 0,8x 4,2x 6,3x 0,8x 4,8x 6,5x 10,0x
Implied Enterprise ValueHigh 32.287 18.842 13.810 32.184 18.152 Low 8.048 9.458 11.924 8.299 8.757 Mean (excl. Lufthansa) 23.421 15.239 13.119 23.424 14.619 Median (excl. Lufthansa) 25.729 15.871 13.656 25.624 16.583
Implied Equity ValueHigh 30.048 16.603 11.571 29.945 15.913 16.887 12.013 Low 5.809 7.219 9.685 6.060 6.518 4.989 3.861 Mean (excl. Lufthansa) 21.182 13.000 10.880 21.185 12.380 11.375 8.988 Median (excl. Lufthansa) 23.490 13.632 11.417 23.385 14.344 11.759 10.846
Implied Share PriceHigh 64,1 35,4 24,7 63,9 33,9 36,0 25,6 Low 12,4 15,4 20,7 12,9 13,9 10,6 8,2 Mean (excl. Lufthansa) 45,2 27,7 23,2 45,2 26,4 24,3 19,2 Median (excl. Lufthansa) 50,1 29,1 24,4 49,9 30,6 25,1 23,1
Implied Share Price
EV/Revenues
EV/EBITDA
EV/EBIT
EV/1y Revenue
(Capital IQ)
EV/1y EBITDA
(Capital IQ) P/EPS Forward P/E
(Capital IQ)
High 64,10 € 35,42 € 24,68 € 63,88 € 33,94 € 36,02 € 25,63 € Low 12,39 € 15,40 € 20,66 € 12,93 € 13,90 € 10,64 € 8,24 € Mean (excl. Lufthansa) 45,18 € 27,73 € 23,21 € 45,19 € 26,41 € 24,26 € 19,17 € Median (excl. Lufthansa) 50,11 € 29,08 € 24,35 € 49,88 € 30,60 € 25,08 € 23,14 €
Mean Equity Value Across MultiplesImplied
Equity ValueImplied share
priceHigh 18.997,4 40,5 Low 6.306,1 13,5 Mean (excl. Lufthansa) 14.141,5 30,2 Median (excl. Lufthansa) 15.553,3 33,2
Enterprise Value Multiples Pricing Multiples
Enterprise Value Multiples Pricing Multiples
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Appendix 53: Airline Merger Cases after EC Merger Regulation 2004 Source: EU COM; Chan & Hsu (2005)
