Valuation of Tesla, Inc. - Research@CBS · autonomous car sharing initiative. Fir this initiative to be realized, Tesla first has to achieve full self-driving capability (level 5

Valuation of Tesla, Inc.

Is the share price ($418) as of 31st December 2019 based on

fundamentals?

A discounted cash flow (DCF) valuation approach accompanied by

a real options valuation (ROV)

Copenhagen Business School, July 2020

Master Thesis

Supervisor: Michael Ahm

Number of pages: 74

Number of characters: 135,243

Date of submission: 15.07.2020

Fatih Kemal Yılmaz (96861)

Cand. merc. International Business

1

Executive Summary

The purpose of this paper is to assess whether the price of one Tesla share as of 31st December 2019,

$418, is based on fundamentals. To address this research question, an overview of the industry

specific outlook and trends will be provided. This will be followed up by an in-depth analysis,

touching upon external as well as internal factors that might affect Tesla’s business case and to

identify sources for value creation. A financial statement analysis will round up the analysis and set

the basis –together with the insights from the strategic analysis– for the projection of future cash

flows. This will be done according to management guideline as well as historical performance.

After determining the weighted average cost of capital (WACC) that is based on various assumptions,

using a discounted cash flow (DCF) model the equity value as of 31st December 2019 will be assessed.

The DCF model will be augmented by determining the option value for Tesla’s robotaxis project, an

autonomous car sharing initiative. Fir this initiative to be realized, Tesla first has to achieve full self-

driving capability (level 5 autonomy) and gain the approval of the regulators.

Tesla is a well-established player in the electric vehicle segment and is ahead of its competitors when

it comes to the battery range as well as battery costs per kWh, autonomous driving and overall product

performance. However, the well-established players are gradually entering the electric vehicle market

and could catch up with Tesla as they have more resources and scale and scope advantages. By

moving from just being a high-premium car manufacturer (Roadster 2008, Model S & X), Tesla

launched two more affordable models, Model 3 & Y (2017 & 2020). However, Tesla is expected to

have high CAPEX in the next the fiscal years, ≈$3.5bn per year. This is necessary to build the

production plants for the upcoming models Semi, Roadster and Cybertruck. Hence, Tesla starts to

cover the major forms of terrestrial transport, as mentioned in the second part of Tesla’s master plan

in 2016.

Estimating the WACC to be 6.87% and applying the DCF model, the computed share price for Tesla

as of 31st December is $1638 leading to a total market capitalization of $296.4bn. Considering the

option value ($42bn) for the robotaxis project a share price of $1,870 or a market cap of $338.5bn is

achieved. While the share price is almost four-times the closing price of 31st December 2019, Tesla’s

currently traded share price provides further validity for this estimation.

2

Table of Contents

Table of Contents ................................................................................................................................. 2

List of Figures ...................................................................................................................................... 4

List of Tables ....................................................................................................................................... 5

List of Abbreviations ........................................................................................................................... 6

1. Introduction to the Paper ............................................................................................................ 8

1.1 Introduction & Motivation ......................................................................................................... 8

1.2 Research Question ...................................................................................................................... 8

1.3 Data Collection .......................................................................................................................... 8

1.4 Delimitation ............................................................................................................................... 8

1.5 Structure of the Paper ................................................................................................................. 9

2. Introduction to Tesla and the Automotive Industry .................................................................. 10

2.1 Tesla ......................................................................................................................................... 10

2.2 Operating Business Segments .................................................................................................. 10

2.2.1 Automotive Segment ........................................................................................................ 10

2.3 Geographical Segments ............................................................................................................ 14

2.4 Share Price Development ......................................................................................................... 15

2.5 The Automotive Industry ......................................................................................................... 16

2.5.1 The Electric Vehicle Market ............................................................................................. 17 2.5.2 Global Automotive Outlook and Trends ........................................................................... 18

3. Strategic Analysis ..................................................................................................................... 20

3.1 External Analysis – PESTEL ................................................................................................... 20

3.1.1 Political & Legal Factors .................................................................................................. 20 3.1.2 Economic Factors .............................................................................................................. 23 3.1.3 Social and Environmental Factors .................................................................................... 25 3.1.4 Technological Factors ....................................................................................................... 25 3.1.5 Conclusion of the External Analysis ................................................................................. 27

3.2 Industry Analysis – Porter’s Five Forces ................................................................................. 28

3.2.1 Threat of New Entrants ..................................................................................................... 28 3.2.2 Threat of Substitute Products ............................................................................................ 30 3.2.3 Bargaining Power of Suppliers ......................................................................................... 30 3.2.4 Bargaining Power of Customers ....................................................................................... 31 3.2.5 The Intensity of Existing Competitive Rivalry ................................................................. 32 3.2.6 Future Success Criteria for the Automotive Industry ....................................................... 33

3.3 Internal Analysis – Value Chain Analysis & VRIN ................................................................ 34

3.3.1 Production Capabilities ..................................................................................................... 34 3.3.2 Product Capabilities .......................................................................................................... 36 3.3.3 Charging Infrastructure ..................................................................................................... 38 3.3.4 Distribution Network ........................................................................................................ 39

3

3.3.5 CEO & Brand: Defining the Future Business Model ....................................................... 39 3.3.6 Customer Understanding – Changed Perception of the Car ............................................. 40 3.3.7 VRIN ................................................................................................................................. 41

4. Financial Statement Analysis ................................................................................................... 42

4.1 Income Statement Analysis ...................................................................................................... 42

4.2 Financial Ratios – Determining the ROE ................................................................................ 43

4.3 Conclusion of the Financial Statement Analysis ..................................................................... 45

5. SWOT Analysis ........................................................................................................................ 47

6. Forecasting................................................................................................................................ 48

6.1 Forecast Period ......................................................................................................................... 48

6.2 Terminal Growth Rate ............................................................................................................. 48

6.3 Forecast – Income Statement ................................................................................................... 49

6.3.1 Forecasting Automotive Sales Revenues .......................................................................... 49 6.3.2 Forecasting other Income Statement Items - Revenues .................................................... 54

7. Weighted Average Cost of Capital (WACC) ........................................................................... 57

7.1 Target Capital Structure ........................................................................................................... 57

7.2 Cost of Equity (re) .................................................................................................................... 58

7.3 Cost of Debt (rd) ....................................................................................................................... 61

7.4 Overview of WACC components ............................................................................................ 61

8. Valuation – Discounted Cash Flow Model (DCF) ................................................................... 63

8.1 DCF – Theoretical background ................................................................................................ 63

8.2 Tesla – DCF valuation ............................................................................................................. 64

9. Sensitivity Analysis .................................................................................................................. 66

10. Real Options Valuation (ROV) ................................................................................................ 68

10.1 Theoretical Background ......................................................................................................... 68

10.2 Tesla – Project Valuation using ROV .................................................................................... 69

10.2.1 Identifying the Option ..................................................................................................... 69 10.2.2 Length of the Option ....................................................................................................... 69 10.2.3 Uncertainty ...................................................................................................................... 70 10.2.4 Robotaxi Project – Option Value .................................................................................... 70

11. Conclusive Summary ................................................................................................................ 74

Bibliography....................................................................................................................................... 75

Appendix ............................................................................................................................................ 81

4

List of Figures

Figure 1: Structure of paper ............................................................................................................................... 9

Figure 2: Tesla’s distribution of revenue across main geographical markets .................................................. 15

Figure 3: Tesla’s price per share in USD ........................................................................................................ 15

Figure 4: Global passenger car sales 2006-2019 (CAGR of 2.27%) ............................................................... 16

Figure 5: KPMG Global Automotive Executive Survey 2019 ........................................................................ 19

Figure 6: World vehicle sales growth in % vs. World GDP growth in % for 2016-2019 ............................... 23

Figure 7: GPD development forecast for China, Europe and the U.S: ............................................................ 24

Figure 8: Expected share of battery prices from 2016 to 2030 ........................................................................ 26

Figure 9: Porter’s Five Forces ......................................................................................................................... 28

Figure 10: Value Chain Analysis of Tesla ....................................................................................................... 34

Figure 11: Tesla Battery Costs vs. Industry Average Battery Cost ($ per kWh) ............................................ 36

Figure 12: Ranking of different EVs with respect to range in miles ............................................................... 37

Figure 13: Income statement – historical performance ................................................................................... 42

Figure 14: Operating efficiency ....................................................................................................................... 43

Figure 15: Asset use efficiency ....................................................................................................................... 44

Figure 16: Short-term liquidity risk ................................................................................................................. 44

Figure 17: Long-term liquidity risk ................................................................................................................. 44

Figure 18: Return on equity ............................................................................................................................. 45

Figure 19: Forecast of production capacity for 2020-2026 ............................................................................. 49

Figure 20: Forecast of total deliveries for 2020-2026 ..................................................................................... 51

Figure 21: Forecast of total revenue for 2020-2026 ........................................................................................ 53

Figure 22: Pro forma income statement for 2020-2026 ................................................................................... 55

Figure 23: Pro forma balance sheet for 2020-2026 ......................................................................................... 56

Figure 24: U.S. government treasury bonds from 2010 to 2019 in % ............................................................. 59

Figure 25: WACC ............................................................................................................................................ 62

Figure 26: DFC valuation as of 31.12.2019 .................................................................................................... 64

Figure 27: WACC & Terminal Growth Rate .................................................................................................. 66

Figure 28: Risk-free Rate & Target Capital Structure .................................................................................... 67

Figure 29: Assumptions for robotaxi DCF ...................................................................................................... 71

Figure 30: PV of set-up and development costs required to exercise the option (in USDm) .......................... 71

Figure 31: PV of net cash flows from taking the project now (in USDm) ...................................................... 72

Figure 32: DCF output for robotaxi project (in USDm) .................................................................................. 73

5

List of Tables

Table 1: Tesla’s international vehicle production capacities ........................................................................... 14

Table 2: Government financial incentives for electric vehicles in Tesla’s main markets ............................... 22

Table 3: Government non-financial incentives for electric vehicles in Tesla’s main markets ........................ 22

Table 4: Forecast of Tesla’s international annual production capacities ......................................................... 35

Table 5: Summary of VRIN analysis .............................................................................................................. 41

Table 6: SWOT Analysis of Tesla ................................................................................................................... 47

Table 7: Average Beta for Tesla ...................................................................................................................... 60

6

List of Abbreviations

AV autonomous vehicle

BEVs battery electric vehicles

BMW Bayerische Motoren Werke

bn billion

CAGR compound annual growth rate

CAPEX capital expenditure

CAPM capital asset pricing model

CEO Chief Executive Officer

D+E debt and equity

DCF Discounted Cash Flow

ECO ecology

EFTA European Free Trade Association

EQ Electric Intelligence

et al. et alia

EU European Union

EV enterprise value

EVs electronic vehicles

FCF forecasted free cash flow

FECVs fuel cell electric vehicles

FSD full self-driving

GDP gross domestic product

GM General Motors

h hour(s)

HD high-definition

HEVs hybrid electric vehicles

ICE internal combustion engine

Inc. Incorporated

IPO Initial Public Offering

km kilometer

km/h kilometer per hour

kW Kilowatt

kWh Kilowatt-hour(s)

m million

mi miles

mph miles per hour

mrp market risk premium

NASDAQ National Association of Securities Dealers Automated Quotations

NIBL Net-Interest Bearing Liabilities

OPEC Organization of the Petroleum Exporting Countries

PESTEL Political (P), Economic (E), Social (S), Technological (T), Environmental (E),

and Legal (L)

PHEVs plug-in hybrid vehicles

PV present value

R&D Research and development

RMB Renminbi (Chinese currency)

7

ROV Real options valuation

SEC Securities and Exchange Commission

SUV Sport Utility Vehicle

T-bills Treasury-bills

T-bonds Treasury bonds

T-notes Treasury notes

TSLA Tesla Motors Incorporated (NASDAQ: TSLA)

U.S. United States

U.S. DoE U.S. Department of Energy

USD U.S. Dollar

VAT value-added tax

VRIN Valuable, Rare, Inimitable and Non-Substituable

VW Volkswagen

w/o without

WACC Weighted Average Cost of Capital

Chapter 1: Introduction to the Paper 8

1. Introduction to the Paper

1.1 Introduction & Motivation

The automotive industry is highly cyclical and exposed to economic booms and busts. Further, due

to the high barriers to entry and exit, the automotive industry has been characterized as an

oligopolistic competitive environment. Thus, of 2,000 U.S. car companies at the start of the 20th

century three endured (Financial Times, 07/2017). Additionally, after a century of internal

combustion engine (ICE) drivetrain technologies polluting the environment, an institutional swift

towards EVs can be observed. This makes it even more interesting to analyze and value Tesla as it

is, on the one hand, a very young company, and on the other hand, selling solely electric vehicles

(EVs). With having a successful and visionary entrepreneur as its CEO, Elon Musk, Tesla keeps

disrupting the market with its technologies. Many analysts therefore believe that Tesla is not valued

for the here-and-now but rather for its high disruptive potential and future growth rate (Financial

Times, 02/2020). To analyze whether this is truly the case provides further relevance for this paper.

1.2 Research Question

The aim of this paper is to provide an in-depth analysis of Tesla to assess whether its high share price

and market capitalization can be justified. Hence, the research question is defined as follows:

“Is Tesla’s share price as of 31st December 2019 based on fundamentals?”

1.3 Data Collection

While addressing the research question, this paper will solely make use of publicly available

information in the form of Tesla’s published SEC reports, consulting & market research report as

well as reliable financial information resources such as Reuters, Bloomberg, Nasdaq, Yahoo Finace.

1.4 Delimitation

Even though Tesla is a globally operating company, due to the scope of the paper following

delimitations are made:

Tesla is a vertically integrated company and operates within two segments: 1.) automotive,

and 2.) energy generation & storage. Since, the automotive sales revenue made up ≈85% of

the total revenues in the last two fiscal years, the main focus will be given to this segment.

Chapter 1: Introduction to the Paper 9

The macro analysis –PESTEL– analysis will focus on Tesla’s main markets that are also

considered to be the most relevant for the automotive industry, namely: U.S., China and

Western Europe.

To compare Tesla’s performance in the automotive industry, BMW, VW and Daimler are

taken as benchmarks.

1.5 Structure of the Paper

In order to provide a thorough answer for the research question, the case company will be presented

first. An introduction to the automotive

industry and electric vehicle segment will

follow, rounded up by an overview of the

megatrends in the automotive industry.

Hereinafter, the strategic analysis

contains a macro-environmental analysis,

an industry analysis, and in internal

analysis across key value chain

capabilities to seize the market

opportunities and identify real options

that relate to Tesla’s business case. The

financial statement analysis will

supplement the strategic analysis and

provide major insights for projections

regarding future cash flows. After doing

so and determining the WACC, a DCF

valuation approach will be performed.

This will be augmented by valuing the

most relevant real option applying to

Tesla that was identified in the strategic

analysis.

Chapter 1: Introduction to the Paper

Chapter 2: Introduction to Tesla and the

Automotive Industry

External Analysis – PESTEL

Industry Analysis – Porter’s Five Forces

Internal Analysis – Value Chain Analysis & VRIN

Chapter 3: Strategic Analysis

Chapter 7: WACC

Chapter 5: SWOT Analysis

Income Statement Analysis

Financial Ratios – Determining the ROE

Conclusion of the Financial Statement Analysis

Chapter 4: Financial Statement Analysis

Chapter 6: Forecasting

Chapter 10: ROV

Chapter 8: DCF

Chapter 9: Sensitivity Analysis

Chapter 11: Conclusive Summary

Figure 1: Structure of paper

Chapter 2: Introduction to Tesla and the Automotive Industry 10

2. Introduction to Tesla and the Automotive Industry

The aim of this chapter is to introduce the reader to the case company Tesla and to the automotive

industry, as Tesla is operating mainly in this industry. This will help to better understand Tesla’s

standout characteristics in the industry as well as to get an overview of the industry-specific outlook

and trends.

2.1 Tesla

In 2003, Tesla Inc. (formerly Tesla Motors, Inc.) was founded in San Carlo, California, with the

mission “to accelerate the advent and sustainable transport by bringing compelling mass-market

electric cars to market as soon as possible” (Tesla, 11/2018). Hence, Tesla designs, develops and

manufactures high-performance fully electric vehicles and energy generation storage systems. In

addition, Tesla sells its products directly to their customers unlike other car manufacturers that sell

through franchised dealerships (Tesla, Annual Report 2019). In 2008, Elon Musk, who has been a

member of the board of directors since 2004, became the CEO of the innovative company (CNBC,

01/2020). On 29th of June, Tesla had its IPO at a share price of $17 and is currently traded on the

NASDAQ exchange under the ticker TSLA (Investor FAQs, Tesla 2020). Having started developing

and selling premium electronic vehicles such as the Tesla Roadster 2008 and later Model S and Model

X, Tesla positioned itself as a niche car manufacturer. Now, with the Model 3 and Model Y launches,

it aims to successfully switchover to being a volume car manufacturer. This was intended and has

been a part of Tesla’s master plan, which will be elaborated later on. Further, Tesla is considered a

serious competitor by the CEO of Volkswagen (VW) as Tesla cars are considered software cars on

unique hardware, hence are up-to-date to compete in the age of the software car (Harvard Business

Review, 02/2020).

2.2 Operating Business Segments

As already touched upon, Tesla operates as two reportable segments: 1.) automotive, and 2.) energy

generation & storage (Tesla Annual Report, 2019). These two segments will be outlined in the

following.

2.2.1 Automotive Segment

Tesla’s revenues are almost completely generated through this segment, as the automotive revenues

accounted for 93.7% of the revenues in 2019 (Tesla, Annual Report 2019). Before illustrating upon


the previous, current and upcoming models, presenting relevant parts of Tesla’s master plan for this

segment will help us to understand the business strategy Tesla is following.

Master Plan

The first part of Tesla’s master plan, published in 2006, consists of three steps for bringing electric

vehicles to the mass market, reflecting Tesla’s mission: 1.) create a low volume expensive sports car,

2.) use that money to develop a medium volume car at a lower price, and 3.) use that money to create

an affordable, high volume car (Tesla, 08/2006).

The second part of Tesla’s master plan, published in 2016, consists of four steps. However, only three

are relevant for this segment: 1.) expand to cover the major forms of terrestrial transport, 2.)

implement self-driving technology (autonomy) and 3.) enable car sharing (Tesla, 07/2016).

Previous Model

In alignment with the first step of Tesla’s initial master plan, high-price/low volume car, Tesla

introduced the Tesla Roadster in 2008. It was the first fully electric car to use lithium-ion battery cells

and to travel from 200 to 250 miles (mi) per charge. Before Tesla terminated production in 2012,

nearly 2,500 units were sold at a starting price of $109,000 (Tesla Annual Report, 2014).

Current Models

1. Model S and Model X

Launching Model S (2012) and Model X (2015) helped accomplishing the second step of Tesla’s

initial expansion plan, producing mid-price/mid-volume car.

Model S is a five-adult premium sedan with a starting price of $69,490 including potential incentives

with up to 402 mi range on a single charge and an acceleration of 2.3 seconds from 0 to 60 mph. In

2013, it became the first electric vehicle to win the most prestigious award in the automotive industry,

the MotorTrend “Car of the Year” award. Additionally, MotorTrend named Tesla’s Model S sedan

the best of the cars that have won the publication’s “Car of the Year” award in the last 70 years

(MotorTrend, 07/2019).

Model X is a five to seven-seat interior sport utility vehicle (SUV). It has a starting price of $74,690

with potential incentives and a range of 351 mi per single charge. The Model X Performance has an

acceleration of 2.6 seconds from 0 to 60 mph.


Both, Model S as well as Model X, have the option to include an autopilot, full self-driving capability,

for $7,000. Since their launches (2012 and 2015) through 31st of March 2020, nearly 460,000 units

of both models were sold in total (in 2019, Tesla began combining sales figures for the Model S and

Model X) (Tesla Annual Report, 2012 – Quarter 1 2020).

2. Model 3 and Model Y

Model 3 (2017) and Model Y (2020, 2021 in Europe) made Tesla realize its last step of the initial

master plan, producing a low-price/high-volume electric vehicle.

The Model 3 sedan has three versions with $31,690 being the starting price, with incentives, for the

cheapest one that has an acceleration of 5.3 seconds from 0 to 60 mph and a 250 mi range per charge.

In contrast, the most expensive Model 3 version has a purchase price of $48,690 including incentives,

an acceleration of 3.2 seconds from 0 to 60 mph and a 299 mi range per single charge. In addition,

the Model 3 was the best-selling plug-in electric vehicle model worldwide with 300,000 units being

sold in 2019 (Statista, Tesla 2020).

The Model Y SUV offers a five to seven seat-interior at a starting purchase price of $56,690 with

incentives. This model can have a maximum range of 316 mi per charge and an acceleration of 3.5

seconds from 0 to 60 mph. Currently, this model is available only in the U.S. market and is expected

to launch the Asian (Chinese) and European market in 2021 (Tesla homepage, 2020).

Both, Model 3 as well as Model Y, have the option to include an autopilot, full self-driving capability,

for $7,000. Since their launches (2017 and 2020) through 31st of March 2020, nearly 460,000 units

of both models were sold in total (in 2019, Tesla began combining sales figures for the Model 3 and

Model Y) (Tesla Annual Report, 2012 – Quarter 1 2020).

Upcoming Models

1. Tesla Roadster

The Roadster is going to be a follow-up model of the 2008 version, announced in 2017 and is expected

to be on the market in 2022 (electrek, 05/2020). This model is expected to be sold for a starting price

of $200,000 – the first 1,000 to be produced, the Founder’s Series, will be sold for $250,000 – with

a range of 620 mi per charge and is claimed to be the quickest car in the world, as it has an acceleration

of 1.9 seconds from 0 to 60 mph (Tesla homepage, 2020).


2. Semi and Cybertruck

Unveiling Tesla Semi (heavy-duty truck) (2017) and the Tesla Cybertruck (light commercial

vehicle/large pickup) (2019) made realize Tesla one of the steps of its second master plan, expanding

to cover the major forms of terrestrial transport. While Tesla Semi is expected to be on the market in

late 2020, Tesla Cybertruck will make it in late 2021 or early 2022. Both models will have the option

to include an autopilot. The Semi comes in two versions and has price of $150,000 or $180,000 and

a range of 300 mi or 500 mi, whereas the Cybertruck starts at $39,990 and has a range of 250, 300 or

500 mi per charge. Lastly, interest in both models are extremely strong; while the Semi noted 2,000

preorders in mid-2019 (Teslerati, 10/2019), the Cybertruck reached a preorder number of 650,000

according to a report from Wedbush (electrek, 06/2020).

Car Sharing

As part of Tesla’s second master plan, Elon Musk announced to launch a ride-sharing app, the Tesla

Network, with its inhouse driver insurance. The first step will be to release Tesla Network with human

drivers before doing it as a full self-driving system as regulatory issues have to be cleared with regards

to autonomous driving (electrek, 02/2020). The app is expected to have a similar business model to

Uber and Tesla will keep between 25%-30% of the revenue from those rides. This initiative is

expected to be on the market in late 2020 or early 2021 (TechCrunch, 04/2019).

International Vehicle Production Capacities

Tesla has three factories available to produce its vehicles; Fremont (California, U.S.), Shanghai

(China) and Berlin-Brandenburg (Germany). Below, Table 1 provides an overview of Tesla’s

international vehicle production capabilities.

According to a Shanghai government filing, the factory in Shanghai is expected to produce 150,000

Model 3 sedans and later hike output, by including the Model Y, to 250, 000 a year once fully

completed (Reuters, 03/2020). On the other hand, the Berlin factory is projected to have a production

capacity of 500,000 annually once fully completed (Tesla, 2020). Further, while the Shanghai factory

is expected to start delivering Model Y in Q1 2021, the Model Y is expected to roll off the line at the

Berlin factory in late 2021 or early 2022 (electrek, 05/2020).


Table 1: Tesla’s international vehicle production capacities

Location Model Current installed annual capacity Status

Fremont

Model S / Model X 90,000 Production

Model 3 / Model Y 400,000

(will extend to 500,000 in 2020) Production

Shanghai Model 3 200,000 Production

Model Y – Construction

Berlin Model 3 – In development

Model Y – Construction

United States

Tesla Semi – In development

Roadster 2020 – In development

Cybertruck – In development

Sources: compiled by author / Tesla Q1 2020 Update, Quarterly Financials

2.2.2 Energy Generation & Storage Segment

Tesla’s energy generation & storage segment supplies power to homes, businesses and utilities by

selling solar panels, solar roofing and lithium-ion battery storage packs called the Powerwall (for

residential use), Powerpack (for business use) and Megapack (for utility applications) (Tesla, 2020).

In 2019, Tesla deployed 1.65 GWh of energy storage, which is more than Tesla deployed in all the

previous years combined. Further, both solar and storage deployments are expected to grow by at

least 50% in 2020 (Tesla, Q4 and FY 2019 Update). While Musk is assuming that Tesla Energy could

become as big as it’s automotive business in the future (CNBC, 12/2019), the energy generation &

storage revenues constituted only 6.3% of 2019 revenues (Tesla, Annual Report 2019).

2.3 Geographical Segments

In order to set the basis for the upcoming strategic analysis, it is crucial to identify Tesla’s main

geographical markets for the PESTEL analysis. Thus, Figure 2 below will illustrate the distribution

of revenue across each segment. Historically, the United States have been Tesla’s largest segment

accounting for 70% and 51% of the 2018 and 2019 revenues, respectively. China is the second largest

single segment, constituting 12% of the 2019 revenues. While the U.S. and China might be the top

revenue generating segments, Tesla achieved the highest revenue market share in the Netherlands

(11.1%) and Norway (9,8%), far more than in the United States (2.2%).


Figure 2: Tesla’s distribution of revenue across main geographical markets

Sources: compiled by author / Tesla annual report 2020

The Netherlands (6% in 2019) and Norway (5% in 2019) are the two biggest contributing European

markets to Tesla’s total revenues. Additionally, the “Other” segment is mostly composed by other

West European countries as well, such as Sweden, Switzerland, Portugal, Ireland, Belgium, United

Kingdom and Germany (Tesla Report 2020, Statista). Hence, the most relevant markets for Tesla’s

business can be identified as the United States (North America), Western Europe and China.

2.4 Share Price Development

Having its initial price offering (IPO) in 2010 at a share price of $17, valuing the company at about

$1.7bn, Tesla became the first publicly traded fully electric vehicle manufacturer. Tesla shares closed

the FY 2019 with shared price of $418 (a 2358% increase since IPO), leading to a market

capitalization of $75.7bn.

Figure 3: Tesla’s price per share in USD

Sources: compiled by author / Charts, compiled by author


This represents a greater market capitalization than that of the well-established player BMW

($53.6bn) and almost as much as VW ($98.3bn). This makes Tesla the third most valuable automaker

behind Toyota with a market capitalization of $195.35bn (ycharts, 12/2019). Having in mind that

Tesla delivered only 367,656 vehicles (Tesla, 2020) worldwide in 2019 while BMW and VW

delivered 2.5m vehicles and 11m vehicles (Statista) respectively, it is obvious that Tesla is valued for

its potential to disrupt the industry (Financial Times, 02/2020).

2.5 The Automotive Industry

Due to the high barriers to entry and exit, the automotive industry has been characterized as an

oligopolistic competitive environment. Thus, of 2,000 U.S. car companies at the start of the 20th

century three endured (Financial Times, 07/2017). Further, approximately 53% of the market is

controlled by the ten largest companies while 14 brands global players control more than 60

automotive brands around the world (Business Insider, 02/2018).

Figure 4: Global passenger car sales 2006-2019 (CAGR of 2.27%)

Sources: compiled by author / OICA

The number of passenger cars sold worldwide, as shown in Figure 4, has been increasing for eight

consecutive years from 49.7m in 2009 to a peaking number of 70.7m in 2017, representing an increase

of 42.3% and a compound annual growth rate (CAGR) of 4.5%. However, the last two years indicate

a negative trend in passenger car sales in all regions, showing a faster a market shrinking at a faster

rate since the financial crisis in 2007/08 (Financial Times, 12/2019). Thus, the sector accounted for

25% of the gross domestic product (GDP) slowdown in 2018 and roughly 30% of the year’s drop in

global trade (Financial Times, 11/2019). This trend might last longer also due to the recent Covid-19

pandemic, as IHS Markit forecasts car sales (all vehicles) to drop by 18% to 73.3m. The car sales in

the United States (U.S.), Europe and China are expected to decline by 26%, 17% and 14%


respectively in 2020 (IHS Markit, 04/2020). Further, volume growth differs across global markets,

as shown in Figure 4: while the U.S. and the EU + European Free Trade Association (EFTA)

experienced a decline during the financial crisis in 2007/08, the passenger car sales skyrocketed in

China, indicating a total increase of 312.3% and a CAGR of 11.6% from 2006 to 2009. Since 2011,

China has been the largest single market with regards to passenger car sales followed by the EU +

EFTA and the U.S. Lastly, over the illustrated time period, the EU + EFTA shows no significant

change, thus implying a CAGR of less than -1%. The U.S. experienced a decline of 39.3% and a

CAGR of -3.8%, hence did not reach its pre-crisis sales volume.

2.5.1 The Electric Vehicle Market

For more than 100 years, the traditional internal combustion engine (ICE) powered by gasoline or

diesel was favored, disregarding alternative powertrain technologies as inefficient and undesired by

consumers (Financial Times, 07/2017). However, due to ever-increasing pressure on car

manufacturers, such as regulatory standards, to reduce vehicle emission, the market for alternative

fuel vehicles moved past the infant state. This might also be due to the government incentives

encouraging customers to buy electronic vehicles (EVs). Despite being a comparatively recent

market, some of the companies that commercialize electric cars have successfully formed their

business models to achieve profitability (IEA, 2019). Thus, the EVs industry has been rapidly

growing with the global stock of electric passenger cars passing 5 million in 2018, indicating an

increase of 63% from the previous year. Approximately 45% of electric cars on the road were in

China in 2018. In comparison, Europe accounted for 24% of the global fleet, while the United States

(U.S.) accounted for 22% (IEA, 2019). According to IEA 2019, global EVs sales reach 23 million

and the stock exceeds 130 million vehicles (excluding two/ three-wheelers) in the New Policies

Scenario (a scenario that includes both the policies and measures that governments around the world

have already put in place) in 2030. In the EV30@30 Scenario (a case scenario reflecting a policy case

characterized by a wider adoption of EVs), EVs sales and stock even nearly double by 2030 where

sales reach 43m and the stock accounts to more than 250 million. According to Strategy& (2019), by

2030 40% of new car registrations in Europe will be for electric vehicles. In the United States (U.S.)

and China the figure is expected to be 35% and 46% respectively.

The Electric Vehicle Segments

The EVs market consists of three segments, namely; the battery electric vehicles (BEVs), the hybrid

electric vehicle (HEVs) and the plug-in hybrid vehicle (PHEVs) (KPMG, 2020). In the following,


these three segments will be presented: BEVs: powered solely by battery packs that have to be

recharged from an external power source (e.g. all Tesla models), HEVs: powered by both a battery

pack and an ICE, and as the battery is charged with generative breaking it can only be refueled with

petroleum (e.g. Toyota Prius), PHEVs: powered by both a battery pack and an ICE, thus can be

refueled both with petroleum as well as external power source (e.g. BMW i8).

2.5.2 Global Automotive Outlook and Trends

According to the KPMG Global Automotive Executive Survey 2019 (KPMG GAES 2019), where

2,028 consumers where asked which powertrain technology they would consider purchasing in the

next five years, hybrids were the clear winner around the globe. This indicates that most consumers

have major concerns regarding the market viability of completely new disruptive technologies, such

as BVEs and fuel cell electric vehicles (FECVs; hydrogen car that effectively has its own efficient

power plant on board, the fuel cell and thus produces the electricity itself), which is further

strengthened by the fact that ICEs remain second best choice for consumers (Appendix 1). However,

when 981 senior executives from world’s leading automotive companies were asked about their

opinion on the global production volume share between ICE, PHEVs, BEVs and FECVs in 2020,

2030 and 2040, no certain powertrain technology dominates. Rather, global executives believe in a

fairly even split, meaning that multiple powertrain technologies will co-exist alongside each other

(Figure 5). It is forecasted that the global car production volume will rise from 98.53 million (m) in

2020 to 134.27m in 2040. Simultaneously, shares for BEVs (21% to 30%), PHEVs (21% to 25%)

and FCEV (18% to 23%) will show a significant increase, whereas ICE’s share will plummet from

40% to 23%. Lastly, alternative powertrain technologies are expected to dominate in 2040 in all three

critical markets for the automotive industry, namely; North America, Western Europe and China. In

particular, BEVs are expected to have the lead within the electric vehicle market by 2040. Thus, it is

no big surprise that giant car companies like Volkswagen, BMW and Daimler have pledged that 25%

of their fleets will be electric by 2025. These are some of Tesla’s competitors that do not need to

make money on their electric cars right away (Financial Times, 10/2019).


Figure 5: KPMG Global Automotive Executive Survey 2019

Source: KPMG Global Automotive Executive Survey 2019, p. 21

Further trends in the automotive industry are the following: Connectivity/in-car technologies (e.g.

custom digital dashboard, heads-up display devices projecting navigation info onto the windshield):

by 2030, sales of 5G enabled vehicles are expected to reach 16m in the European Union (EU), U.S.

and China (Strategy&, 2019). Automated: level 4 vehicles (fully automated driving, but still requiring

the presence of a driver) are expected to be operating in restricted areas at less than 50km/h by 2021

and by 2029 Level 5 vehicles (full automation, no driver). According to KMPG (2020), 19% and 46%

out of the 1154 executives expect fully self-driving cars to be operational in their market in 2025 and

2030, respectively. However, when only U.S. executives’ opinions are taken into consideration, 30%

and 40% expect fully self-driving to be operational in the U.S. by 2030 and 2040, respectively. In

addition, 77% of the executives believe that autonomous and non-autonomous vehicles will result in

severe safety issues if mixed on the road. On the other hand, executives from government authorities

have the most pessimistic view among stakeholders, with votes of only 30% for 2030 (remarkable

drop from 53% in 2019), 28% for 2040, and 20% for 2050 on the arrival for level 5 autonomy

(KPMG, 2020). Car/Ride Sharing: according to KPMG (2018), 43% of consumers believe that 50%

of the car owners they know today no longer want to own a personal vehicle by 2025, rather prefer

car sharing initiatives. Yet, the number of cars on the road will double from 2017 to 2 billion by 2040

– more will be electric, shared and autonomous – according to the Organization of the Petroleum

Exporting Countries (OPEC) (Financial Times, 07/2017).

Chapter 3: Strategic Analysis 20

3. Strategic Analysis

The purpose of this chapter is to conduct an external, an industry and an internal analysis. This will

help to better evaluate the macro-environmental factors affecting the automotive industry, the degree

of competitiveness in that industry and lastly, to assess Tesla’s resources and capabilities.

3.1 External Analysis – PESTEL

The PESTEL model is a tool for auditing the macro-environmental factor that have an impact on a

corporation’s business success. It provides a useful way to analyze the overall external environment

from different angles by focusing on six external environmental factors: Political (P), Economic (E),

Social (S), Technological (T), Environmental (E), and Legal (L). In addition, the PESTEL framework

is helpful for management as they determine the strategy of a business (Burt et. Al., 2006).

Historically, the automotive industry has been highly regulated, extremely vulnerable to economic

cycles, and greatly affected by social and normative schemes (KPMG, 2019). The PESTEL

framework will help to analyze and evaluate these characteristics. According to KPMG (2019), the

most crucial markets for the automotive industry in the coming years are U.S., China and Western

Europe. This is, as earlier identified, in alignment with the most important markets for Tesla. Thus,

the primary focus of the PESTEL analysis will be on these markets.

3.1.1 Political & Legal Factors

Throughout the last years, international conventions have increased the mandate for the Western

world to reduce global CO2 emissions and carbon footprint. This contributed to various government

incentives and regulations to lower CO2 emissions with the intention to promote the purchase of

electric vehicles. However, local governments are at different stages encouraging green technology

and preventing the purchase of the environmentally harmful ICE powertrain technology. According

to Lieven (2015), there are three ways a government can promote the adaptation of electric vehicles;

1.) monetary benefits, 2.) traffic regulations, and 3.) investments in the charging infrastructure.

Hence, the numerous government policies and programs address both the automotive industry’s

demand and supply side to either incentivize or to regulate and discipline the actual behavior. This

key identification by Lieven is also in alignment with the findings of IEA (2020), as fiscal incentives

at the vehicle purchase and complementary measures (e.g. road toll rebates, low-emission zones, etc.)

are pivotal to attract consumers and businesses to choose the electric option. In addition, as stated by


KPMG (2020), 81% of the leading executives in the automotive industry agree that the future

powertrain technology will be driven by regulation, particularly subsidy strategies and tax breaks will

be essential instruments. These incentivizing instruments make the KPMG Automotive Institute

believe that the automotive sector will experience a global relaunch in Q3 2020. In order to

successfully promote the sale of electric vehicles, governments are following variations of the

classifications identified by Lieven.

Monetary Benefits & Traffic Regulations

Monetary benefits can be both, supplier as well as customer-oriented. An example of an incentive

program on the supply side would be the U.S. Department of Energy (U.S. DoE) making $25bn

available for grants and loans promoting fuel efficiency or technical advances within electric vehicles.

Lieven (2015) considers this a highly efficient way of promoting electric vehicles, as it reduces entry

barriers for new actors in the industry and improves market competitiveness. This incentive program

is worth mentioning since Tesla itself made use of this program by getting approval for a $465m loan

in 2010. This loan was primarily used for an assembly plant for Model S and another facility to

manufacture electric powertrains (Tesla, 04/2010). A more recent example for the supply side

incentive program would be the case of Germany. Part of the Germany’s most recent economic

stimulus program stipulates to support vehicle manufacturer by €1bn in 2021 and 2022 respectively

for the purpose of investing in alternative powertrain technologies.

On the other hand, local governments introduce customer-oriented incentive programs, such as

exempting EVs from purchase and road taxes, too. Complementary measures such as reduced ferry

or (no) parking fees are an important part of this program. Further, non-financial incentives like

authorizing electric vehicles to access bus or carpool lane are an effective short-term initiative

(Lieven, 2015). Banning polluting vehicles from some urban areas for instance is an additional traffic

regulation that is widely used in Germany (Independent, 02/2018). Concrete monetary benefits (Table

2) and traffic regulations (Table 3) applying to Tesla’s main markets can be found in the following

tables below.

The implementation of incentive programs in the form of monetary benefits and traffic regulations is

of significant importance when it comes to boost the sales of electric vehicles, which can be illustrated

by the Danish case. In 2016, the subsidies for electric vehicles phased out in Denmark and this

resulted in a decline of 60% in EVs sales (Levring, 06/2017).


Table 2: Government financial incentives for electric vehicles in Tesla’s main markets

Financial incentives

U.S

:

Max. $7,500 Federal tax credit; only available for the first 200,000 vehicles sold from each

manufacturer (Since 01/2020 Tesla cars no longer eligible for this incentive)

Various purchase rebates for EVs and other incentives dependent on the state, e.g. reduced

registration fees, exemption from state emission testing

Ch

ina EVs are exempt from 10% sales tax through the end of 2022

Subsidies up to RMB25,000 ($3,500) will apply to passenger cars costing less than

RMB300,000 ($42,480)

Net

her

lan

ds

Until 2025: Subsidy of €4,000 for EVs with list price between €12,000-€45,000 & min. range

of 120 km; €2,000 for used EVs

EVs are exempt from purchase & ownership tax, company car tax of 4%

Investments in clean technologies are partially deductible from corporate and income tax

Norw

ay

No annual road tax

Max. 50% of the total amount on ferry fares

Parking fee with an upper limit of a maximum 50% of the full price

Company car tax reduction reduced to 40%

No purchase/ import taxes

Exemption from 25% VAT on purchase

Sources: compiled by author / CleanTechnic / electrive / wallbox / Tesla / FutureCar / AutoNews / China briefing

Table 3: Government non-financial incentives for electric vehicles in Tesla’s main markets

Non-Financial incentives

U.S. Carpool lane access

Free municipal parking

China Free municipal parking (dependent on the city/region)

Netherlands

Upon request, the city will install a charging station on your street; city will bear

the installations cost but you still have to pay for charging

From 2030, only emissions-free vehicles will be allowed to be newly registered

Norway Access to bus lanes

Sources: compiled by author / CleanTechnic / electrive / wallbox / Tesla / FutureCar / AutoNews / China Briefing

Charging Infrastructure

According to Lieven (2015), the lack of range and the deficient charging infrastructure are the two

key reasons for a relatively low penetration rate of EVs. However, today there have been big

advancements regarding the ranges of EVs – will be touched upon in later stage of the thesis – as well

as massive deployments of charging stations in the key automotive markets. For instance, China had


516,000 public charging stations at the end of 2019, a remarkable development coming from less than

58,000 stations in 2015 (Statista, 01/2020). While governments’ investments and programs with

regards to the charging infrastructure are increasing by time, a well-established charging

infrastructure is also dependent on the cooperation of car manufacturers (IEA, 2020). Due to this

reason, Tesla launched its own so-called Tesla Supercharger. Today, Tesla has 1,971 Supercharger

stations with 17, 467 Superchargers globally – Asia, North America and Europe & Middle East

(Tesla, 2020).

3.1.2 Economic Factors

Being highly exposed to the economic environment and the boom and bust cycles of the economy,

the automotive industry can be stamped as a cyclical one. Further, Figure 6 illustrates this relationship

very well since the world vehicle sales seem to follow the world GDP growth pattern.

Figure 6: World vehicle sales growth in % vs. World GDP growth in % for 2016-2019

Sources: compiled by author / OECD and OICA 2006-2019

Historically, the automotive industry has always been hit by a recession in the economy, e.g. 2008-

2009, since consumers respond by postponing their decision to buy a new car (KPMG, 2019). The

consequences of the financial crisis in 2008-2009 demonstrates this pattern very well, as the following

U.S. recession crashed the local automotive industry due to a major downturn in the purchasing power

of consumers. The government bailout of the two established U.S. car manufacturers, General Motors

and Ford, in 2009 was one of the repercussions of that financial crisis (Forbes, 01/2016). It remains


to be seen how serious the expected Covid-19 economic recession will affect the U.S. automotive

industry. On the other hand, China was not hit as much as the U.S. and became the leading market

for automakers in 2009, a position it has continued to defend until today (KPMG, 2019).

Despite the recent economic slow-down due to the Covid-19, the outlook for the global GDP is

optimistic; OECD (2020) forecasts the real GDP long-term to be relatively stable at 2.3%-2.8%. In

the Figure 7 below, the GDP development forecasts until 2025 are shown. It can be seen that China

shows the highest GDP growth rates of 4%-5.5% while the U.S. and Europe tend to have a more

constant growth rate of ≈2% and ≈1%, respectively. China does not only seem to remain a strong

economy but is also expected to leapfrog the market with its electric vehicles, making the Asian

country the future e-mobility market (OECD, 2020 & KPMG, 2019).

Figure 7: GPD development forecast for China, Europe and the U.S:

Source: compiled by author / OECD

Commodity Prices

As elaborated above, the world GDP is a strong and reliable indicator for the future performance of

the automotive industry. At the same time, the profitability of car manufacturers is further the prices

of various commodities such as oil, lithium, steel, aluminum and nickel (KPMG, 2019). The prices

of aluminum and steel, which Tesla uses to build the bodywork of its cars, do not represent a major

risk as the prices of both metals have been relatively stable over the last few years and are expected

to stay at that level. Yet, the commodities used for components in the batteries, lithium and nickel,

may pose a significant exposure for electric vehicle manufacturers, such as Tesla. However, while

lithium prices have been falling since 01/2018 and expected to stay at the same level for the next two


years (Trading Economics, 2020), nickel prices show a high degree of volatility and are expected to

increase over time from currently $11,617 per metric ton (mt) to $15,182 per mt in 2030 (World

Bank, 2020). Hence, any disruption or shortages in the supply of these crucial commodities as well

as increase in costs, could harm Tesla’s business (Annual Report p. 20, 2019). Lastly, 73% of the

leading automotive executives agree that a country’s access to mineral resource will dictate the

country’s preferred powertrain technology (KPMG, 2020).

3.1.3 Social and Environmental Factors

In the automotive industry, prescriptive and cultural institutions play a critical role. It is important to

consider the social dimension when analyzing the current environment and the implications of the

social trends for future car models. There are many societal patterns on the market, including the

public conception of the ICE and EVs, customer expectations from the car of the future, and the

customer’s general attitude towards car ownership (KPMG, 2019).

Despite an increasing awareness towards the harmful effects of polluting powertrain technologies,

leading global automotive executives believe that multiple drivetrain technologies, such as BEVs

(30%), Hybrids (25%), FCEVs (23%) and ICEs (23%), will co-exist by 2040 (KPMG, 2019). Thus,

the traditional ICE technology, will still have an essential market share. This might be due to

customer-concerns about the range and capabilities of alternative powertrain technologies.

Since the future car is awaited to be fully autonomous, the perception and usage of the car is going to

be extremely different. This expectation and trend in the automotive industry made the past

purchasing criteria, e.g. ECO, comfort and sport, irrelevant. These criteria will be replaced by how

much space the car offers to relax during the ride, how much space it offers to work and lastly, the

offer of entertainment systems (KPMG, 2017). Due to the more and more software-like becoming

future cars, KPMG (2019) states that data privacy and security remain the number one purchasing

criteria. Additionally, transparency of total cost of ownership is catching up which actually

exemplifies the changed consumer behavior towards car ownership. According to KPMG (2018),

43% of consumers believe that 50% of the car owners they know today no longer want to own a

personal vehicle by 2025, rather prefer car sharing initiatives.

3.1.4 Technological Factors

Technological advancements are fundamentally related to electric vehicles and the automotive

industry. Over the last few years, the sector has achieved major technological improvements. Still,

according to KPMG (2019), the main reasons for consumers to stay away from an electric vehicle are


price (35%), charging experience (24%), and range concerns (18%). Hence, decreasing the overall

cost of an electric vehicle and improving the range-performance are pivotal factors to increase an

electric vehicle’s acceptance. Apparently, consumers are primarily focusing on the purchasing price

of a car but disregard the total cost of ownership advantage an EVs offers, thanks to the currently

cheaper variable costs (KPMG, 2019). Further, according to a Bloomberg report (04/2017), 2025 is

looking to be the earliest year of price parity between ICEs and BEVs. A more recent article on Forbes

(06/2019), indicates this case to occur by or shortly before 2025. Additionally, the share of the battery

in the price of a mass manufactured BEVs in 2016 is expected to show a substantial decline from

48%-55% in 2016 to 18%-23% by 2030, illustrated in Figure 8. To put that into numbers, the cost of

a lithium battery cell is expected decrease from $200 per kWh in 2018 to $100 per kWh in 2023.

From 2018 to 2019 alone, the battery costs fell by 13% (Green Car Report, 12/2019). A substantial

reduction in battery costs would make the purchasing price of EVs competitive with respect to the

conventional ICE powertrain technology. Moreover, a decline in the purchasing prices of EVs can

only be achieved when significant economies of scale and scope are reached (Business Insider,

09/2017).

Figure 8: Expected share of battery prices from 2016 to 2030

Source: Bloomberg New Energy Finance 04/2017

Worth mentioning is also, that the range performance of electric vehicles has been improved over the

last couple of years. For instance, a Tesla Model S had an initial range of 265 mi when first launched

in 2012 and now has a range of 390 mi, an increase of 125 mi over eight years. Another example

would be the Nissan LEAF, having an initial range of 84 mi in 2011 and now improved by 141 mi,

making 225 mi on a single charge (CleanTechnica, 10/2018 & Tesla Statista, 2020). Not only the

range but also a well-established charging infrastructure is necessary to consider the electric


powertrain technologies a sustainable one, which needs serious investments. In addition, the charging

time is pivotal, as this process should not take hours, which would only make the anxious customers

avoid purchasing an electric vehicle (KPMG, 2019).

3.1.5 Conclusion of the External Analysis

The growth of the automotive industry and the adaptation of electric vehicles depend on various

external factors. The most crucial one however is a strong economic growth as, historically, there is

a strong correlation between the world GDP growth and world vehicle sales numbers. Tesla’s main

markets – U.S., China and (Western) Europe – are all expecting a GDP growth in the upcoming years.

While China is expected to have the highest GDP growth with 4%-5.5%, the U.S. and European

market shows a steady GDP growth rate of ≈2% and ≈1% for the upcoming years. Further,

governments have to attract suppliers and customers with financial and non-financial incentives.

Especially during this Covid-19 economic slowdown, 81% of the leading executives in the

automotive industry agree that the future powertrain technology will be driven by regulation,

particularly subsidy strategies and tax breaks will be essential instruments. These incentivizing

instruments make the KPMG Automotive Institute believe that the automotive sector will experience

a global relaunch in Q3 2020 (KPMG, 2020). To illustrate the effect of such incentives, Denmark

noted a 60% decline a year after its subsidies for EVs phased out (Levring, 06/2017). In addition,

fluctuations of commodity prices may affect the overall electric vehicles purchasing prices, especially

commodities used for the batteries. Speaking of batteries, range concerns and an insufficient charging

infrastructure are key reasons for why customers still prefer ICE to EVs. Moreover, the perception of

a car is changing with technological advancements such as autonomous driving, as customers are

now looking for a different driving experience: relax & socialize, work & concentrate and enjoy

entertainment systems while driving (KPMG, 2017). Lastly, consumer behavior towards car

ownership has changed as to KPMG (2018), 43% of consumers believe that 50% of the car owners

they know today no longer want to own a personal vehicle by 2025, rather prefer car sharing

initiatives.


3.2 Industry Analysis – Porter’s Five Forces

Porter’s Five Forces is an effective method to analyze the industry attractiveness while the

attractiveness is identified by the competitive

landscape. The competition depends on five

forces, namely threat of new entrants, threat

of substitute products or services, bargaining

power of suppliers, bargaining power of

customers and the intensity of existing

competitive rivalry, as illustrated in the

Figure 9. Hence, the mutual strength of these

forces determines the ultimate profit

potential of an industry. Thus, the weaker the

forces collectively, the greater the chances of

superior returns (Harvard Business Review,

03/1979). Since Tesla is competing in the

automotive industry, including all powertrain

technologies, this analysis pursues to deliver an understanding of the competitive environment within

that specific industry.

3.2.1 Threat of New Entrants

If a specific industry promises high returns, more companies will seek to enter that industry in the

hope of taking root in the market and gain a certain market share. In doing so successfully, this would

necessarily affect the existing companies’ market share in a negative way. Hence, in order to

determine the threat of new entrants, it is pivotal to analyze various factors affecting the ability to

enter that specific market, known as the barriers to entry. While doing so, special attention should be

given to the distinction of the traditional ICE automotive industry and the growing electric vehicle

market.

High capital requirements – raw materials, workforce and production plants –, lack of distribution

channels, and the natural complexity of the car have traditionally characterized the automotive

industry, leading to extremely challenging barriers to entry for new market entrants. Looking at the

CAPEX/Sales ratio, VW and BMW have quite stable ratios of ≈5% and ≈7% over the last three fiscal

years (MarketScreener, 2020) while Tesla had a CAPEX/Sales ratio of 40% in 2017, 12% in 2018

Figure 9: Porter’s Five Forces

Source: Harvard Business Review, 03/1979


and 7% in 2019 (Appendix 2). Tesla seems to have established itself in the automotive industry as it

shows a comparable CAPEX/Sales ratio with two traditionally well-established German car

manufacturers. However, Tesla (368,000 vehicles) is far away from reaching annual sales volumes

like VW (11m vehicles) or BMW (2.5m vehicles). In order to increase its sales volumes, Tesla has to

build more production plants and this again will require significantly high expenditures. Nevertheless,

leading automotive executives state that Tesla, which strengthened its second-place ranking this year

(KPMG, 2020), challenges BMW’s e-mobility leading position. The economies of scale and scope

have played a major role in the automotive industry, following Henry Ford’s innovative production

process, and the potential to reach economies of scale have traditionally stopped new entrants

(Harvard Business Review, 08/2011). Thus, the threat of new entrants has been very low in the

automotive industry.

Focusing solely on the electric vehicle market, the threat of “new” entrants is considerably higher as

many big players in this industry like Volkswagen, BMW and Daimler have pledged that 25% of

their fleets will be electric by 2025. These are some of Tesla’s competitors that do not need to make

money on their electric cars right away (Financial Times, 10/2019) and already have the required

capital and economies of scale to rough up the EVs market. However, the threat does not only arise

from traditional car manufacturers but from disruptive technologies in general, as these advancements

could change the landscape car manufacturers used to compete in. While the ICE powertrain

technology corresponds to 22% of the direct cost of vehicle today, the powertrain types for various

EVs amount 32%-55% of the direct cost of vehicle. What this means is that the function of traditional

car manufacturers could be reduced to a supplier-role, solely manufacturing the bodywork of the car,

if other players in the industry have a competitive advantage in building batteries (McKinsey,

11/2019). Another disruptive element would be the autonomous driving and the related importance

of data security. Today, many car manufacturers work on the software for autonomous driving but so

does Waymo, the Alphabet self-driving unit that initially began as a Google project (Financial Times,

01/2019). Even though Tesla seems to be ahead – will be touched upon later in the internal analysis

section – when it comes to driven autopilot miles, Waymo’s intention is not to produce cars but rather

license this software (Waymo, 2020). This could help already well-established industry giants who

slept on this technology to license the software and catch up with competitors such as Tesla within

no time.


Thus, historically the threat of new entrants has been low. However, focusing purely on the electric

vehicle market, this assessment changes as traditional industry giants are changing their portfolios

gradually towards alternative powertrain technologies.

3.2.2 Threat of Substitute Products

In the short-term, the primary threat for electric vehicles is the widespread ICE powertrain technology

as the demand for electric vehicles highly depend on governmental subsidy strategies and tax breaks

(KPMG, 2020). In addition, 2025 is considered the earliest year of price parity between ICEs and

BEVs (Bloomberg, 04/2017). Seen in a longer-term perspective, FCEVs (hydrogen car that

effectively has its own efficient power plant on board, the fuel cell and thus produces the electricity

itself) could be a serious substitute to BEVs as this drivetrain technology is not confronted with

limitations of EVs such as range and charging time (KPMG, 2019).

A very well-known substitute product for cars in general is public transportation as it solves many

problems related to the ICE powertrain technology, for instance traffic congestions, pollution and

price (Lieven, 2015). Electric vehicles are able to work out the above-mentioned issues as well, yet

the price is still above the level of a traditional car. A more serious threat is the widespread car sharing

companies such as Uber, Share Now, Lyft, Grab. According to a Frost & Sullivan report (08/2016),

there will be 35,000,000m car sharing users 2025 worldwide, coming from 10,000,000 users in 2017,

maintaining the annual growth rate of 16.4%. McKinsey (2020) states that the shared mobility market

currently exceeds $60bn in value across the three largest markets, namely U.S., China and Europe.

Besides, the future is expected to bring even greater gains with the launch of self-driving taxis and

shuttles towards the end of this decade. Through 2030, McKinsey forecasts the annual growth rate

for shared mobility to exceed 20%. Further, car sharing could make up 26% of global miles traveled

(IBM, 2019). Lastly, as previously mentioned, 43% of consumers believe that 50% of the car owners

they know today no longer want to own a personal vehicle by 2025, rather prefer car sharing

initiatives (KPMG, 2018).

Hence, currently the threat of substitute products seems to be moderate but is expected to increase

significantly, especially with the introduction of self-driving taxis at the end of this decade.

3.2.3 Bargaining Power of Suppliers

According to PWC (2019), automotive supplier transactions continue to surge indicating a

consolidation among the suppliers. Car manufacturers are outsourcing non-key activities with the


intention of focusing solely on core competencies and remaining cost competitive (Gunasekaran et

al., 2008). This is further supported by Ernst & Young (EY) (2016), stating that in 2015 suppliers’

proportion of value added in the automotive industry amounted to 82%, coming from 56% in 1985

and 69% in 2000. A further remarkable advantage of outsourcing is that by outsourcing only 10%-

15% of the long-term R&D budget, 10%-50% savings can be achieved (EY, 2019). According to

PWC (2019), autonomous vehicle (AV) technology and full vehicle electrification represent the two

dominant future technologies affecting vehicle suppliers. However, companies that do not produce

systems or components directly linked to EVs or AV production may find their markets due to

disruptive technologies in the automotive industry. Some firms are making investments now that are

meant to help them stay competitive in a future where AVs and EVs dominate, although it may take

years before they actually pay off. Others might expect technology to evolve, and consumer demand

to shift before they act (PWC, 2019).

Tesla is sourcing 2,000 parts from 300 different suppliers for the Model S, showing how dependent

Tesla is from its suppliers (Tesla Annual Report, 2013). This is further supported by the Model 3

delay for which Elon Musk blamed the suppliers (SupplyChainDive, 08/2017). Lastly, Tesla itself

states in its most recent annual report (p. 84, 2019) that there is a high supply risk as Tesla is dependent

on their suppliers, the majority being single source suppliers. Lastly, Tesla just recently secured a

deal to purchase 12m pounds of cobalt annually from a Swiss-based company, Glencore, recognized

as the world’s miner of the metal. This partnership is expected to extremely alleviate any supply

shortage concern for the Gigafactory Shanghai and Berlin, especially since more automakers aim to

break into the EVs market in the future.

Hence, the trend of increasing outsourcing activities and consolidation among suppliers indicate a

growing bargaining power of suppliers, especially for car manufacturers that sleep on disruptive

technologies. Speaking of Tesla, it seems to be highly dependent on its suppliers.

3.2.4 Bargaining Power of Customers

The bargaining power of customers depends on the distribution network the car manufacturer uses.

While other car manufacturers use the traditional franchised dealership model, Tesla sells its cars

through a network of company-owned stores (Tesla, Annual Report 2019). This means that customers

of other car manufacturers have a higher bargaining power, as the dealerships purchase high number

of vehicles, leading to economies of scale. In contrast to this, Tesla’s customers are individuals and

not dealerships. Hence, Tesla has an advantage with its distribution model, as this does not let space


for big discounts. On the other hand, individuals are extremely price sensitive and Tesla has to

consider this fact in their business model, especially since Tesla is not any longer targeting the high

premium segment. With the launches of the Model 3 & Y (2017 & 2020), Tesla is becoming a volume

manufacturer and targeting the mass market that is larger in size but also extremely price sensitive.

Further, with the increasing EVs product portfolio of traditional car companies, customers will have

low switching costs. This trend effectively increases the individual’s bargaining power, underlining

the value of cost-competitiveness. A recent example would be that in order to qualify for

governmental subsidies, Tesla had to reduce the price of standard range Model 3 in China

(TechCrunch, 04/2020). This played into Chinese customers’ hands.

In addition, through the increasing threat of substitute products such as the car sharing option or the

self-driving taxis in future, the bargaining power of customers may increase over time. BMW and

Daimler are attempting to alleviate this problem with their car sharing company Share Now, a joint

venture of the both industry giants (Share Now, 2020). Tesla is planning on launching a “robotaxi”

network – which will be elaborated later on – to expand its business model (electrek, 02/2020).

Thus, the bargaining power of customers is expected to increase as Tesla entered the mass market

and the threat of substitute products is increasing due to technological advancements.

3.2.5 The Intensity of Existing Competitive Rivalry

High competition and high barriers to exit have traditionally characterized the automotive industry,

creating saturation on the market and a highly competitive environment. With the launch of the Tesla

Roadster in 2008 and the Model S in 2012, Tesla created a so far neglected sub-market within the

automotive industry, the electric vehicle market. At present, the competition in this market can be

identified as low to moderate – from which Tesla has benefited – compared to the ICE market but is

expected to become fierce the moment other traditionally well-established car manufacturers

introduce/expand their EVs fleet. For instance, VW, BMW and Daimler have pledged that 25% of

their fleets will be electric by 2025 and these are only some of Tesla’s competitors that do not need

to make money on their electric cars right away (Financial Times, 10/2019). The different level of

competition might stem from the different stages of the product lifecycle. For one thing, the ICE

market is currently maturing with lower growth, rising suppliers and customers bargaining power,

and lower switching costs leading to lower margins and a less attractive environment. Further, the

fierce competition among ICE car manufacturers in connection with the regulatory financial and non-

financial incentives for EVs animated them to seek profits and revenues elsewhere. On the other hand,


based on my assessment, the EVs market is in its final introduction or in a very early stage of its

growth phase as many other car manufacturers are breaking into the EVs segment gradually. A switch

to the emerging EVs segment comes with high R&D costs and investments in adjusting production

facilities. However, traditional car manufacturers do not face the same steps Tesla had to take, such

as investing in production capabilities and distribution channels. Hence, the well-established key

players in the automotive industry, once entering the EVs segment, might be able to quickly catch up

with Tesla.

Thus, the intensity of existing competitive rivalry across the ICE segment is intense and in the electric

vehicle market low to moderate. However, this is expected to become fierce once big players

introduce or expand their EVs fleet.

3.2.6 Future Success Criteria for the Automotive Industry

Analyzing the automotive industry attractiveness has revealed some major findings. Technological

advancements disrupt the industry while governmental regulations oblige traditional car

manufacturers to enter the alternative powertrain technology market. Due to a lack of competition in

the EVs segment, Tesla dominated this segment. However, Tesla might find itself in a fierce

competitive landscape once other car manufacturers start introducing and expanding their EVs

product portfolio. Then the questions get, whether Tesla is sufficiently ahead of its competitors to

protect its leading position, whether it can leave its rivals in the dust or might they quickly catch up?

In order profoundly answer this question; it is crucial to get an understanding of the megatrends in

the automotive industry, requirements for future cars, and the internal capabilities of Tesla.

Based on the analyses carried out so far and the megatrends identified by KPMG and Strategy&, the

future performance in the automotive industry will be driven by the following criteria:

Capabilities in production and distribution, and the ability to reach scale and scope

Battery performance of electric vehicles

Convenient access to a fast and widespread charging infrastructure

Operational flexibility to mitigate booms and busts (local or regional)

Capability to (quickly and successfully) respond to disruptive technologies

Changed perception of the car – understanding the customer

Defining & adapting the future business model


3.3 Internal Analysis – Value Chain Analysis & VRIN

In alignment with the above-mentioned future success-criteria within the automotive industry, key

internal resources and capabilities across the value chain for Tesla will be analyzed to seize the

identified market opportunities. Each step will be assessed using the VRIN, a resource-based

framework to identify potential sustainable competitive advantage. According to Barney (1991),

sustained competitive advantage can only be achieved if a resource is valuable, rare, imperfectly

imitable, and non-substitutable.

Figure 10: Value Chain Analysis of Tesla

Source: compiled by author

3.3.1 Production Capabilities

The primary difference between Tesla and well-established industry players like VW and BMW is

that Tesla has not been able to produce cars in large volumes and cost-effectively. However, this is

supposed to change with the announced ramp-ups of the installed annual production capacity in

Fremont and Shanghai (Tesla, Q1 2020 & Reuters, 03/2020) and the Gigafactory Berlin that is

expected to have a production capacity of 500,000 annually once fully completed (Tesla, 2020).

Considering the most recent announcements and expert assessments for upcoming models, following

production capabilities in Table 4 can be concluded, which will also set the basis for the sales forecast

later on:

Production Product Charging infrastructure Distribution network CEO & Brand Consumer


Table 4: Forecast of Tesla’s international annual production capacities

Location Model Installed/forecasted annual

capacity Comment

Fremont

Model S & X 90,000 No further ramp-up

announced

Model 3 & Y 400,000

(will extend to 500,000 in 2020)

No further ramp-up

announced

Shanghai Model 3 & Y 200,000 250,000 as from 2022

Berlin

Model Y 500,000

Late 2021, due to

Covid-19 2022 seems

more realistic

Model 3 – No announcement has

been made

United States

Tesla Semi 25,000 in 2021 Will gradually increase

up to 100,000 in 4 years

Roadster 1,000 in 2022 (Founder’s Series) Will gradually increase

to 4,000

Cybertruck 300,000 in 2022 Will gradually increase

to 500,000


According to the table above, Tesla should be able to produce 1,691,000 vehicles and more as from

2022. Tesla produced 365,000 vehicles in 2019 and delivered 368,000 vehicles. This would almost

represent an increase by a factor of five, from 2019 to 2022. However, if Tesla wants to sustain in the

automotive industry, it has to start delivering more vehicles. With the launches of Model 3 & Y, a

more affordable Tesla car, Tesla aims to become a volume manufacturer. Still, there is a long way to

go when comparing Tesla with VW and BMW, which delivered 11m and 2.5m vehicles in 2019,

respectively.

While the vertically integrated supply chain does have it pluses (e.g. technological capabilities, etc.)

and minuses (e.g. reduced flexibility, capital requirements) (Harvard Business Review, 01/1983),

Tesla had to deal a lot with its shortcomings regarding the battery production. Due to a bottleneck in

the production of Model 3 in Q1 2018, Tesla had serious problems putting cars on the road (CNBC,

04/2018). According to electrek, the Gigafactory Nevada produced more than 600m lithium-ion

battery cells, totaling to 11GWh of energy. This sum of energy should be sufficient to more cars than

produced, meaning that regular production is probably running below current capacity. It seems to

look like that battery cell production does not appear to bottleneck Tesla models (electrek, 01/2019).

As in previous analyses mentioned, reducing battery production costs is an essential success factor,


not only for Tesla but also for the whole EVs segment. According to Forbes (01/2020), Tesla has

managed to reduce the battery costs from $230 per kWh in 2016 to $127 per kWh in 2019. While the

costs are expected to decline to $114 per kWh in 2020 for Tesla, the industry average (Bloomberg,

03/2019) price per kWh is expected to be $143 in 2020, as illustrated in Figure 11. This represents a

price level per kWh that Tesla achieved in 2018. Hence, it can be concluded that Tesla is two years

ahead of the industry average concerning the battery costs. Assuming that the average Tesla car has

a 70kWh battery installed, this would imply a decline of the battery cost per vehicle from $16,000 in

2016 to approximately $8,000 in 2020.

Figure 11: Tesla Battery Costs vs. Industry Average Battery Cost ($ per kWh)

Source: Forbes, 01/2020

Tesla has to scale up its production rate, as sustaining in the highly competitive automotive industry

requires a higher delivery number. For this purpose, Tesla has to think about expanding or building

new production plants in the already established or new geographical segments to also increase its

global footprint. When it comes to efficiently producing batteries, Tesla is two years ahead of the

industry average and continues to reduce the battery costs per kWh. Being able to do so is crucial as

the battery costs are considered a key cost driver for electric vehicles, especially in order to make

EVs cost-competitive with the ICE drivetrain technology. According to KPMG (2019), 35% of the

consumers said that the price of EVs is the reason why they stay away from purchasing one. Hence,

a general price reduction of EVs would make this alternative powertrain technology more attractive.

3.3.2 Product Capabilities

When purchasing an electric vehicle, one of customers’ main concern is range anxiety. Additionally,

as autonomous driving will establish itself in the future, looking at how far Tesla is with the full self-

driving (FSD) project.


Battery Performance

KPMG (2019) states that 18% of the consumers have range concerns, leading them to ignore the

electric alternative. As illustrated below in Figure 12, currently Tesla models are leading the ranking

with respect to the range.

Figure 12: Ranking of different EVs with respect to range in miles

Source: Statista, Tesla Report 2020

While Model S & X Long Range Plus AWD ($74,990 & $79,990 w/o incentives) have the highest

ranges, comparing these high-premium electric vehicles with a Mustang Mach-E ($43,895 w/o

incentives) would be misleading. However, even the Model 3 & Y ($46,990 and $52,990 w/o

incentives), that are considered a more affordable product and more comparable to the other listed

electric vehicles, have a higher range. The question is whether this can indicate a sustained

competitive advantage as other big players are starting to enter the EVs segment. However, to assess

the current state, Pierre Ferragu (Tesla expert, commonly seen on Bloomberg & CNBC podcasts)

thinks that no competitor comes close to Tesla range-wise (CleanTechnica, 10/2019). This is further

supported by Houchois (Jefferies MD, industry expert), stating that against expectations the gap

between Tesla and its peers is widening, from product to battery and technological capacities

(Seeking Alpha, 06/2020). On the other hand, considering industry giants breaking into the EVs

segment, they will most likely be able to shorten the gap to Tesla. This would be consistent with

Barney’s (1991) theory, as a technology itself cannot lead to a sustained competitive advantage since

peers will be able to replicate or substitute it. Thus, Tesla has to continue exceeding market

expectations to keep or even widen the gap.

Full Self-Driving Project


Autonomous driving is one of the megatrends in the automotive industry and Tesla’s approach is

different from its peers. While Tesla’s peers mostly use high-definition (HD) maps or a laser-based

system for their autonomous driving project, Tesla uses ultrasonic sensors which are built on cars and

can be unlocked by paying for the software (Tesla Autopilot, 2020). Further, Tesla is approaching a

remarkable 2bn self-driving miles driven coming from 0.1bn miles in 2016. Comparing this to its

peers, Waymo and GM drove only 1.3m and 447,000 miles, respectively (Forbes, 11/2019).

Currently, Tesla cars are not fully autonomous, as the enabled features (Tesla, 2020) require active

driver supervision (Tesla Autopilot, 2020). Additionally, once the software is fully market-ready, it

still has to gain the approval of regulators. Further, based on the KPMG (2020) findings, 77% of the

industry executives think that autonomous and non-autonomous vehicles will lead to severe safety

issues if mixed on the roads. Hence, either Tesla has to wait for its peers’ autonomous readiness as

well or regulators have to create an “island of autonomy” that can be accessed solely by autonomous

vehicles (KPMG, 2020).

Tesla seems to have a competitive advantage about both the battery range as well as the FSD.

However, it is questionable whether these advantages can be labeled as sustained competitive

advantages due to the emerging threat of competitors.

3.3.3 Charging Infrastructure

According to KPMG (2019), 24% of the consumers stated that the insufficient charging infrastructure

is a significant entry barrier into the electric world. Due to the lack of supporting programs, especially

in early stages, Tesla started to build its own charging network, the so-called Tesla Supercharger. At

present, Tesla has 1,971 Supercharger stations with 17,467 Superchargers in total in North America,

Asia and Europe & Middle East (Tesla Supercharger, 2020). According to a Morgan Stanley industry

expert, this venture paid off as the charging infrastructure played a key role to make electric vehicles

a viable alternative to the traditional ICE vehicles. Jonas further estimates the charging network to

consist of 15,000 stations by 2030 (CNBC, 02/2019). Especially the launches of Model 3 & Y further

underlines the significance of the Supercharger stations as these models are intended to be mass

products. On the other hand, BMW collaborated with local operators and created a joint venture with

Charge Now and Daimler. This network has now more than 100,000 charging points worldwide

(AvairX, 2020).

Besides having a geographically widespread charging infrastructure, the charging time is pivotal.

Technically, Tesla Superchargers are able to charge with 150 kW but Tesla restricted this to 120 kW.


It takes only 30 minutes to reach an 80% charge, and about 80 minutes to a 100% charge for a Tesla

(Tesla Supercharger, 2020) whereas a BMW i3 would need 3h to be fully charged. Further, even

compared to other peers, Tesla has the quickest charging time – apart from the Smart EQ (Mobility

House, 2020).

A well-established charging infrastructure and the charging time are key factors for consumers to

consider when thinking of buying an electric vehicle. Tesla has a sustained competitive advantage

regarding the charging time but has to invest more to expand its Supercharger network, especially

since the Model 3 & Y launches.

3.3.4 Distribution Network

The capability of distributing and selling in the most efficient and profitable way has been and still is

a fundamental challenge for car manufacturers. The traditional way of distributing its cars is the way

through dealerships, as done by e.g. BMW, VW, that mostly rely on sales as well as revenues from

repair work and maintenance. However, Tesla took the vertical integration approach and now has 434

fully company owned store and service locations globally (Tesla, Q1 2020). Introducing this new

distribution channel, Tesla again disrupted a whole industry. Having in mind that EVs only have 20

moving parts, whereas ICE cars have over 2000, this distribution model seems to be cost-efficient

thanks to less maintenance requirements of EVs (Forbes, 09/2018). One might argue, that Tesla has

to increase its physical footprint by opening more stores but the trend looks like that cars will be

purchase online in the future. According to KPMG (2020), 80% of the consumers would be ready to

purchase a car online. One could argue that especially for Tesla consumers, who tend to have an

innovative mind-set, this could be a further welcomed changed.

3.3.5 CEO & Brand: Defining the Future Business Model

Tesla’s CEO, Elon Musk, is a very well-known Silicon Valley serial entrepreneur. He has history full

with successful start-ups, like X.com and PayPal. He has a polarizing personality and is known to

disrupt certain industries with his projects, such as to make space tourism commercial with SpaceX

or to accelerate the world’s transition to sustainable energy (Tesla, About Tesla 2020) and while

building an affordable car for everyone, providing zero emission electric power generation options

with Tesla (Tesla, 2006). This new disruptive business model is contrary to the one of the already

established players that are blamed for polluting the environment and disregarding alternative

powertrain technologies. Thus, Tesla is considered the second leading e-mobility leader, directly

behind BMW (KPMG, 2020). Tesla heavily relies on its visionary, polarizing and popular CEO,


word-of-mouth propaganda and supportive media as Tesla’s advertising budget, in contrast to its

peers, equals zero. Elon Musk’s polarizing personality and disruptive announcements for upcoming

models and projects lead to high media attention and coverage (Growfusely, 2019).

For Tesla, being considered a highly innovative and disruptive company is beneficial when defining

its future business model. According to KPMG (2019), Tesla is together with BMW 2nd with the

highest prospects for success in the new ecosystem value, after Toyota being the undisputed leader.

Further it divides the future industry in three categories; 1.) Hardware oriented asset-based players,

2.) Hardware & software-oriented asset-based players enriched with software features and

functionalities, 3.) Software-oriented players providing a release-free daily integration. Tesla would

surely belong to the second as the first category will supply the rest of the industry as contract

manufacturer (KPMG, 2019). Tesla does not seem to reach scale and scope benefits anytime soon.

Additionally, in future profits will be determined by access to data explaining why data privacy and

security remain the number one purchasing criteria (KPMG, 2019 & 2020).

3.3.6 Customer Understanding – Changed Perception of the Car

According to KPMG (2020), future profits will be determined by miles traveled and not units sold,

particularly if car ownership in certain applications, e.g. cities, is basically decreasing. Hence, the

ecosystem requires car manufacturers to be transformation ready. An industry giant like BMW

already established its car sharing network called Share Now – started as Drive Now in 2011 with

300 cars (Kölnische Rundschau, 07/2012) –, together with Daimler, by anticipating the changed

perception of the car. BMW is using this initiative to present its electric vehicle fleet (BMW i3 and

the Mini SE) which is semi-autonomous (Share Now, 2020). Even though, 43% of consumers believe

that 50% of the car owners they know today no longer want to own a personal vehicle by 2025, rather

prefer car sharing initiatives KPMG (2018), Tesla has not been able to launch such initiative so far.

However, in April 2019 Elon Musk introduced the idea of a robotaxi network that should have been

launched this year and generating a gross profit of ≈$30,000 per taxi. However, besides the Tesla cars

not being ready to operate fully autonomous, this project has to gain the approval of regulators first

and this can take time as elaborated in section 2.5.2 (Financial Times, 04/2019). Currently, Elon Musk

stated that there are several things to primarily focus on, such as ramping up the Model Y production,

getting the Gigafactory Berlin to production, expanding the Gigafactory Shanghai, getting Tesla Semi

and Cybertruck to production (electrek, 05/2020). It seems like that Tesla does not have much time

for the car sharing initiative yet.


3.3.7 VRIN

Due to limited access to company-internal information and the complex automotive industry in

general, missing to identify some key competitive advantages might have been occurred during this

internal analysis. This is coherent with Barney’s (1991) theory, as the source of a sustained

competitive advantage should not be easily identifiable. Applying the VRIN framework, key internal

resources and capabilities across the value chain have been analyzed and summed up in the table

below in the hope to provide an understanding of Tesla’s current position in the market:

Table 5: Summary of VRIN analysis

Valu

ab

le

Ra

re

Imp

erfe

ctly

im

ita

ble

Non

-su

bst

itu

tab

le

Competitive Implication

Production capabilities ✔ ✔ ✘ ✔ Temporary competitive advantage

Product capabilities ✔ ✔ ✔ ✔ Sustained competitive advantage

Charging infrastructure ✔ ✔ ✔ ✘ Temporary competitive advantage

Distribution network ✔ ✔ ✔ ✔ Sustained competitive advantage

CEO & Brand ✔ ✔ ✔ ✔ Sustained competitive advantage

Customer understanding ✔ ✘ ✘ ✘ Competitive parity


Chapter 4: Financial Statement Analysis 42

4. Financial Statement Analysis

This chapter intends to provide an understanding of Tesla’s historical performance which will be

pivotal –along with the strategic analysis– when making cash flow projections for the forecast period

in the chapter after next. First, an analysis of the income statement will be provided. Afterwards a

financial ratio analysis will be conducted, touching upon operating efficiency, asset use efficiency,

short-term/long-term liquidity risk, and finally leading to determine one of the most important metrics

for investors, the return on equity (ROE). The fiscal years 2016-2019 set the basis for the following

analysis (Appendix 3, Appendix 4).

4.1 Income Statement Analysis

Among the automotive revenues, the “energy generation & storage” as well as “services and other”

revenues contribute to total revenues. However, the focus lies on the total automotive revenues which

include the “automotive leasing” revenues as this made up 91%, 82%, 86% and 84% of the total

revenues in 2016, 2017, 2018 and 2019, respectively.

Figure 13: Income statement – historical performance

Source: compiled by author, Tesla annual reports

Income Statement, USDm 2016 2017 2018 2019 Historical Average

Total automotive revenues 6,351 9,642 18,515 20,821

Growth % 52% 92% 12% 52%

Total revenues 7,000 11,759 21,461 24,578

Growth % 68% 83% 15% 55%

Total automotive cost of revenues 4,750 7,433 14,174 16,398

as of Total automotive revenues, in % 75% 77% 77% 79% 77%

Total cost of revenues 5,400 9,536 17,419 20,509

as of Total revenues, in % 77% 81% 81% 83% 82%

Gross profit 1,600 2,223 4,042 4,069

as of Total revenues, in % 23% 19% 19% 17% 18%

Total operating expenses 2,266 3,855 4,430 4,138

Growth % 70% 15% -7% 26%

Income (Loss) from operations (EBIT) -666 -1,632 -388 -69

Growth % 145% -76% -82% -4%

Income (Loss) before income taxes (EBT) -745 -2,209 -1,005 -665

Growth % 197% -55% -34% 36%

Net Income (Loss) -772 -2,241 -1,063 -775

Growth % 190% -53% -27% 37%


The gross profit shows a remarkable increase, representing a total growth of 154% from 2016 due to

the significant increase in the automotive revenues. However, as Tesla is nearly a completely

vertically integrated company, high operating expenses diminishes these good results. Tesla

distributes its cars through its own stores and develop further alternative selling platforms, the SG&A

costs made up 89%, 100%, 72% and 64% of the gross profit in the last four fiscal years. Including

the R&D costs, this led to a loss from operations (EBIT) in the last four years. The negative EBIT

inevitably impacts the net income in a negative way, leading to an overall negative net income.

4.2 Financial Ratios – Determining the ROE

The negative net income has a substantial impact on the ROE, as a negative net income will lead to

a negative ROE. In the following, the ROE will be determined by applying the following formula:

ROE = Net Profit Margin ∗ Asset Turnover Ratio ∗ Equity multiplier

Operating Efficiency

Operating efficiency will be assessed by calculating the gross profit margin and net profit margin:

Figure 14: Operating efficiency

While the gross profit margin seems to maintain a steady level, the net profit margin shows a good

trend. The high net profit margin in 2017 can be explained by the Model 3 launch in that fiscal year,

hence resulting in higher cost of revenues (in particular battery costs), increasing R&D and SG&A

expenses as more research had to be done and more stores were needed to distribute the cars.

Asset use efficiency

The asset turnover ratio (ATR) is a measure indicating how efficiently a company uses its asset to

generate revenue and is calculated by dividing the Total revenues by Total asset. A higher ATR

represents a higher efficiency rate of a company’s asset usage (Corporate Finance Institute (CFI),

2020).

Operating efficiency 2016 2017 2018 2019 Historical Average

Gross profit margin 23% 19% 19% 17% 19%

Net profit margin (1) -11% -19% -5% -3% -10%


Figure 15: Asset use efficiency

According to CSIMarket (2020), the four-year ATR ratio for the auto & truck industry ranged

between 1.24 (2016) and 0.69 (2019). Firstly, a positive trend can be observed, and secondly, over

time Tesla’s ATR ratio moved up to the industry average.

Short-Term Liquidity Risk

The short-term liquidity risk represents a firm’s ability to meet its short-term obligations, hence

enabling a company to run its business (Petersen et al., 2017). It is calculated by calculating the ratio

of current assets over current liabilities (Appendix 5).

Figure 16: Short-term liquidity risk

A ratio of 1 is indicating that a company is only just able to cover its current liabilities with its current

assets, greater than 1 would indicate the ability to fully cover short-term obligations, and lesser than

1 would signal a short-term liquidity risk as the company would not be able to meet its short-term

obligations. Tesla seems to have improved this ratio over the last three years and had ratio of 1.1 in

2019. However, this the ratios from the years before indicate that Tesla already dealt with short-term

liquidity risk and this might repeat itself again in the future.

Long-Term Liquidity Risk

The long-term liquidity risk indicates a company’s long-term financial health as well as its ability to

meet all future obligations (Petersen et. al., 2017).

Figure 17: Long-term liquidity risk

Asset use efficiency 2016 2017 2018 2019 Historical Average

Asset turnover ratio (2) 0.3 0.4 0.7 0.7 0.5

Short-term liquidity risk 2016 2017 2018 2019 Historical Average

Current ratio 1.1 0.9 0.8 1.1 1.0

Long-term liquidity risk 2016 2017 2018 2019 Historical Average

Financial leverage 1.4 2.1 1.8 1.3 1.6

Equity multiplier (3) 4.1 5.5 5.2 4.6 4.8


The financial leverage ratio shows the relation of the NIBL to Total stockholder’s equity and in

general, a high ratio represents a higher long-term liquidity risk. While Tesla’s financial leverage

ratio declined from 2017, a ratio of 1.3 in 2019 still is significantly higher than the industry average

of 0.38 in 2019 (CSIMarket, 2020). Having a certain leverage ratio is good, since debt-financing is

cheaper than equity-financing. It remains to be seen whether Tesla will finance its announced projects

with equity or debt.

Equity multiplier

The equity multiplier is a leverage ratio measuring the share of a company’s assets financed by equity

and is calculated by dividing a company’s Total assets by Total shareholder equity. Hence, a higher

ratio would imply that a significant share of the assets was financed by debt, meaning higher long-

term liquidity risk (CFI,2020). Historically, Tesla’s equity multiplier ratios have been very high

indicating a high long-term liquidity risk.

ROE

The return on equity is a profitability measure and is calculated by the ratio of net profit (loss) after

tax over the book value of equity (Petersen et al., 2017).

Figure 18: Return on equity

Due to Tesla’s negative net income, the ROE can only be negative and thereby destroys value for

shareholders. Further, the average global ROE for the auto & truck industry was 7.2% in 2019

(Damodaran, Dataset 2020), a number from which Tesla is far away. This is of course due to the fact that

Tesla still is a young player in the automotive industry and has to massively invest in R&D and other

expansion projects. However, it still has to work on its (operating) efficiency to achieve scale and scope

affects, leading to positive net incomes.

4.3 Conclusion of the Financial Statement Analysis

The financial statement analysis provided important information about Tesla’s current financial situation:

Tesla has shown high growth rates in the past

Very high operating expenses (R&D and SG&A)

Negative net income

Return on equity (ROE) 2016 2017 2018 2019 Historical Average

ROE=(1)*(2)*(3) -14% -43% -18% -10% -21%


Very high long-term liquidity risk, as well as possible short-term liquidity risk

Negative ROE, due to negative net income

Chapter 5: SWOT Analysis 47

5. SWOT Analysis

In the antecedent two chapters, a thorough strategic and financial analysis have been conducted. The

strategic analysis helped identifying Tesla’s strengths and weaknesses, external as well as internal,

but also helped recognizing business opportunities for Tesla. On the other hand, the financial

statement analysis provided a good understanding of Tesla’s financials that can be categorized as

strengths or weaknesses. The following SWOT analysis displays a great overview by summing up

the key findings of strategic as well as financial analysis.

Table 6: SWOT Analysis of Tesla

Strengths Weaknesses

Brand: company that went and sells “green”

Strong innovative capabilities (highly innovative CEO)

Vertically integrated value chain, providing the

complete service for its consumers

Ranked second leading e-mobility leader

Battery:

a) Low battery costs per kWh

b) Unmatched Supercharger network performance

c) Leading in battery range

FSD: ahead of its competitors

No marketing costs

Historically high growth rates

Increased geographical footprint (Shanghai & Berlin

next)

Extension of products (e.g. Semi, Cybertruck)

Launching a mass volume car (Model 3&Y)

Vulnerable financial position:

a) Never had a profitable year

b) high long-term liquidity

risk;

High CAPEX requirements for

upcoming projects;

Experienced ramp-up problems

in the past, might occur again;

Supply chain: single supplier

for most used components and

systems

Opportunities Threats

Share of EVs is expected to increase due to stricter

emission policies & governmental incentives

New segment to electrify, e.g. high passenger density

urban transport

Car sharing initiative/”robotaxi” project

Huge growth potential:

a) ramping-up production volumes for certain plants,

if demand is given,

b) start manufacturing Model 3 in Gigafactory Berlin

c) building up a new plant in a new market

d) energy generation & storage segment

EV incentives are going to

phase out in some key markets

in 2-3 years (e.g. China)

Covid-19 pandemic hitting the

economy (possible decrease in

buying power due to high

unemployment rates)

Technological dilution due to

increased competition

(competitors with high

resources may catch up)


Chapter 6: Forecasting 48

6. Forecasting

The aim of this chapter is to set the basis for Tesla’s future cash flows. However, Tesla being a young

company and having experienced negative cash flows historically makes it challenging and highly

sensitive to predict. Thus, the case company’s value has to be based on future predictions. The

forecasts are based on Tesla’s SEC reports from 2016-2019 as well as on the in-depth analysis of

future automotive sales revenues.

6.1 Forecast Period

Before estimating future cashflows, it is crucial to define the forecast period. The length of this period

depends on when the company will reach a stable growth, hence its steady state. Typically, a

forecasting period of five years is sufficient. However, in situations where the company is in its early

stages, choosing a longer projecting period is more appropriate (Rosenbaum et al., 2009). According

to the strategic analysis, Tesla is going to have launched all of its vehicle models in 2022; hence, all

Gigafactories will be operating by then. The forecasting period is determined by considering five

years (standard case) from including 2022, hence 2020-2026 – a total of seven years.

6.2 Terminal Growth Rate

As earlier presented in section 2.5 and Figure 4 in particular, the passenger car sales market has grown

at a CAGR of 2.27% from 2006-2019. As the automotive industry is highly cyclical, the chosen time

period is a good reflection of this cyclicality as it considers the financial crisis in 2008 and hereby the

possible booms and busts of an economy. This is important as the global economy moves towards a

recession due to the Covid-19 pandemic (Financial Times, 06/2020). Further, it was shown that the

global vehicle sales follow the global GDP movements. This gives validation to consider the long-

term global GDP growth rate the terminal growth rate. Since Tesla reaches a steady state in 2026, the

time period from 2026-2060 will be taken into account. The global GDP (2026-2060) is expected to

grow with a CAGR of 2.32%, as illustrated in Appendix 6 (OECD, 2020). As both proxies, the

industry CAGR from 2006-2019 and the expected global GDP CAGR from 2026-2060 are very close

to each other, it can be assumed that the forecasted global long-term GDP CAGR represents the

automotive industry’s long-term growth rate. Thus, the terminal growth rate for the DCF-model is

assumed to be 2.32%.


6.3 Forecast – Income Statement

The explicit forecast from 2020-2026 will be based on the outcomes from the strategic as well as

financial statement analysis of the company. Special focus will be given to the automotive sale

revenues as these made up 82% of the total revenues in the last two fiscal years.

6.3.1 Forecasting Automotive Sales Revenues

In order to forecast the automobile sales revenues for the forecast period 2020-2026, it is crucial to

provide an overview about all production plants. The forecasted maximum production capacity and

the launch dates of the announced plants as well as models are based on Elon Musk’s statements as

well as expert opinions.

Overview of Plant/Model Launches & Production Capacities

The Figure 19 below provides a great overview of each plant’s production capacity as well as the

launches of the upcoming models with respect to their production volume.

Figure 19: Forecast of production capacity for 2020-2026

FY 2020E FY 2021E FY 2022E FY 2023E FY 2024E FY 2025E FY 2026E

Fremont

Model S & X 79,200 90,000 90,000 90,000 90,000 90,000 90,000

Model 3 & Y 352,000 500,000 500,000 500,000 500,000 500,000 500,000

431,200 590,000 590,000 590,000 590,000 590,000 590,000

Shanghai

Model 3 & Y 174,667 200,000 250,000 250,000 250,000 250,000 250,000

Berlin

Model Y 500,000 500,000 500,000 500,000 500,000

Total Model 3 & Y

production526,667 700,000 1,250,000 1,250,000 1,250,000 1,250,000 1,250,000

Tesla Semi 25,000 50,000 75,000 100,000 100,000 100,000

Roadster 1,000 2,000 2,000 3,000 4,000

Cybertruck 300,000 300,000 400,000 400,000 500,000

Theoretical max.

production capacity605,867 815,000 1,691,000 1,717,000 1,842,000 1,843,000 1,944,000


Following assumptions are made (for supplementary remarks see Appendix 7):

Fremont: Production capacities in FY 2020E are reduced according to the 10-week shutdown

due to Covid-19. Further, the announced Model 3 & Y capacity extension to 500,000 cars for

FY 2020E is postponed to FY 2021E due to Covid-19. From FY 2021E, the production

capacity is assumed to stay constant.

Shanghai: Production capacity is adjusted to the Covid-19 1.5-week shutdown and the

changing production rates. As of June 2020, weekly production rate will be 4,000 cars/week

instead 3,000 cars/week. From FY 2022E, the production capacity will stay constant for the

forecast period.

Berlin: Due to Covid-19, production will not start in late FY 2021E but in FY 2022E and the

production capacity will be 500,000 cars/year. Model 3 is not considered, as no

announcements have been made with regard to this.

Semi: Production will start in FY 2021E with a limited number such as 25,000 and will –

according to Elon Musk– gradually move up to a target rate of 100,000 per year within four

years.

Roadster: Will be launched in FY 2022E, starting with the production of the Founder’s Series

–the first 1,000 to be produced– and then gradually climb up to 4,000 per year.

Cybertruck: Will be launched in FY 2022E with an annual production rate of 300,000,

gradually moving up to 500,000.


Forecasting Total Deliveries

Next step for calculating the automotive sales revenue would be to determine how many units of each

model is delivered in each forecasted year. The Figure 20 provides a helpful overview.

Figure 20: Forecast of total deliveries for 2020-2026

Following assumptions are made:

Model S & X: The FY 2020E delivery number was calculated by multiplying the Q1 2020

delivery number with four and considering only 85% of it with the intention to reflect the

Covid-19 effect. In FY 2021E, the growth rate is expected to be 50% as the production

capacity will increase compared to 2019 and the economy to slowly recover. From FY 2022E

an annual 2% growth for these two models is assumed.

Q1 2020 FY 2020E FY 2021E FY 2022E FY 2023E FY 2024E FY 2025E FY 2026E

Total vehicle production 102,672 605,867 815,000 1,691,000 1,717,000 1,842,000 1,843,000 1,944,000

Deliveries

Model S & X, units 12,200 41,480 62,220 63,464 64,734 66,028 67,349 68,696

Growth in % 50% 2% 2% 2% 2% 2%

Model 3 & Y, units 76,200 289,560 560,000 875,000 918,750 964,688 1,012,922 1,063,568

Delivery rate as of

total production in %80% 70%

Growth in % 5% 5% 5% 5%

Model Y delivered from

Berlin factory, units350,000 367,500 385,875 405,169 425,427

Tesla Semi 17,500 37,500 60,000 85,000 87,550 90,177

Delivery rate as of

total production in %70% 75% 80% 85%

Growth in % 3% 3%

Roadster 1,000 1,700 1,870 2,550 3,400

Delivery rate as of

total production in %100% 85% 85% 85%

Growth in % 10%

Cybertruck 270,000 290,250 360,000 387,000 450,000

Delivery rate as of

total production in %90% 90% 90%

Growth 7.50% 7.50%

Total Deliveries 88,400 331,040 639,720 1,246,964 1,335,434 1,477,586 1,557,371 1,675,840


Model 3 & Y: The FY 2020E delivery number is calculated by multiplying the Q1 2020 units

delivered by four and considering 95% to be delivered. This assumption is based on two

things: 1.) Tesla’s main markets –and further European markets such as Germany– have

extended or introduced further incentives to buy EVs. I expect the delivery percentage to be

80% and 70% in FY 2021E and FY 2022E, respectively since the incentives e.g. China will

continue until 2022. From 2022, a modest growth rate of 5% is assumed for the remaining

period.

Semi: As mentioned in chapter two, preorder’s amounted to 2,000 units in mid-2019

(Teslerati, 10/2019). However, it is assumed Tesla will deliver 70% of the produced Semis in

FY 2021E. As the production volume increases by time, the delivery rate moves up to 85%

in FY 2024E. As it reaches its maximum capacity by then, a growth rate of 3% is assumed for

the remaining forecasted two years.

Roadster: Tesla Roadster will be launched in FY 2022E. It is assumed that in FY 2022E only

the Founder’s Series (1,000 units) will be produced and fully delivered. As the production

volume moves up in FY 2023E, the delivery rate decreases to 85%, still resulting a higher

absolute number. Considering this vehicle to be priced at $200,000 after the first 1,000 units,

the delivery number is remarkable. As the production volume stays the same for FY 2024E

as in FY 2023E, a growth rate of 10% is assumed. A delivery rate of 85% of total production

is predicted for the remaining two years.

Cybertruck: According to electrek (06/2020), at present preorders for the Tesla Cybertruck

amounts to 650,000. However, as the initial production volume will start with 300,000 units,

a delivery rate of 90% for FY 2022E is assumed which seems very reasonable. As the

production volume stays the same in FY 2023E a growth rate of 7.5% is assumed. The same

pattern repeats itself for the remaining four years, ending up with total estimated delivered

units of 450,000 in FY 2026E.


Forecasting Automotive Revenues

In the following, the forecasted total automotive sales revenue for the forecasted period will be

calculated. In doing so, the costs for the full self-driving software will be considered as Tesla

customers are able to add the autopilot option to their purchase. Further, autonomous driving is

considered a megatrend in the automotive industry.

Figure 21: Forecast of total revenue for 2020-2026


Average price: The average price was calculated considering the U.S. prices (as prices across

the globe don’t differ much) with incentives as –already elaborated in the strategic analysis–

incentives will be the main driver to attract consumers, in particular during the recent

economic slowdown. Further, an annual 1% price decrease is assumed by achieving

production efficiency (Appendix 8).

Average $price/unit

in thousandsFY 2020E FY 2021E FY 2022E FY 2023E FY 2024E FY 2025E FY 2026E

Model S 79.49 78.70 77.91 77.13 76.36 75.59 74.84

Model X 84.69 83.84 83.00 82.17 81.35 80.54 79.73

Model 3 40.36 39.95 39.55 39.16 38.77 38.38 38.00

Model Y 50.69 50.18 49.68 49.18 48.69 48.21 47.72

Tesla Semi 165.00 163.35 161.72 160.10 158.50 156.91

Roadster 250.00 200.00 198.00 196.02 194.06

Cybertruck 53.23 52.70 52.17 51.65 51.14

Revenue in USDm

Model S & X 3,405 5,057 5,106 5,156 5,207 5,258 5,309

Model 3 & Y 13,182 25,238 40,813 42,425 44,100 45,842 47,653

Tesla Semi 2,888 6,126 9,703 13,608 13,877 14,150

Roadster 250 340 370 500 660

Cybertruck 14,373 15,296 18,783 19,989 23,011

FSD cost (not in USDm) 7,500 8,000 8,000 8,000 8,000 8,000 8,000

FSD revenue 1,490 3,327 6,983 8,013 9,457 10,590 12,066

Total Revenue 18,077 36,509 73,650 80,933 91,525 96,056 102,849


Model S & Y revenue: When calculating the revenue for these two models, it is assumed that

both models contribute equally, hence each 50%. This assumption has to be made as Tesla

does not distinguish between the sales numbers of these models anymore.

Model 3 & Y revenue: Calculating the sales revenue for these two models, the approach was

the same as for Model S & Y for the years FY 2020E and FY 2021E. However, with the

launch of the Gigafactory Berlin in FY 2022E that is going to manufacture Model Y only, this

calculation has to be adjusted. Hence, the units of Model 3 & Y delivered from Berlin will be

treated separately from the sum of Model Y delivered from Fremont and Shanghai. The Model

Y units from Berlin will be calculated with the average Model Y price in the related year

whereby the Model 3 & Y units from Fremont and Shanghai will be calculated by taking the

average price of both models and under the assumption that each model contributes equally,

hence each 50%.

FSD revenue: When calculating the revenues generated by the FSD upgrade, for FY 2020E it

is assumed that 60% of the customers will purchase it. This will increase by 5% annually,

until reaching 90% in FY 2026E. Hence, 90% of the customers will pay for this upgrade.

Further, in FY 2020E the FSD price is reflected by $7,500 as the cost to include this upgrade

rose from $7,000 to $8,000 starting from July 2020 (electrek, 07/2020).

6.3.2 Forecasting other Income Statement Items - Revenues

Automotive leasing: It is assumed that the automotive leasing revenues drop by 5% in FY

2020E to reflect the Covid-19 effect and is expected to decrease by 5% to reflect a slow

increase in FY 2021E. From FY 2022E it is expected to grow at 15%.

Energy generation and storage: As it is stated in the Q4 2019 report, the deployment for this

segment is expected to grow by 50%, it is assumed that this segment shows a constant a

growth rate of 25%.

Services and other: These revenues are related to repairs, vehicle insurance revenue, sales of

used vehicles, etc. (Tesla Annual Report, 2020 p.1). It is estimated that the revenues will show

a modest increase by 5% in FY 2020E and then show a growth of 30% in FY 2021E. The

growth rate for FY 2022E will grow by 50% as through the launch of the Gigafactory Berlin,

the revenues for this section will show a remarkable increase too. From FY 2023E, it is

assumed to show a growth of 20% for the remaining forecast period.


Pro Forma Income Statement

The overview below provides the historical average based on the last three fiscal years, 2016-2019.

(For further information, see Appendix 9).

Figure 22: Pro forma income statement for 2020-2026


Revenue growth: This relates mainly to the predicted automotive sales revenue.

Gross margin: It is assumed that the gross margin starts near the historical average and stays

constant for FY 2021E and FY 2022E as Tesla has to deal with e.g. a larger product volume,

order more raw materials, etc. From FY 2023E it is predicted that Tesla achieves scale and

scope effects as well as reduce its battery costs. Additionally, the margin increases by annually

2%. Moreover, the costs were predicted based on historical averages with small adjustments

for the forecast period.

R&D and SG&A: These two sections both make up the operating expenses and Tesla stated

in its last annual report (p.41) aiming to reduce these expenses as a percentage of the total

revenues. Considering this, a gradual decrease is assumed. Considering the increase in

revenues, the operating expenses are still high.

Depreciation: This is assumed to make 16% of the PP&E, as Tesla has to massively invest in

machinery equipment considering the production ramp-up, Gigafactory Berlin and the

upcoming models. In addition, the Supercharger network is constantly expanding.

Pro Forma Income Statement

Historical

average

FY

20

20

E

FY

20

21

E

FY

20

22

E

FY

20

23

E

FY

20

24

E

FY

20

25

E

FY

20

26

E

Revenue Growth 55% -6% 85% 92% 11% 14% 7% 9%

Gross-margin 18% 19% 18% 18% 20% 22% 24% 26%

R&D, as of revenue in % 8% 6% 5% 2% 1.5% 1% 1% 1%

SG&A, as of revenue in % 15% 12% 8% 4% 2% 2% 1% 1%

Depreciation, as of PP&E in % 18% 16% 16% 16% 16% 16% 16% 16%


6.4 Forecast – Balance Sheet

Below is a pro forma balance sheet provided with the needed FCFF inputs.

Figure 23: Pro forma balance sheet for 2020-2026


PP&E: Future PP&E estimations are based on the historical average of the last two fiscal

years as the relative PP&E values (as of revenue) of earlier years can be considered outlier.

While the PP&E decreases in relative values, it shows a remarkable increase. This seems

coherent with the Gigafactories in construction and in development.

CAPEX: The CAPEX values are estimated based on management guidelines. According to

the last annual report (p.41), the capital expenditures in FY 2020E and the following two fiscal

years are expected to be between $2.5bn and $3.5bn. The forecast lies at the high end of

management guidance over the next 3 years (FY 2020E-FY 2022E). Thereafter, it drops

gradually to $1.5bn, still needing high CAPEX for production ramp-ups that is spread over

the forecast period.

Current assets: Forecasted based on the last three-year average, as this should provide a

reliable estimation. A gradual relative increase is considered, by considering increasing

receivables from global business activities.

Current liabilities: Estimated based on the last two-year average and is expected to gradually

show a relative decrease.

Pro Forma Balance Sheet

Historical

average FY

2020E

FY

2021E

FY

2022E

FY

2023E

FY

2024E

FY

2025E

FY

2026E

PP&E, as of Revenue in % 48% 48% 48% 48% 40% 40% 40% 40%

CAPEX – 3500 3500 3500 3000 2500 2000 1500

Current assets, as of revenue in % 23% 23% 23% 24% 24% 25% 25% 26%

Current liabilities, as of revenue in % 35% 35% 35% 34% 34% 33% 33% 32%

Chapter 7: Weighted Average Cost of Capital (WACC) 57

7. Weighted Average Cost of Capital (WACC)

The weighted average cost of capital (WACC) is a widely accepted method for use as the discount

rate to calculate the present value (PV) of a company’s forecasted free cash flow (FCF) and terminal

value. It represents the weighted average of the required return on the capital invested – usually the

debt and equity – in a given firm. Further, WACC may also be thought of as an opportunity cost of

capital or what an investor would hope to earn in an alternative investment profile (Rosenbaum et al.,

2009).

The formula for the calculation of WACC is (Rosenbaum et al., 2009):

𝑊𝐴𝐶𝐶 = 𝑟𝑒 ∗𝐸

𝐷 + 𝐸+ (𝑟𝑑 ∗ (1 − 𝑡)) ∗

𝐷

𝐷 + 𝐸

where: re = cost of equity

rd = cost of debt

t = marginal tax rate

E = market value of equity

D = market value of debt

The capital structure or total capitalization (enterprise value (EV)) of a company includes two main

components, debt and equity (D+E). The rates re and rd represent the company’s market cost of equity

and debt, respectively (Rosenbaum et al., 2009).

7.1 Target Capital Structure

The WACC is determined on choosing a target capital structure for the company that is coherent with

its long-term strategy (Rosenbaum et al., 2009). In order to represent the true opportunity cost of both

lenders (debt) and investors (equity), the long-term capital structure has to be based on market values

(Petersen et. Al, 2017). In doing so, the debt-to-EV ratio (calculated as NIBL/(NIBL+Equity)) for

Tesla in the (2017-2019) would be 18%, 15%, 11%., respectively for the last three-year period

(Appendix 10). Currently, Tesla’s capital structure does not provide a valid reflection of the target

capital structure. In this case, Petersen et al. (2017) recommends using comparable companies’ capital

structure as a benchmark. Damodaran (2020), estimates the NIBL/(NIBL+Equity) ratio to be 53.44%

for the auto & truck industry based on 132 companies globally. Since Tesla does not reveal its target


NIBL/(NIBL+Equity) ratio, this ratio is assumed to converge to the auto & truck industry average.

Thus, the industry average of 53.44% will be considered for the WACC calculation.

7.2 Cost of Equity (re)

The cost of equity is the required annual rate of return, which is expected to receive by a company’s

equity investors (including dividends) and is not simply observable in the market. In order to calculate

the return on a company’s equity, the capital asset pricing model (CAPM) will be employed

(Rosenbaum et al., 2009).

Capital Asset Pricing Model

The CAPM relies on the premise that equity investors need to be compensated for their assumption

of systemic risk (related to the overall market) in the form of a risk premium, or the amount of a

market return in excess of a stated risk-free rate.

The formula is as follows (Rosenbaum et al., 2009):

𝑟𝑒 = 𝑟𝑓 + 𝛽𝑙 ∗ (𝑟𝑚 − 𝑟𝑓)

where: re = cost of equity

rf = risk-free rate

l = levered beta

rm = expected return on the market

rm – rf = market risk premium (mrp)

In the following, each of these components will be determined.

Risk-Free Rate

The risk-free rate is the expected rate of return received by investing in a “riskless” security. U.S.

government securities, like T-bills (Treasury-bills), T-bonds or T-notes are considered by market

“risk-free” as they are backed by the U.S. federal government (Rosenbaum et al., 2009). In order to

consider the currency and inflation, cashflows and risk-free rates have to be consistent (Damodaran,

2008). Both, U.S. T-bonds rates and Tesla’s cash flows, are given in nominal values. Further, Tesla’s

cashflows are reported and forecasted in USD. Hence, there is validity to use the T-bond rate as a

proxy for the risk-free rate. In the Figure 24 below, the rates for a 10-year U.S. government bond are

given for the period 2010-2019.


Figure 24: U.S. government treasury bonds from 2010 to 2019 in %

Source: compiled by author / OECD, 2010-2019

As of Q4 2019, the U.S. 10-year government bond exhibited a rate of 1.8%. However, as the T-bond

rate has been fluctuating around 1,56%-3.72% in the chosen time period and the WACC is assumed

to stay constant for the forecasted period, applying the 10-year average provides further validity.

Hence, the risk-free rate is estimated to be 2.41%.

Beta ()

Beta () is a measure of the covariance between the rate of return on a company’s stock and the

overall market return (Rosenbaum et al., 2009). It can be determined in various ways, whereby two

will be elaborated; 1.) Financial information resources, and 2.) Industry beta.

Financial Information Resources

Since Tesla Inc. is a publicly traded company, the beta can be sourced from reliable financial

information resources such as NASDAQ, Reuters, Yahoo Finance and MarketWatch. As can be seen

in Table 7, the average beta of these resources would be 1.17. However, this approach might not be

a reliable indicator for future returns (Rosenbaum et al., 2009).


Table 7: Average Beta for Tesla

Resource Beta

NASDAQ 1

Reuters 1,23

Yahoo Finance 1,2

MarketWatch 1,24

Average 1,17

Source: compiled by author / NASDAQ / Reuters / Yahoo Finance / MarketWatch

Industry Beta

An alternative way to determine the beta is to look for specific industry betas. As, in the long-term,

Tesla’s beta is expected to approach the industry beta, this represents a valid approach. Based on 134

global companies, Damodaran (2020) determined the unlevered beta for the auto & truck sector to be

0.85.

Going on with the unlevered beta (u) of 0.85, which has to be levered. When applying the formula

(Rosenbaum et al., 2009) for levering the beta, the expected capital structure and marginal tax rate

will be used.

β𝑙 = β𝑢 ∗ (1 +D

𝐸∗ (1 − t))

β𝑙 = 0.85 ∗ (1 +53.4%

46.6%∗ (1 − 23.79%))

β𝑙 ≈ 1.59

The beta, which will be considered for the WACC calculation, is 1.59

Market risk premium (rm – rf)

The market risk premium (mrp) is the spread of the expected market return over the risk-free rate

(Rosenbaum et al., 2009). According to Petersen et. al (2017), three ways can be approached when

determining the market risk premium: 1.) Sourcing estimates from investors and using the average,

2.) Determining the ex-post excess return based on past data, and 3.) Calculating the ex-ante premium

with respect to current stock prices. The second approach is widely used among practitioners

(Damodaran, 2012). Damodaran constantly keeps updating his estimates, which equals to 6.01% for

the S&P500 in January 2020 (Damodaran Dataset, 2020). Hence, for ongoing WACC calculations a

market risk premium of 6.01% will be considered.


7.3 Cost of Debt (rd)

The cost of debt (rd) expresses a company’s credit profile at the target capital structure that is based

on various factors such as size, sector, outlook, credit rating, cyclicality, etc. In the case of being at

the target capital structure, the cost of debt is derived from e.g. its outstanding bonds. On the other

hand, if the company is not at its target capital structure, the cost of debt has to be sourced from its

peer companies (Rosenbaum et al., 2009). However, Damodaran (2020) provides a credit spread of

5.15% (considering Tesla’s rating to be B- by S&P (11/2019)) for developed market firms with a

market capitalization greater than $5bn.

Taking Damodaran’s estimate to consideration and adjusting it for the risk-free rate, a required return

on straight debt of 7.56% is achieved.

Tax Rate (t)

The marginal tax rate is preferred, as determining the effective tax rate relies on various factors

difficult to satisfy in practice (Petersen et al., 2017). Since Tesla operates internationally, Damodaran

(2020) suggests taking the global average marginal tax rate of 23.79% (KPMG, 2020) is appropriate.

7.4 Overview of WACC components

After determining all the relevant WACC inputs, the WACC for Tesla corresponds to 6.97%.

Considering the strategic as well as financial analysis statement analysis, an adjustment to the WACC

could be seen necessary. This would further be validated by Tesla’s SEC report (12/2019) as it clearly

states that just like in the past Tesla might experience delays or other complications in the design,

manufacture, launch and production ramp in the future.


Figure 25: WACC

In addition, Morgan Stanley estimated Tesla’s WACC to 13% in December 2019 and J.P. Morgan to

9.9%, and other financial information resources give a range from 6.6%-8.6% (Finbox, 12/2019).

Hence, the calculated WACC seems to be in the lower range and not fully represent the weighted

average of the required return on the capital invested. For this purpose, one might add a risk-premium

of e.g. 2%, leading to an adjusted WACC of 8.97%. This could make the DCF model more

conservative. However, as this approach has no theoretical foundation, this issue will be reopened

and analyzed in the sensitivity analysis.

Target capital structure

NIBL/(NIBL+Equity) 53.44%

Equity/(NIBL+Equity) 46.56%

Cost of equity

risk-free rate 2.41%

systematic risk (beta) 1.59

market risk premium 6.01%

Cost of equity 8.15%

Cost of debt


credit spread (risk premium on NIBL) 5.15%

tax rate 23.79%

After-tax cost of debt (adjusted for the risk-free rate) 5.76%

WACC 6.87%

Chapter 8: Valuation – Discounted Cash Flow Model (DCF) 63

8. Valuation – Discounted Cash Flow Model (DCF)

The aim of this chapter is to provide a theoretical background of the DCF model with respect to its

application and limitation. Thereinafter, a DCF analysis and its output for Tesla will be presented.

8.1 DCF – Theoretical background

The discounted flow cash analysis is a broadly applied valuation methodology that is premised on the

principle that the value of a company can be derived from the present value of its forecasted free cash

flow (FCF). The projected FCF is determined by making assumptions regarding a company’s

financial performance, sales growth rates, profit margins, capital expenditures and net working capital

(NWC). After projecting the FCF for the defined forecast period, a terminal value (TV) is calculated

to capture the remaining value of the target company beyond that projection period. This is done, as

it is difficult to accurately forecast a company’s financial performance over an extended period.

Following, the forecasted FCF and terminal value are discounted to the present at the company’s

WACC. Lastly, the present value (PV) of the FCF and the terminal are added up to determine the

enterprise value, which is crucial for the DCF valuation (Rosenbaum et al., 2009). In the following,

the formulas are shown:

FCFF = NOPAT + Depreciation & Amortization – CAPEX − △ NWC (Rosenbaum et al.,

2009)

Enterprise value = ∑𝐹𝐶𝐹𝐹𝑡

(1+𝑊𝐴𝐶𝐶)𝑡𝑛𝑡=1 +

𝐹𝐶𝐹𝐹𝑛+1

(𝑊𝐴𝐶𝐶−𝑔)𝑡 ∗1

(1+𝑊𝐴𝐶𝐶)𝑛 (Petersen et al., 2017)

Limitations of the DCF model

Even though the DCF model is considered to be the best practice by Damodaran (2002), just like any

other model, this model comes with some limitations. For instance, this model is highly dependent

on the projections made, especially when a longer forecast period is chosen. Further, it is very

sensitive to assumptions such as the WACC, terminal growth rate or margins. Additionally, the

present value of the terminal value can make up to 75% or more of the DCF valuation and this reduces

the significance of the forecasted annual FCF. Lastly, it assumes a constant capital structure, which

is needed when determining the WACC (Rosenbaum et al., 2009)


8.2 Tesla – DCF valuation

This section will present the DCF model, following the two-stage valuation approach. The equity

value (market capitalization) is determined by deducting the NIBL in 2019 from the enterprise value.

Further, the price per share in $ is determined by dividing the equity value with number of shares

outstanding at the valuation date. For complementary information, see Appendix 11.

Figure 26: DFC valuation as of 31.12.2019

The projected FCFF for the first year is negative due to the high CAPEX requirements for the

announced Gigafactories and upcoming models. Further, the total revenues are expected to decrease

Assumptions

WACC 6.87%

Terminal growth rate 2.32%

Marginal tax rate 23.79%

DCF-Model FY 2020E FY 2021E FY 2022E FY 2023E FY 2024E FY 2025E FY 2026E

USDm

Total revenues 23,153 42,806 82,195 91,286 104,079 111,288 121,344

Gross Profit 4,457 7,553 14,731 18,153 22,810 26,510 31,283

Total operating expenses 4,168 5,565 4,932 3,195 3,122 2,226 2,427

Operating earnings 290 1,989 9,800 14,958 19,687 24,284 28,856

NOPAT 221 1,516 7,468 11,400 15,004 18,507 21,991

Depreciation & Amortization 1,778 3,288 6,313 5,842 6,661 7,122 7,766

CAPEX 3,500 3,500 3,500 3,000 2,500 2,000 1,500

△ NWC 515 -2,358 -3,083 -909 802 -577 1,622

FCFF -2,016 3,661 13,364 15,151 18,362 24,206 26,635

PV of FCFF -1,886 3,206 10,948 11,614 13,171 16,246 16,726

Output

USDm

∑ PV of FCFF 70,025

Terminal Value (TV) 375,977

PV of TV 236,109

Enterprise Value 306,134

NIBL 9,685

Equity Value 296,449

shares outstanding in m 181

Price per share in $ 1,637.84


in FY FY 2020E and this contributes to the negative FCFF as well. However, from 2021 positive

FCFF is expected despite having a high CAPEX. This is mainly because of the expected high

automotive sales revenue and the Semi launch. In Addition, there is a remarkable FCFF rise from FY

FY 2021E to FY FY 2022E. This can be explained by the launch of Gigafactory Berlin –expected to

start with a production volume of 500,000 Model Y units per year–, the very expensive Tesla Roadster

and based on the preorders the highly popular Cybertruck. From FY FY 2022E through FY FY 2024E

the increase in FCFF is modest and can be explained stating that by that time the most of the

Gigafactories will have achieved their maximum production capacities. However, the decline of the

CAPEX contributes to effect that too. The FCFF increase from FY FY 2024E through FY FY 2026E

can be justified by firstly, the decreasing CAPEX, and secondly, the continuing production ramp-up

of certain models and achieving scale and scope effects, hence efficiency.

As of 31st of December 2019, Tesla closed with a share price of $418.33 (market capitalization of

$75.7bn) (GuruFocus, 2020) which is remarkably lower, corresponding to just a quarter, than the

$1637.84 (market capitalization of $296.4bn) computed. While buying Tesla shares would be

considered a lucrative investment strategy, one should take into account that the present value of the

terminal value accounts to 77.1% of the total enterprise value in the present case. This will further be

touched upon in the sensitivity analysis.

Chapter 9: Sensitivity Analysis 66

9. Sensitivity Analysis

According to Petersen et. al. (2017), a DCF analysis should always be followed by a sensitivity

analysis, examining the outcome from changing one or more key variables. The WACC is calculated

on various assumptions including the target capital structure, the beta, the market risk premium and

the credit spread. Further, the present value of the terminal value amounted to 77.1% of the total

enterprise value making it very sensitive to the estimated long-term growth rate. Also, conducting the

WACC calculation based on the assumption that Tesla will reach the industry target capital structure

should be sensitized. Especially, Tesla being far away from the target capital structure. Further, since

the current risk-free rate for 10-year T-bond is 0.7% (Bloomberg, 2020), the risk-free rate should be

sensitized as well.

WACC & Terminal Growth Rate

The WACC is assumed to stay constant over the forecast period, which makes it an extremely

sensitive assumption. Also, as previously touched upon, many reliable financial information

resources estimated the WACC for Tesla to be around 6%-13%. In order to provide an overview of

how a 0.75% increase or decrease would affect the share price, the WACC is sensitized. Assuming

the same long-term growth rate, a change of 0.75% in either way remarkably affects the share price.

An increase of 0.75%-2.25% leads to a share price drop of ≈$300-$700. At the same time, a decrease

of 0.75%-2.25% in the WACC –assuming the base case terminal growth rate (TGR)– an increase of

≈$400-$2,200 can be observed. Hence, the Tesla’s share price is highly sensitive to even small

changes in the WACC.

Figure 27: WACC & Terminal Growth Rate

1637.84 4.62% 5.37% 6.12% 6.87% 7.62% 8.37% 9.12%

1.57% 2980 2253 1777 1445 1203 1019 877

1.82% 3219 2391 1864 1503 1243 1048 898

2.07% 3505 2549 1961 1567 1287 1080 921

2.32% 3853 2734 2071 1638 1335 1114 946

2.57% 4286 2952 2197 1717 1388 1150 972

2.82% 4839 3213 2342 1806 1446 1191 1001

3.07% 5570 3530 2511 1907 1511 1235 1032

WACC

Ter

min

al G

row

th R

ate

Chapter 9: Sensitivity Analysis 67

On the other hand, a 0.25% change in the terminal growth rate, which was estimated according to the

real GDP long-term growth rate (2026-2060), affects the share price more the smaller the WACC.

Thus, the share price is more sensitive to a change in the TGR when the WACC is lower. For instance,

while a 0.25% change in the TGR changes the share price by ≈$70-$80 in the base case, for a WACC

of 4.62% it corresponds to a ≈$350-$430 change. Lastly, a 0.25% change in the TGR considering a

WACC of 9.12% changes share price minimally, ≈$25 in either way. Hence, the terminal value

impacts the share price the more the lesser the WACC and the higher the TGR, which is very intuitive.

Risk-free Rate & Target Capital Structure

The DCF model assumes a constant risk-free rate. In the present case, the risk-free rate was estimated

by the 10-year average yield of a 10-year T-bond. However, in the current state, the risk-free rate is

far under 1%. Hence, it is necessary to sensitize the share price considering the current state. Further,

the DCF model assumes a constant target capital structure and the beta was levered applying the

target capital structure. Hence, while sensitizing the share price for the target capital structure, a

sensitivity analysis for the (implied) beta is conducted simultaneously.

Figure 28: Risk-free Rate & Target Capital Structure

The share price does not seem to be highly sensitive to a 0.5% change in the risk-free rate. In the base

case, the share price changes by ≈$30 in either way. However, changing the debt portion (NIBL/

(NIBL+Equity Value)) by 5% in either way, changes the share price by ≈$60-$70 in the base case.

Further, a change of the debt portion of the capital structure by 5% leads to a change of 0.7 in the

beta. Hence, one could also say that a 0.7 change in the beta –the beta that was initially levered by

applying the base case target capital structure– leads to a ≈$60-$70 change of the share price in the

base case.

1637.84 0.91% 1.41% 1.91% 2.41% 2.91% 3.41% 3.91%

1.80 68.44% 1545 1518 1492 1466 1442 1418 1395

1.73 63.44% 1604 1576 1547 1520 1494 1468 1443

1.66 58.44% 1668 1637 1607 1577 1549 1521 1494

1.59 53.44% 1736 1702 1670 1638 1607 1577 1548

1.52 48.44% 1808 1772 1737 1702 1669 1637 1606

1.45 43.44% 1886 1846 1808 1771 1735 1701 1667

1.38 38.44% 1969 1926 1885 1844 1806 1768 1732

Risk-free Rate

NIB

L/(

NIB

L+

Eq

uit

y V

alu

e)implied

beta

Chapter 10: Real Options Valuation (ROV) 68

10. Real Options Valuation (ROV)

The aim of this chapter is to firstly provide a theoretical background for a real option valuation

(ROV). Hereinafter, this valuation approach will be applied to one of the in the strategic analysis

identified business opportunities for Tesla using the Black-Scholes model. The identification of the

option to value and the Black-Scholes model components will be discussed after the theoretical part.

10.1 Theoretical Background

According to Damodaran (NYU Stern Lecture Slides, 01/2012) and McKinsey (01/2000) traditional

DCF approaches in some cases underestimate or even ignore the value of an asset, especially if the

following options are embedded in the asset:

Option to delay: deferring the business decision to the future

Option to expand: expanding into new markets or launching a new product

Option to abandon: stopping production or abandoning investments in case of identifying

great potential for losses at early stages

However, Damodaran stresses that an option pricing valuation is not an alternative to the DCF

valuation but rather an augmentation, thus supplementing the DCF model (NYU Stern Lecture Slides,

01/2012).

Black-Scholes Model

The Black-Scholes model can only be applied for European calls and puts, meaning they can only be

exercised at maturity. In contrast, the American option can be exercised before maturity. The formula

for the dividend-protected Black-Scholes model is as follows (Damodaran):

𝑉𝑎𝑙𝑢𝑒 𝑜𝑓 𝑐𝑎𝑙𝑙 = 𝑆 𝑁(𝑑1) − 𝐾 𝑒−𝑟𝑡 𝑁(𝑑2)

where: d1 =ln(

𝑆

𝐾)+(r +

𝜎2

2)t

𝜎√𝑡

d2 = d1 − 𝜎√𝑡

S = current value of underlying asset

K = strike price of the option

t = life to expiration of the option


r = riskless interest rate corresponding to the life of the option

𝜎2= variance in the ln(value) of the underlying asset

10.2 Tesla – Project Valuation using ROV

Tesla seems to be not valued for the here-and-now but rather for its high disruptive potential and

future growth due to the new upcoming models and high-marginal technology services, e.g. self-

driving cars (Financial Times, 02/2020). Hence, performing a ROV on top of a traditional DCF

approach seems inevitable.

10.2.1 Identifying the Option

The most important options relating to Tesla and their business case have been identified in the

strategic analysis. These options were also summed up in the SWOT analysis under “Opportunities”.

The identified options were the following:

Launching a new product, e.g. high-passenger-density urban transport

Implementing the robotaxi project

Ramping up production volumes if demand is given

Start to manufacture Model 3 in Gigafactory Berlin

Building a new plant in a new market

The robotaxi project seems to be the most relevant option to value, as it combines three future

megatrends in the automotive industry, namely: 1.) EV fleet, 2.) car sharing, and 3.) autonomous

driving. It is important to remember according to KPMG (2018), 43% of consumers believe that 50%

of the car owners they know today no longer want to own a personal vehicle by 2025, rather prefer

car sharing initiatives. Further, the number of cars on the road will double from 2017 to 2 billion by

2040 – more will be electric, shared and autonomous – according to the Organization of the Petroleum

Exporting Countries (OPEC) (Financial Times, 07/2017). Considering the trends and market outlook,

the robotaxi project stands out.

10.2.2 Length of the Option

The length of the option is the time to expiration on the option (Damodaran NYU Lecture Slides,

n.d.). In this case, the length was determined by taking U.S. government executives’ opinion on when

they expect level 5 autonomy will be legally approved. 42% of the government executives expect it

to be in 2030, 17% in 2025, 2040 or “NEVER”, respectively and 8% expect autonomy readiness in


2050 (Appendix 12). Hence, 2030 seems to be a reasonable date to expect going live with this project.

This would make the length of the option 10 years, 2020-2029. As the Black-Scholes Model is

applied, the option can only be exercised at maturity, hence 2029.

10.2.3 Uncertainty

Determining the uncertainty is crucial and depends on the underlying asset. In this case, there seems

to be two big sources of uncertainty for Tesla’s robotaxi project: achieving an adequate level of

technical autonomy and gaining the approval of regulators. Hence, the risk measure –volatility of the

underlying asset– has to do with these uncertainties. There two ways to determine the volatility

(standard deviation) of the underlying asset: 1.) Performing a Monte Carlo Simulation (Francic et. al,

2004), or 2.) estimate the standard deviation using the annualized standard deviation in firm value of

publicly traded firms in the correspondent market (Damodaran NYU Lecture Slides, n.d.). However,

Damodaran’s approach does not really apply here in this case as there is no publicly traded company

with exactly the same business model as the robotaxi project. Recently, China approved Pony.ai’s

autonomous car sharing project (Financial Times, 05/2020). Since Pony.ai is not a publicly traded

company, Damodaran’s approach cannot be followed. Nevertheless, in the broader sense the robotaxi

project is a car sharing project. This would allow to estimate the standard deviation based on Uber’s

as well as Lyft’s annualized standard deviation. Uber’s average 252-day historical stock volatility

was 51 and Lyft’s 61.5 (Market Chameleon, 2020). As of January 2020, Damodaran (Dataset)

measured the standard deviation in the global auto & truck industry across 131 companies to be

20.23%. As there is no perfectly estimate available, the standard deviation should be sensitized.

10.2.4 Robotaxi Project – Option Value

This section will provide a step-by-step guidance through the real option valuation.

Assumptions for the Determining Exercise Price

In the following, the assumptions regarding this real option valuation will be presented. These are

mainly based on Tesla’s Autonomy Day video on YouTube (Tesla Autonomy Day, YouTube 04/2019

starting at 3:06:00):


Figure 29: Assumptions for robotaxi DCF

Figure 30: PV of set-up and development costs required to exercise the option (in USDm)


Geographical limitation: This model considers the U.S. market only, as level 5 autonomy

regulatory approval will vary from country to country.

FSD: This model assumes Tesla to achieve an adequate level of autonomy by 2029

Fleet size: Elon Musk expects to have a fleet size of 10m Tesla-owned robotaxis globally in

the long-term. While Tesla owners have the option to enlist their car into this Tesla Network,

this model excludes this option for simplicity purposes. Further, this model assumes a fleet

size of 400,000 robotaxis for 2030 –launch year.

R&D expenses: An ongoing R&D expense of $500m is assumed to develop the FSD beyond

the state of art and to be extremely safe. The R&D expenses are expected to be due over the

whole projection period (2020-2035) as the FSD has to be constantly improved.

Assumptions

WACC 6.87%


Tax rate 23.79%

long term growth rate 2.32%

FY

20

20

E

FY

20

21

E

FY

20

22

E

FY

20

23

E

FY

20

24

E

FY

20

25

E

FY

20

26

E

FY

20

27

E

FY

20

28

E

FY

20

29

E

Revenues

Costs:

R&D expenses 500 500 500 500 500 500 500 500 500 500

Manufacturing costs 7,000 7,000

Gigafactory costs 3,000

Supercharger stations 25 25 25 25

other costs 2,000

maintenance costs

Total costs: 500 500 500 500 500 3,500 525 525 7,525 9,525

Operating earnings: -500 -500 -500 -500 -500 -3,500 -525 -525 -7,525 -9,525

Net Profit: -500 -500 -500 -500 -500 -3,500 -525 -525 -7,525 -9,525

PV -468 -438 -410 -383 -359 -2,349 -330 -309 -4,138 -4,901


Supercharger stations: It is expected that Tesla will have to set up Supercharger stations (on

average 8 Superchargers per station (Tesla, 2020)) solely for the robotaxi fleet. According to

an UBS report, the cost to build a supercharging station is $250,000 (CleanTechnica,

08/2019). A total of 400 Supercharger stations is projected to be built in the last four years of

the option.

Gigafactory: This model goes with the assumption that Tesla is going to build a Gigafactory

to manufacture the robotaxis. It will cost 3$bn (estimated on the basis of the €5bn cost for

Gigafactory Berlin).

Manufacturing costs: Elon Musk stated that the current price to manufacture a robotaxi is

<$35,000 and expects this to decline to <$25,000 in a few years. This model goes with the

high-end cost expectation, as Elon is known to be too optimistic. Further, this makes sure not

to ignore the risks associated with a project’s costs (Harvard Business Review, 12/2004). Half

of the fleet size will be produced in 2028, the residual half in 2029.

Assumptions for Determining the Spot Price

In the following, the current value of the asset will be determined based on various assumptions.

These are based on the Tesla Autonomy Day video as well Tesla Autonomy Day, YouTube 04/2019

starting at 3:06:00).

Figure 31: PV of net cash flows from taking the project now (in USDm)

FY 2030E FY 2031E FY 2032E FY 2033E FY 2034E FY 2035E

Revenues 12,000 11,200 10,400 9,600 8,800 8,000

Costs:

R&D expenses 500 500 500 500 500 500

Manufacturing costs

Gigafactory costs

Supercharger stations

other costs

maintenance costs 200 200 200 200 200

Total costs: 500 700 700 700 700 700

Operating earnings: 11,000 9,800 9,000 8,200 7,400 6,600

Net Profit: 8,383 7,469 6,859 6,249 5,640 5,030

PV 4,036 3,365 2,892 2,465 2,082 1,737



Annual gross profit per robotaxi: The annual gross profit is stated to be around ≈$30,000

per robotaxi at 50% utility. This is a reliable assumption by Tesla, hence the gross profit

of one robotaxi is projected to be ≈$30,000 in this model. However, from 2031 the gross

profit per robotaxi is expected to decline by $2,000 annually due to increasing

competitors. The decline will continue until it reaches a steady state at an annual gross

profit of $20,000.

Maintenance costs: The annual maintenance costs are expected to be $500 per robotaxi,

summing up to a total of $200m annually.

Net profit: Operating earnings will be taxed with marginal tax rate of 23,79%.

Perpetuity: This project is considered to operate infinitely, hence the last net profit will be

treated a perpetuity.

Calculating Option Value for Robotaxi Project

Based on the assumptions above the DCF analysis leads to the following output.

Figure 32: DCF output for robotaxi project (in USDm)

Since all components of the Black-Scholes model are determined, the value of the option can be

determined. This will be done by inserting the output into Damodaran’s template for valuing a project

as an option (Damodaran Spreadsheets, 2020). In doing so, the value of the project is $42.1bn

(Appendix 13). Further, the spot price being higher than the exercise price shows that this option is

already in the money. The computed $42.1bn can be added to the equity value determined through

the DCF model. Hence, Tesla’s market capitalization would account to $338.5bn or a share price of

$1,870 as of 31st December 2019.

Output

Exercise price -14,084

Terminal value at 2035 113,111

PV of TV at 2020 36,556

Spot price at 2020 53,133

Chapter 11: Conclusive Summary 74

11. Conclusive Summary

This paper sought to examine whether Tesla’s high share price ($418) and market cap ($75.7bn) as

of 31st December 2019 is based on fundamentals by applying a DCF analysis and a ROV. As Tesla

has many characteristics being typical for growth companies such as negative operating income, a

negative return on equity and high investments, a ROV had to be conducted in addition to a DCF.

This is because in some cases traditional DCF valuation approaches tend to underestimate or even

ignore the value of an asset, especially if options are embedded in it. Tesla has been able to disrupt

the market with its product announcements and product launches over and over, making it necessary

to identify real options for Tesla and valuing it.

Tesla’s growth depends on macroeconomic factors, such as the GDP development as this is highly

correlated with the sales of cars. Further, the launch of Model 3 & Y that are considered a mass

volume product will be a crucial contributing factor for Tesla’s positioning in the automotive market

because achieving scale and scope effects are pivotal to become profitable. With the new locations

for its production plants in Shanghai and Berlin, Tesla made the right step and increased its

geographical footprint. However, realizing its targets such as launching the Semi, Cybertruck and the

new Roadster will require massive investments. In order to keep its competitive advantages, such as

the battery range, overall car performance and the Supercharger network, as well as having

remarkably lower battery costs per kWh, Tesla has to stay innovative as the well-establish players

such as BMW, VW and Daimler are gradually entering the electric vehicle market.

Conducting the DCF based on management guidance and historical performances, a share price of

$1,638 as of 31st December 2019 was computed. This is a lot higher than Tesla closed on that day,

$418, indicating a huge upside potential for Tesla shares. However, the sensitivity analysis showed

that the share price is highly sensitive to even small changes in the WACC. Considering the base case

(TGR 2.32%), an increase of 0.75%-2.25% in the WACC leads to a share price drop of ≈$300-$700.

At the same time, with a decrease of 0.75%-2.25% in the WACC an increase of ≈$400-$2,200 in the

share price can be observed. In addition, the real option valuation based on the robotaxis project

would add $42.1bn to the equity value, leading to a share price of $1,870 or a total market

capitalization of $338.5bn as of 31st December 2019. While the computed share price –even without

the option value– seems to be very high, the current share price (07/2020) provides validity.

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https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/reboost-a-comprehensive-view-on-the-changing-powertrain-component-market-and-how-suppliers-can-succeed



https://www.mobilityhouse.com/int_en/knowledge-center/charging-time-summary

https://www.nasdaq.com/market-activity/stocks/tsla

https://www.pwc.com/us/en/industrial-products/publications/assets/pwc-global-auto-supplier-consolidation-study-2019.pdf

https://www.pwc.com/us/en/industrial-products/publications/assets/pwc-global-auto-supplier-consolidation-study-2019.pdf

https://www.reuters.com/companies/TSLA.O/key-metrics

https://www.rundschau-online.de/region/koeln/carsharing-anbieter--drive-now--startet-in-koeln-5384764

https://www.rundschau-online.de/region/koeln/carsharing-anbieter--drive-now--startet-in-koeln-5384764

https://www.spglobal.com/marketintelligence/en/news-insights/trending/6o5guvhjyxdmekfqa0t2mw2

https://www.spglobal.com/marketintelligence/en/news-insights/trending/6o5guvhjyxdmekfqa0t2mw2

https://www.supplychaindive.com/news/Tesla-3-supply-chain-Elon-Musk-production/448287/

https://www.supplychaindive.com/news/Tesla-3-supply-chain-Elon-Musk-production/448287/

https://www.tesla.com/about

https://www.tesla.com/autopilot

Bibliography 80

https://www.tesla.com/blog/secret-tesla-motors-master-plan-just-between-you-and-me


https://www.teslarati.com/tesla-glencore-cobalt-deal-gigafactory-shanghai-berlin/

www.bmw.de

https://www.tesla.com/blog/secret-tesla-motors-master-plan-just-between-you-and-me


https://www.teslarati.com/tesla-glencore-cobalt-deal-gigafactory-shanghai-berlin/

http://www.bmw.de/

Appendix 81

Appendix

Appendix 1: Global consumer powertrain technology preferences over the next 5 years .............................. 82

Appendix 2: CAPEX / Automotive sales ratio 2017-2019 .............................................................................. 83

Appendix 3: Analytical income statement ....................................................................................................... 84

Appendix 4: Analytical balance sheet ............................................................................................................. 85

Appendix 5: Short-term liquidity risk ............................................................................................................. 86

Appendix 6: Real GDP long-term growth rate – World .................................................................................. 87

Appendix 7: Covid-19 effect on production capacity ...................................................................................... 88

Appendix 8: Average price calculations for each model ................................................................................. 89

Appendix 9: Projected income statement ........................................................................................................ 90

Appendix 10: Tesla – Historical debt-to-EV ratio ........................................................................................... 91

Appendix 11: Historical & projected △NWC calculations ............................................................................. 92

Appendix 12: Level 5 autonomy readiness according to U.S. government executives ................................... 93

Appendix 13: Option valuation spread sheet – Damodaran template ............................................................. 94

Appendix 82

Appendix 1: Global consumer powertrain technology preferences over the next 5 years

KPMG Global Automotive Executive Survey 2019, p. 20

Appendix 83

Appendix 2: CAPEX / Automotive sales ratio 2017-2019

Compiled by author

2017 2018 2019

CAPEX (based on quarterly reports) 3,415 2,101 1,327

Automotive sales revenue 8,535 17,632 19,952

CAPEX/Automotive sales ratio 40% 12% 7%

Appendix 84

Appendix 3: Analytical income statement

Compiled by author

USDm 2016 2017 2018 2019

Revenues

Automotive sales 5,589 8,535 17,632 19,952

Automotive leasing 762 1,107 883 869

Energy generation and storage 181 1,116 1,555 1,531

Services and other 468 1,001 1,391 2,226

Total Revenues 7,000 11,759 21,461 24,578

Cost of revenues

Automotive sales -4,268 -6,725 -13,686 -15,939

Automotive leasing -482 -708 -488 -459

Energy generation and storage -178 -874 -1,365 -1,341

Services and other -472 -1,229 -1,880 -2,770

Total cost of revenues -5,400 -9,536 -17,419 -20,509

Depreciation 947 1,636 1,901 2,154

Gross Profit 2,547 3,859 5,943 6,223

Operating expenses

Research & development -834 -1,378 -1,460 -1,343

Selling, general and administrative (SG&A) -1,432 -2,477 -2,835 -2,646

Total operating expenses -2,266 -3,855 -4,295 -3,989

EBITDA 281 4 1,648 2,234

Depreciation & amortization -947 -1,636 -1,901 -2,154

EBIT -666 -1,632 -253 80

Interest income 9 19 24 44

Interest expense -199 -471 -663 -685

Other income (expense), net 111 -125 22 45

EBT -745 -2,209 -870 -516

Provision for income taxes -27 -32 -58 -110

Net earnings -772 -2,241 -928 -626

Appendix 85

Appendix 4: Analytical balance sheet

Compiled by author

Operational assets 2016 2017 2018 2019

PP&E 5,983 10,028 11,330 10,396

Intangible assets, net 376 362 282 339

Goodwill 0 60 68 198

Accounts receivable 499 515 949 1,324

Inventory 2,067 2,264 3,113 3,552

Other assets 216 273 572 808

Operating lease vehicles, net 3,134 4,117 2,090 2,447

Solar energy systems, net 5,922 6,347 6,271 6,138

Prepaid expenses and other current assets 194 268 366 713

Operating lease right-of-use assets 0 0 0 1,218

MyPower customer notes receivable, net of current portion 506 457 422 393

Total operational asset 18,897 24,691 25,463 27,526

Operational liabilities

Accounts payable 1,860 2,390 3,405 3,771

Accrued liabilities 1,210 1,732 2,094 2,905

Customer deposits 664 854 793 726

Resale value guarantee 180 787 503 317

Other long-term liabilities 1,891 2,443 2,710 2,655

Total operational liabilities 5,805 8,206 9,505 10,374

Invested Capital 13,092 16,485 15,958 17,152

Financial liabilities

short-term

Deferred revenue, current 763 1,015 630 1,163

Convertible senior notes 10 0 0 0

Current portion of debt and finance leases 984 797 2,568 1,785

Convertible senior notes issued to related parties 10 3 0 0

Current portion of promissory notes issued to related parties 166 100 0 0

Total short-term financial liabilities 1,933 1,915 3,198 2,948

long-term

Deferred revenue, net of current portion 852 1,178 991 1,207

Debt and finance leases, net of current portion 5,860 9,416 9,404 11,634

Solar bonds issued to related parties, net of current portion 99 0 0 0

Resale value guarantees, net of current portion 2,211 2,309 329 36

Redeemable noncontrolling interests in subsidiaries 367 398 556 643

Total long-term financial liabilities 9,389 13,301 11,280 13,520

Total liabilities 11,322 15,216 14,478 16,468

Financial assets

Cash & cash equivalents 3,393 3,368 3,686 6,268

Restricted cash 106 155 193 246

Restricted cash, net of current portion 268 442 398 269

Total financial assets 3,767 3,965 4,277 6,783

Net-interest bearing liabilities (NIBL) 7,555 11,251 10,201 9,685

Total stockholder's equity 5,537 5,234 5,757 7,467

Invested capital (NIBL + equity) 13,092 16,485 15,958 17,152

Appendix 86

Appendix 5: Short-term liquidity risk

Compiled by author

USDm 2016 2017 2018 2019

Assets

Current assets

Cash and cash equivalents 3,393 3,368 3,686 6,268

Restricted cash 246 246 246 246

Accounts receivable, net 499 515 949 1,324

Inventory 2,067 2,264 3,113 3,552

Prepaid expenses and other current assets 194 268 366 713

Total current assets 6,399 6,661 8,360 12,103

Liabilities

Current liabilities

Accounts payable 1,860 2,390 3,405 3,771

Accrued liabilities and other 1,210 1,732 2,094 2,905

Deferred revenue 763 1,015 630 1,163

Resale value guarantees 180 787 503 317


Current portion of debt and finance leases 984 797 2,568 1,785

Current portion of promissory notes issued to related parties 166 100

Total current liabilities 5,827 7,675 9,993 10,667

Total current assets 6,399 6,661 8,360 12,103


Short-Term Liquidity Risk 1.1 0.9 0.8 1.1

Appendix 87

Appendix 6: Real GDP long-term growth rate – World

OECD, 2020, compiled by author

TIME GDP

2026 123,158,600 2026 123,158,600

2027 126,660,500 2060 267,676,800

2028 130,211,500

2029 133,809,400 CAGR 2.32%

2030 137,451,300

2031 141,134,700

2032 144,854,900

2033 148,609,900

2034 152,396,600

2035 156,212,100

2036 160,055,300

2037 163,927,700

2038 167,831,600

2039 171,768,800

2040 175,741,200

2041 179,751,800

2042 183,803,500

2043 187,900,500

2044 192,046,000

2045 196,242,100

2046 200,491,500

2047 204,800,800

2048 209,175,500

2049 213,620,100

2050 218,138,100

2051 222,732,700

2052 227,400,500

2053 232,143,700

2054 236,962,300

2055 241,856,500

2056 246,828,200

2057 251,890,500

2058 257,049,600

2059 262,310,300

2060 267,676,800

Appendix 88

Appendix 7: Covid-19 effect on production capacity

Compiled by author

Shanghai production capacity/week production decrease due to Covid-19

till May 2020 3,000 cars/week1.5 week shutdown;

4,500 fewer vehicles were produced

from June 2020 4,000 cars/week –

from January 2021, including Model Y 4,000 cars/week

from January 2022 5,000 cars/week

Fremont production capacity/week production decrease due to Covid-19

Model S & X 1,800 cars/week6 weeks closed;

10,800 fewer Model S & X were produced

Model 3 & Y 8,000 cars/week6 weeks closed;

4,800 fewer Model 3 & Y were produced

Appendix 89

Appendix 8: Average price calculations for each model

Tesla, 2020, compiled by author

Average price calculations

69,490

89,490

Average price 79,490

74,690

94,690


31,690

40,690

48,690


46,690

54,690


150,000

180,000


39,900

49,900

69,900


Cybertruck

Model 3

Model S

Model X

Model Y

Tesla Semi

Appendix 90

Appendix 9: Projected income statement

Compiled by author

USDm

Historical

Average FY 2020E FY 2021E FY 2022E FY 2023E FY 2024E FY 2025E FY 2026E

Revenues

Automotive sales 18,077 36,509 73,650 80,933 91,525 96,056 102,849

Growth % 57% -9% 102% 102% 10% 13% 5% 7%

Automotive leasing 826 867 997 1,146 1,318 1,516 1,743

Growth % 8% -5% 5% 15% 15% 15% 15% 15%

Total automotive revenues 18,902 37,376 74,647 82,079 92,843 97,572 104,593

Growth % 52% -9% 98% 100% 10% 13% 5% 7%

Energy generation and storage 1,914 2,392 2,990 3,738 4,672 5,840 7,300

Growth % 185% 25% 25% 25% 25% 25% 25% 25%

Services and other 2,337 3,038 4,558 5,469 6,563 7,876 9,451

Growth % 71% 5% 30% 50% 20% 20% 20% 20%

Total revenues 23,153 42,806 82,195 91,286 104,079 111,288 121,344

55% -6% 85% 92% 11% 14% 7% 9%

Cost of revenues

Automotive sales 13,738 29,207 58,920 63,128 69,559 71,081 74,051

margin % 78% 76% 80% 80% 78% 76% 74% 72%

Automotive leasing 454 477 548 631 725 834 959

margin % 57% 55% 55% 55% 55% 55% 55% 55%

Total automotive cost of revenues 14,192 29,684 59,469 63,758 70,284 71,915 75,010

margin % 77% 75% 79% 80% 78% 76% 74% 72%

Energy generation and storage 1,722 2,105 2,572 3,140 3,831 4,672 5,694

margin % 87% 90% 88% 86% 84% 82% 80% 78%

Services and other 2,781 3,464 5,424 6,235 7,154 8,191 9,356

margin % 125% 119% 114% 119% 114% 109% 104% 99%

Total cost of revenues 18,696 35,253 67,464 73,133 81,269 84,778 90,061

margin % 81% 81% 82% 82% 80% 78% 76% 74%

Gross profit 4,457 7,553 14,731 18,153 22,810 26,510 31,283

margin % 19% 19% 18% 18% 20% 22% 24% 26%

Operating expenses

Research and development 1,389 2,140 1,644 1,369 1,041 1,113 1,213

as of Revenue in % 7% 6% 5% 2% 1.5% 1% 1% 1%

Selling, general and administrative 2,778 3,425 3,288 1,826 2,082 1,113 1,213

as of Total Revenues in % 14% 12% 8% 4% 2% 2% 1% 1%

Total operating expenses 4,168 5,565 4,932 3,195 3,122 2,226 2,427

Operating earnings 290 1,989 9,800 14,958 19,687 24,284 28,856

Appendix 91

Appendix 10: Tesla – Historical debt-to-EV ratio

Yahoo Finance Market Capitalization Data, 2020

NIBL/(NIBL+Equity) 2017 2018 2019

NIBL 11251 10201 9685

Market Capitalization as of 31th December 52300 57200 75700

Enterprise Value (EV) 63551 67401 85385

NIBL/EV 18% 15% 11%

Appendix 92

Appendix 11: Historical & projected △NWC calculations

Compiled by author

2016 2017 2018 2019

Currents assets

Acc receivable 499 515 949 1,324

Inventory 2,067 2,264 3,113 3,552

Prepaid expenses

and other assets194 268 366 713

Total current asset 2,760 3,047 4,428 5,589

Current liabilities

Acc payable 1,860 2,390 3,405 3,771

Accrued liabilities

and other1,210 1,732 2,094 2,905

Deferred revenue 763 1,015 630 1,163

Resale value guarantees 180 787 503 317



NWC -1,917 -3,731 -2,997 -3,293

△ NWC -1,814 734 -296

FY 2020E FY 2021E FY 2022E FY 2023E FY 2024E FY 2025E FY 2026E

Total current asset 5,325 9,845 19,727 21,909 26,020 27,822 31,549

Total current liabilities 8,104 14,982 27,946 31,037 34,346 36,725 38,830

NWC -2,778 -5,137 -8,220 -9,129 -8,326 -8,903 -7,281

△ NWC 515 -2,358 -3,083 -909 802 -577 1,622

Appendix 93

Appendix 12: Level 5 autonomy readiness according to U.S. government executives

KPMG Global Automotive Executive Survey 2020

Appendix 94

Appendix 13: Option valuation spread sheet – Damodaran template

http://www.stern.nyu.edu/~adamodar/pc/project.xls

VALUING A PRODUCT PATENT/PROJECT AS AN OPTION

This program calculates the value of a product patent or

a project as an option.

Assumptions

1. All the assumptions underlying the Black-Scholes model apply

2. The current value of the project and the variance in this value are known.

The user has to input the following variables

1. Present value of net cashflows from taking project now.

2. Variance in the present value, as a function of environmental and technical changes.

3. Present value of the cost of developing the product/project for commerical use.

4. Riskless interest rate that corresponds to length of the product patent.

5. Length of the product patent / rights to the project.

6. Expected annual after-tax cashflow from project after it is developed.

Inputs relating the underlying asset

Enter the present value of net cashflows from taking project now = $53.1

Enter the standard deviation in the present value of project cashflows =20.23%

Inputs relating to the option

Enter the present value of the cost of developing product/project = $14.1 (in currency)

Enter the life of the product patent / project rights = 10 (in years)

your cash flows will decline proportionately (1/remaining life of the patent)

Do you want to change this default? No

If so, enter the expected annual cost of delaying investment (as % of value)

General Inputs

Enter the riskless rate that corresponds to the option lifetime = 2.41%

VALUING A LONG TERM OPTION/WARRANT

Stock Price= $53.1 T.Bond rate= 2.41%

Strike Price= $14.1 Variance= 0.04092529

Expiration (in years) = 10 Annualized dividend yield= 0.00%

d1 = 2.769343294

N(d1) = 0.997191529

d2 = 2.129614523

N(d2) = 0.983398274

Value of the product patent/project right = $42.1

As a default, we will assume that you if you do not invest in the project once it

becomes viable, you will lose one year of protection and that

Documents

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