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Introducing the leader
National Research UniversityHigher School of Economics
Prepared by:Sergey Stepanov
Vladimir SeleznevVyacheslav KabaevSofya Kondratyeva
Vitaly Pentegov
| 2
DISCLOSURES:
Ownership and material conflicts of interest:The author(s), or a member of their household, of this report does not hold a financial interest in the securities of this company.The author(s), or a member of their household, of this report does not know of the existence of any conflicts of interest that might bias the content or publication of this report. Receipt of compensation:Compensation of the author(s) of this report is not based on investment banking revenue.Position as a officer or director:The author(s), or a member of their household, does not serve as an officer, director or advisory board member of the subject company.Market making:The author(s) does not act as a market maker in the subject company’s securities.Disclaimer:The information set forth herein has been obtained or derived from sources generally available to the public and believed by the author(s) to be reliable, but the author(s) does not make any representation or warranty, express or implied, as to its accuracy or completeness. The information is not intended to be used as the basis of any investment decisions by any person or entity. This information does not constitute investment advice, nor is it an offer or a solicitation of an offer to buy or sell any security. This report should not be considered to be a recommendation by any individual affiliated with CFA Association (Russia), CFA Institute or the CFA Institute Research Challenge with regard to this company’s stock.
CFA Institute Research Challenge
Business Description
Macroeconomic Environment
Competitive Positioning
Financial Analysis
Valuation
Investment Risks
Investment Summary
Appendix
Contents
3 Higher School of Economics 2016
0
2000
4000
6000
8000
10000
12000
Jan-10 Jan-11 Jan-12 Jan-13 Jan-14 Jan-15 Jan-16
Strong business with temporary volatile stock
4 Higher School of Economics 2016Sources: Bloomberg, Thomson Reuters, team estimates
Recommendationfor MGNT:ME
HOLD
Target Price: RUB 12,001
Upside: 16%
Investment Highlights
#1 retail chain in Russia by market cap, number of stores, revenue and earnings
Profitable, cash flow generating company
Successfully developing in difficult macroeconomic environment
12,001
Dec-16
RU
B p
er s
ha
re
10,320
MGNT:ME – ticket for Magnit local shares trading on the Moscow Stock Exchange (MOEX)
MGNT:LI – ticket for Magnit GDRs trading on the London Stock Exchange (LSE)
Sources: Thomson Reuters, MOEX, LSE, Company data, team estimates
Inclusion in indexes provides additional demand from passive investors 2
in MICEX & RTS
in MSCI Russia8%
6%
Weights in indexes**
The highest share of foreign investments among Russian stocks
One of the most attractive company in Russia’s stock universe
5
Market capitalization
Closing Price
Target Price
52-week High/Low
ADTV (3M),shares
Std Dev (1M)
SharesOutstanding
Free-float
EV/EBITDA
P/E
Market Profile*
RUB 10,320
RUB 12,944/9,251
153,862
94.6 mln
RUB 1 trn
25.9%
18.2x
10.8x
* as of 8th of April 2016
MOEX LSE (GDRs)
29.9%
USD 19 bln
USD 39
USD 30/62
177,086
22.1x
11.7x
RUB 12,001 USD 36
1 Share=5 GDRs
Higher School of Economics 2016
** MICEX – RUB index including 50 most liquid Russian companies, RTS – USD index
22.2% 43.0%
1
Magnit GDRs are trading at a premium to the local shares3
Due to lower liquidity on MOEX in comparison with LSE
0
20
40
60
MGNT:LI MGNT**
USD
$6 average premium through 2009-2015
MGNT**– implied price for Magnit GDRs, calculated as local share price divided by 5 and converted into USD
NorthCaucasian
South
Volga
Siberia
Central
Ural
NorthWest
2,361
#1 food retail chain in Russia
Sources: Bloomberg, Company data
Cities & Towns
7 FederalDistricts
Convenience Stores
Hypermarkets
Magnit Family
Drogerie stores(Cosmetics)
9,594
219
155
2,121
12,089 RetailStores
74%
17%
5%
4%
948804
270 253163
Magnit X5 Dixy Lenta O'key
4.4
3.3
0.9 0.90.6
Magnit X5 Lenta O'Key Dixy
Revenues of top 5 retailers in 2015
Selling space in 2015 (mln sq.m.)Number of stores Revenue share
(RUB bln)
Profitability
6
10%
15%
12%
18%
Higher School of Economics 2016
Sources: Company data
5,882 Trucks
1.29 mln sq.m.
The biggest fleet in Europe
Centralization Degree
90% for
Convenience Stores
73% for
Hypermarkets
Warehouse Space
596 SKUs
11%
Distribution Centers34
Share of Revenue in 2015
Private Label
Logistic system
Private Label & Own production
Own Production
83 ha
Biggest greenhouse in Eastern Europe
37%Coverage ofMagnit’s sales of vegetables
The most developed logistic system in Russia with efficient centralization strategy1
Private label of Magnit covers significant share of revenue2
Success based on efficient vertical integration
7 Higher School of Economics 2016
The main shareholder of the company is the CEO maintaining strong corporate governance1
Board of directors serves shareholders’ interests 2
London
Stock Exchange
29.9%
Moscow
Stock Exchange
Sergey Galitskiy, CEO
Minority investors
Free-float
25.9%
55.8%
{
35.1%
9.1%
One of the most attractive company in Russia’s stock universe
8
April, 2006
April, 2008
IPO on RTS & MICEXAttracted RUB 9,5 bln,
SPO on LSEAttracted USD 480 mln
11 members
5 Executive Directors
6 Non-Executive Directors (3 independent) International experience
Effective risk-management
Strong ethics SergeyGalitskiy,CEO
MagnitPJSC
“Russian leaders in corporate governance.”
“TOP-1000 Russian managers”
“CEO of the year”
“Company with the best corporate governance” 3 HR and Remuneration Committee
3 Audit Committee
Higher School of Economics 2016Sources: Company data, Thomson Reuters, Forbes, Kommersant
1.3% 0.6% -3.7% -1.5% 1.0%
6.5%
11.4%12.9%
8.6%7.0%
2013 2014 2015 2016F 2017F
Real GDP growth CPI
High correlation of real wages with retail turnover ensures retail rebound when macroeconomic condition improves
As a result we see leap in prices and recession1
3
7-Apr-1612-Apr-14
$107 $41
₽69₽34
2Fall in oil prices led to ruble depreciation and budget cut
31-Dec-16
$40-50
₽60-66
RUB/USD*
Brent, brl.
Sources: Tomson Reuters, Federal State Statistics Service, team estimates
Exchange quotes and Brent prices dynamics
Historical changes in retail sales and real wages
-13%
-8%
-3%
2%
7%
12%
Jan-11 Jun-11 Nov-11 Apr-12 Sep-12 Feb-13 Jul-13 Dec-13 May-14 Oct-14 Mar-15 Aug-15 Jan-16
Retail Sales, y/y, % Real Wages, y/y, %
2%Forecast of y/y real wages growth since 2017
92%Correlation between real wages & retail sales
Turbulent macroeconomic environment affects retail
9 Higher School of Economics 2016
* CFA Institute notation for foreign exchange quotes
88%
84%
78%
72%
68%
64%
62%
52%
41%
Germany
US
Japan
Poland
Russia (2020)
China
Russia (2015)
Brazil
Turkey
72% 68%
46% 42%30%
20%12%
Germany CzechRepublic
Poland US Russia (2020) Russia Turkey
Consolidation is the ongoing trend 3
Sources: Euromonitor, Federal State Statistics Service, team estimates
Modern retail penetration will increase1 2 Small urban areas are the future growth driver
18%
62%
28%
77%
9%
30%
0%
20%
40%
60%
80%
2004 2006 2008 2010 2012 2014
Overall RussiaBig cities (>1mn)Small towns (<100k)
4 Regulation changes are manageable
- From 10% to 3%
Decreasing rebates
Shortening payables periods, days:
- Perishable goods: from 10 to 5
- More than 1 month storage life: from 30 to 20
- Other: from 45 to 35
Modern retail penetration by country Evolution of modern retail penetration
Market share of top 5 retailers
Room for modern retail growth still exists
10 Higher School of Economics 2016
21%
14%
6%12%
22%
Magnit Dixy Lenta X5 Retail Group O'key
Selling space expansion is the main source of revenue growth for Magnit
1 Magnit is the leader in the segment 2 Convenience format grows most rapidly2
2 4
11.6%14.5%
23.8%
Supermarkets Hypermarkets Convenience Stores
Sources: Euromonitor, Company data
3 Magnit targets small towns due to low competition
Market shares of Russian peers in 2015 Industry sales by channel: 2010-2015 CAGR
Selling space dynamics: 2010-2015 CAGR
Revenue dynamics: 2010-2015 CAGR
26% 26% 23%
15%12%
Magnit Dixy Lenta X5 Retail Group O'key
65% 35%
Location of stores by area type
Magnit is the leader in the low cost segment
11
Magnit7%
X56%
Dixy2%
Lenta2%
O'key1%
Other82%
Higher School of Economics 2016
Towns(population <500k)
Cities(population
>500k)
-7.1%
-3.8%
-0.7%
2.0% 2.0%
1 Magnit underperforms in LFL indicators
Sources: Infoline, Company data
3 Magnit’s logistics is essential for cost reduction and expansion
Avoiding drawbacks of ruble depreciation
Independence from suppliers
90%
7
5,882
34
MagnitDixy
X5
O’Key
Lenta
Like-for-Like traffic change in the industry (2015)
Current difficulties are alleviated by competitive advantages
12
<1 day
Drogerie (cosmetics) format is an opportunity222
Own production helps to cope with instabilities 4
1.5% of sales generated by produced vegetables
50 bln RUB
to be invested within 5 years
154% CAGRof revenues through
2011-2015
1.5 RUB trnmarket size
9.6%
15.0%
11.6%
18.1%
Convenience stores
Hypermarkets
Magnit Family
Cosmetics stores
EBITDA margin by formats in 2015
Higher School of Economics 2016
Share of direct supplies
Time between order and delivery
Federal Districts
Trucks
Distribution centers
10.9% 11.2%
7.2%6.5%
4.8%6.0%
4.1%
2.2%1.4%
0.2%
Magnit Lenta X5 O'Key Dixy
8.2%
10.9%12.2%
3.7%
6.0%7.3%
2011 2015 2020FEBITDA margin Net margin
Sources: Company data, team estimates
Magnit’s margins dynamics
EBITDA and Net Income margins in 2015 (comparison with local peers)
Magnit has sound margins with potential to grow
13
Vertical integration
Strong bargaining power with suppliers
Highly profitable Cosmetic stores
Private label development
Higher School of Economics 2016
-0.5
0.0
0.5
1.0
1.5
-50
0
50
100
150
2011 2012 2013 2014 2015E 2016F 2017F 2018F 2019F 2020F
FCFF, RUB bln (lhs) Net debt / EBITDA (rhs)
Increasing shareholders’ return
2
Sources: Company data, team estimates
Large revenues with decelerating growth1
0
600
1200
1800
2400
2013 2014 2015E 2016F 2017F 2018F 2019F 2020F
Growing cash flows3
x
x
x
x
x
Revenue dynamics (RUB bln)
0.4%
3.3%
12.2%
8%
63%
50%
0%
20%
40%
60%
0%
4%
8%
12%
2011 2014 2020FDividend yield (lhs) Payout ratio (rhs)
-
7,000
14,000
21,000
28,000
2011 2012 2013 2014 2015E 2016F 2017F 2018F 2019F 2020F
Selling space expansion (‘000 sq.m.)
In the long-run growth of selling space will also slow down
The company is turning into a cash cow
4
17 Higher School of Economics 2016
Sources: Company data, Bloomberg, team estimates
DCF provides sound economic basis for Magnit valuation
15
Target price of RUB 12,001 doesn’t indicate significant upside as well as downside
Lack of direct peers in Russia due to Magnit’s unique
developed business model and strong corporate governance
Target Price: RUB 12,001
Upside: 16%
Total Upside*: 18.1%
* Including:Annualized HPR andforecasted dividend yield
DCF ValuationRecommendation is
based 100% on Intrinsic Value
3,306 8,243EV/EBITDA 2016F
5,341P/E 2016F 8,749
9,801 15,620DCF
5,250 10,875PEG 2016F
9,251 12,37152 Week range
4,000 8,000 12,000 16,000
Current priceRUB 10,320
Target priceRUB 12,001
No reliable peers
Lack of international peers due to different economic
environment and the competitive landscape
Relative valuation
underestimates target price
Football field valuation graph (RUB)
Higher School of Economics 2016
-5.0E-06
4.5E-05
9.5E-05
1.5E-04
2.0E-04
2.5E-04
Despite huge CapEx, FCFF is significant and will grow further
Sources: Company data, Bloomberg, Damodaran, team estimates
WACC Calculation
Target capital structureDebt-to-Total Capitalization 0.10Equity-to-Total Capitalization 0.90
Cost of DebtCost of Debt 10.7%Effective Tax Rate 23.1%After-tax Cost of Debt 8.2%
Cost of Equity in RUBCost of Equity 17.5%
WACC in RUB (forecast period) 16.6%WACC in RUB (terminal period) 14.6%21
41
62
91
123
2016F 2017F 2018F 2019F 2020F
Terminal Period GrowthInflation in the long-run 5.3%Real GDP sustainable growth 1.1%
Growth rate 6.4%
Monte Carlo simulation confirms HOLD recommendation
FCFF dynamics (RUB bln)
Inputs to simulation
1. Revenue growth rate
2. EBITDA margin
6. Terminal growth3. CapEx
4. dNWC
5. WACC
Simulation statisticsMean RUB 12,095Std Dev RUB 1,6845th percentile RUB 9,405Median RUB 12,02895th percentile RUB 14,962
DCF valuation based on the moderately conservative assumptions
10,000 simulations
1
2
16 Higher School of Economics 2016
19% 41%40%
RUB 10,320 RUB 12,126Current price +17.5% Required Return
Sources: team estimates
New limiting amendments to the Trade Law
low
med
ium
hig
h
low medium high
Further fall in real wages
Price war
Reaching the market share limit of 25%
Impact
Pro
bab
ility
Magnit faces mainly macroeconomic and regulatory risks
Stress Test
17 Higher School of Economics 2016
Price war
Increase in non-core operations
Lowering efficiency due to significant
increase in non-core operations
Negative impact on margins due to:-lowering operational efficiency-lower than expected economies of scale
Target price range: RUB 9 820 – 11 245
Ticket Sales Net Income CapEx
Further fall in real wages
Target price range: RUB 8 768 – 10 153
Ticket &Traffic Sales Net Income CapEx
Target price range: RUB 10 400 – 11 856
Risk Matrix
Sources: team estimates, Thomson Reuters
HOLD
Pros Cons
Profitable cash-generating company
Strong corporate governance
High stock market volatility
Country risks:- Economic sanctions- Poor macroeconomic environment
Liquid stock, which is included in several
indices (MSCI Russia and MICEX & RTS)
Exchange rate fluctuations (high impact for GDRs)
Great business but difficult market result in Hold
18 Higher School of Economics 2016
Current Price Target Price:
RUB 10 320
Upside:
RUB 12 001 16%
APPENDIX MENU
II. Business Overview:• Geographical Coverage & Logistics• Store formats description
Convenience | HypermarketMagnit Family | Drogerie
• Suppliers & Import• Private Label & Employees • Funding story ,Free-float & Shareholders• Company’s organization structure(2)• Board of directors
III. Macro & Competitive• Indicators of peer companies• LFL indicators by format• Revenue split, average checks and locations• Sales growth and food CPI• Economic growth by sector 2003-2013 • Dynamics of food and non-food retail growth • Brent prices versus USD/RUB exchange rate
I. Financial Statements:• Income statement• Balance sheet• Cash flow statement
IV. Financial Analysis• Key financial ratios• Working capital• Depreciation and amortization• DuPont analysis• Cost of sales and SG&A structure and dynamics• Bonds repayment
National Research UniversityHigher School of Economics
V. Valuation• Discounted Cash Flow Analysis• Cost of Equity and WACC• Enterprise Value and Implied Share Price• Trading Multiples Analysis• Trading Multiples Analysis (Local shares)• Trading Multiples Analysis (GDRs)• Peer Group Analysis (Russian retailers)• Peer Group Analysis (International retailers)• Revenue Calculations (Marginal Revenue)• Revenue Calculations (L-f-L forecasting)• Revenue Calculations (Regression Analysis)• Revenue Analysis
VI. Stock Analysis• Stock Correlation• Spread• GDRs return & RUB devaluation
APPENDIX
Financial Statements
Business Overview Appendix
Industry Analysis Appendix
Financial Analysis Appendix
Valuation Appendix
National Research University
Higher School of Economics
in RUB mln Historical Income Statement Projected Income Statement
Period Ending December 31 2011 2012 2013 2014 2015E 2016F 2017F 2018F 2019F 2020F
Revenue
Retail Revenue 335 700 448 661 579 695 763 527 947 801 1 135 605 1 337 271 1 561 825 1 793 345 2 040 752
y/y revenue growth, % 42.1% 33.6% 29.2% 31.7% 24.1% 19.8% 17.8% 16.8% 14.8% 13.8%
Cost of sales
Cost of goods sold (237 872) (308 662) (388 112) (510 150) (635 027) (777 889) (909 345) (1 054 232) (1 192 574) (1 336 692)
Transportation expenses (11 319) (13 975) (17 592) (20 730) (25 733) (31 797) (38 781) (46 855) (55 594) (65 304)
Less due to inventory shortage (4 845) (6 972) (8 718) (12 067) (14 410) (17 266) (20 332) (23 746) (27 266) (31 027)
Total Cost of sales (254 036) (329 609) (414 423) (542 947) (675 170) (826 952) (968 457) (1 124 833) (1 275 434) (1 433 024)
COGS as a % of revenue 75.7% 73.5% 71.5% 71.1% 71.2% 72.8% 72.4% 72.0% 71.1% 70.2%
Gross profit 81 663 119 052 165 272 220 581 272 631 308 653 368 814 436 993 517 911 607 728
Gross profit margin, % 24.3% 26.5% 28.5% 28.9% 28.8% 27.2% 27.6% 28.0% 28.9% 29.8%
Operating expenses
Selling expense (2 132) (2 479) (3 406) (6 262) (7 773) (9 313) (11 367) (13 276) (16 140) (18 367)
Selling as a % of revenue 0.6% 0.6% 0.6% 0.8% 0.8% 0.8% 0.9% 0.9% 0.9% 0.9%
General & Administrative expenses (41 448) (53 949) (75 196) (96 624) (123 000) (141 265) (161 661) (184 674) (207 043) (229 596)
G&A as % of revenue 15.8% 15.7% 17.0% 16.8% 13.0% 12.4% 12.1% 11.8% 11.5% 11.3%
Rent and utilities (11 742) (16 350) (23 129) (31 284) (40 970) (51 787) (64 338) (79 275) (96 032) (115 291)
Rent as % of revenue 3.5% 3.6% 4.0% 4.1% 4.3% 4.6% 4.8% 5.1% 5.4% 5.6%
Total Operating expense (55 322) (72 777) (101 730) (134 170) (171 743) (202 366) (237 366) (277 224) (319 215) (363 254)
OpEx as % of revenue 16.5% 16.2% 17.5% 17.6% 18.1% 17.8% 17.8% 17.8% 17.8% 17.8%
Other income, net 1 227 990 1 530 2 313 2 871 2 271 2 675 3 124 3 587 4 082
Other income, net as % of revenue 0.4% 0.2% 0.3% 0.3% 0.3% 0.2% 0.2% 0.2% 0.2% 0.2%
Foreign exchange gain(loss) 39 116 (351) (2 814) 0 - - - - -
EBITDA 27 608 47 381 64 721 85 910 103 759 108 558 134 123 162 892 202 282 248 556
EBITDA margin (%) 8.2% 10.6% 11.2% 11.3% 10.9% 9.6% 10.0% 10.4% 11.3% 12.2%
Depreciation and amortization (7 983) (11 270) (14 184) (17 610) (20 081) (24 768) (29 595) (34 567) (39 688) (44 963)
EBIT 19 624 36 111 50 537 68 300 83 678 83 790 104 528 128 326 162 595 203 593
EBIT margin (%) 6% 8% 9% 9% 9% 7% 8% 8% 9% 10%
Investment income 286 258 187 372 - - - - - -
Interest
Interest expense (loans) (2 124) (2 923) (2 771) (5 125) (8 004) (8 981) (9 583) (9 409) (8 135) (6 786)
Interest expense (bonds) (1 503) (1 478) (2 553) (1 906) (1 870) (5 293) (4 100) (2 935) (2 330) (2 330)
Interest expense (Finance Leases) (58) (12) (0) 0 0 0.0 0.0 0.0 0.0 0.0
Cost of qualifying asset 265 357 355 385 366 368.4 373.0 369.0 370.2 370.7
Net interest expense (3 420) (4 055) (4 969) (6 646) (9 508) (13 905) (13 310) (11 975) (10 095) (8 745)
EBT 16 490 32 313 45 754 62 027 74 169 69 886 91 218 116 351 152 499 194 848
EBT margin (%) 5% 7% 8% 8% 8% 6% 7% 7% 9% 10%
Income tax expense (4 186) (7 196) (10 134) (14 341) (17 148) (16 158) (21 090) (26 901) (35 258) (45 049)
Tax rate (%) 25% 22% 22% 23% 23% 23% 23% 23% 23% 23%
Net Income 12 304 25 117 35 620 47 686 57 021 53 728 70 128 89 450 117 241 149 799
Net income margin (%) 4% 6% 6% 6% 6% 5% 5% 6% 7% 7%
Earnings per share (EPS) 137.90 265.62 376.69 504.29 603.01 568.18 741.62 945.95 1239.85 1584.15
Average common shares outstanding, '000 89 220 94 561 94 561 94 561 94 561 94561 94561 94561 94561 94561
Sources: Company data, team estimates
Appendix 1: Income statement
21 Higher School of Economics 2016
in RUB mln Historical Income Statement Projected Income Statement
Period Ending December 31 2011 2012 2013 2014 2015E 2016F 2017F 2018F 2019F 2020F
Assets
Non-current assets
Property, plant and equipment, net 122 874 158 753 195 158 232 969 277 888 321 370 362 072 399 912 434 803 466 656
Investment property 0 329 325 600 600 600 600 600 600 600
Land lease rights 2 543 2 908 3 259 3 074 3 228 3 389 3 559 3 737 3 924 4 120
Intangible assets 285 523 740 905 1 356 1 885 2 281 2 760 3 339 4 040
Goodwill 0 0 1 367 1 367 1 367 1 367 1 367 1 367 1 367 1 367
Long-term financial assets 406 189 70 97 97 97 97 97 97 97
Total non-current assets 126 108 162 701 200 921 239 013 284 536 328 708 369 976 408 473 444 130 476 881
Current assets:
Inventories 29 144 41 026 56 095 81 476 89 078 110 609 131 294 149 614 167 614 181 277
Trades and other receivables 533 584 632 813 897 1 400 1 502 1 626 1 671 1 901
Advances paid 1 800 2 677 3 171 4 849 5 365 6 427 7 568 8 838 10 148 11 547
Prepaid expenses 380 182 252 243 329 388 390 456 437 498
Taxes receivable 39 29 28 69 0 0 0 0 0 0
Short-term financial assets 172 877 1 151 475 475 475 475 475 475 475
Income tax receivables 0 0 0 132 0 0 0 0 0 0
Cash and cash equivalents 17 205 12 453 5 931 17 692 18 075 10 072 12 994 16 719 20 232 36 147
Total current assets 49 274 57 827 67 260 105 749 114 219 129 371 154 223 177 728 200 576 231 845
Total assets 175 382 220 528 268 181 344 761 398 755 458 080 524 200 586 201 644 706 708 726
Equity and Liabilities
Equity attributable to equity holders of the parent
Share capital 0.9 0.9 0.9 0.9 1.0 1.0 1.0 1.0 1.0 1.0
Share premium 41 440 41 595 42 024 42 399 42 399 42 399 42 399 42 399 42398.776 42398.776
Treasury shares (145) (551) (123) (500) 0 0 0 0 0 0
Retained earnings 37 289 58 190 84 261 101 752 129 695 155 485 187 744 227 102 276 343 336 263
Total equity attributable to equity holders of parent 78 584 99 236 126 162 143 652 172 095 197 885 230 144 269 502 318 743 378 662
Non-controlling interest 111 0 0 0 0 0 0 0 0 0
Toatal equity 78 696 99 236 126 162 143 652 172 095 197 885 230 144 269 502 318 743 378 662
Non-current liabilities
Long-term borrowings and loans 45 850 38 247 37 442 44 410 52 000 54 600 56 238 62 340 59 843 50 745
Long-term obligations under finance leases 13 0 290 202 0 0 0 0 0 0
Deferred tax liability 4 155 6 159 8 173 10 416 10 720 11 022 11 137 11 268 11 412 11 568
Total non-current liabilities 50 018 44 406 45 904 55 028 62 720 65 622 67 375 73 608 71 255 62 313
Current liabilities
Trade and other payables 33 566 42 921 48 171 66 795 70 292 86 547 103 214 118 647 132 785 141 339
Accrued expenses 3 946 5 021 6 612 8 185 11 622 14 249 16 713 18 988 21 864 24 184
Taxes payable 2 467 3 731 4 629 5 386 6 145 7 242 8 353 9 521 10 703 11 942
Dividends payable 1 1 0 14 372 14 540 13 969 18 935 25 046 34 000 44 940
Income tax payable 501 91 295 0 0 0 0 0 0 0
Short-term advances received 0 0 88 88 0 0 0 0 0 0
Short-term obligations under finance leases 187 12 0 0 0 0 0 0 0 0
Short-term borrowings and loans 6 000 25 110 36 320 51 257 61 340 72 567 79 467 70 890 55 356 45 346
Total current liabilities 46 668 76 887 96 115 146 082 163 939 194 573 226 681 243 091 254 708 267 751
Total liabilities 96 686 121 293 142 018 201 110 226 659 260 195 294 056 316 699 325 963 330 064
Total liabilities & equity 175 382 220 528 268 181 344 761 398 755 458 080 524 200 586 201 644 706 708 726
Appendix 2: Balance sheet
Sources: Company data, team estimates 22 Higher School of Economics 2016
in RUB mln Historical Income Statement Projected Income Statement
Period Ending December 31 2011 2012 2013 2014 2015E 2016F 2017F 2018F 2019F 2020F
Cash flows from operating activities
Profit before income tax 16 490 32 313 45 754 62 027 74 169 69 886 91 218 116 351 152 499 194 848
Adjustments for: 0 0 0 0.2 0.2 0.2 0.2 0.1 0.1
Depreciation 7 822 11 025 13 890 17 264 20 081.3 24 767.8 29 594.8 34 566.8 39 687.8 44 962.5
Amortization 158 244 294 345 515.3 716.2 866.6 1 048.6 1 268.9 1 535.3
Finance costs 3 420 4 055 4 969 6 646 9 508 13 905 13 310 11 975 10 095 8 745
Investment income (286) (258) (187) (372) 0 0 0 0 0 0
Loss from disposal of property, plant and equipment 199 21 211 436 0 0 0 0 0 0
Loss from disposal of investment property 0 0 0 0 0 0 0 0 0 0
Revaluation of investment property 0 (100) 3 (275) 0 0 0 0 0 0
Bad debt provision (19) 123 71 113 140.5 168.4 198.3 231.6 265.9 302.6
Foreign exchange loss (39) (116) 351 2 814 0 0 0 0 0 0
Gain on disposal of subsidiary (478) 0 0 0 0 0 0 0 0 0
Working capital changes 5 984 (896) (8 163) (9 330) (437) (3 178) (1 687) (904) (1 138) (3 241)Cash generated from operations 33 252 46 413 57 195 79 669 103 978 106 265 133 501 163 269 202 679 247 153
Income tax paid (1 433) (5 601) (8 021) (12 525) (17 148) (16 158) (21 090) (26 901) (35 258) (45 049)
Interest paid 232 (4 378) (4 759) (6 807) (9 508) (13 905) (13 310) (11 975) (10 095) (8 745)
Interest received (3 474) 236 209 375 0 0 0 0 0
Net cash (used in)/generated from operating activities 28 576 36 670 44 624 60 711 77 321 76 203 99 100 124 393 157 325 193 358
Cash flows from investing activities
Purchase of property, plant and equipment (48 691) (47 310) (50 051) (55 712) (65 000.0) (68 250.0) (70 297.5) (72 406.4) (74 578.6) (76 816.0)
Purchase of ownership in a single asset entity (940) 0 0 0 0 0 0 0 0 0
Purchase of investment property 0 (395) 0 0 0 0 0 0 0 0
Purchase of intangible assets (222) (463) (442) (461) (1 044) (1 112) (1 346) (1 628) (1 970) (2 384)
Purchase of land lease rights (1 287) (506) (719) (224) (154) (161) (169) (178) (187) (196)
Proceeds from disposal of subsidiary 0 (111) 227 96 0 0 0 0 0 0
Proceeds from sale of property, plant and equipment 125 148 647 556 0 0 0 0 0 0
Proceeds from sale of land lease rights 293 864 0 4 0 0 0 0 0 0
Acquisition of subsidiaries 0 0 (1 717) 0 0 0 0 0 0 0
Loans provided (11 053) (6 142) (6 419) (19 659) 0 0 0 0 0 0
Loans repaid 11 410 5 676 6 241 20 304 0 0 0 0 0 0
Net cash used in investing activities (50 366) (48 241) (52 232) (55 094) (66 198) (69 523) (71 813) (74 213) (76 736) (79 396)
(21 790) (11 570) (7 608) 5 617 11 123 6 679 27 288 50 181 80 590 113 962
Cash flows from financing activities
Dividends paid (999) (4 216) (9 545) (15 825) (28 912) (28 510) (32 904) (43 981) (59 046) (78 939)
Shares issuance / (repurchase) 14 806 (250) 856 (2) 500 0 0 0 0 0
Cash Flow Avaliable for Debt Repayment (7 982) (16 036) (16 297) (10 210) (17 289) (21 830) (5 616) 6 200 21 544 35 023
Long-term debt issuance / (repayment) 0 (7 603) (805) 7 034 7 590 2 600 1 638 6 102 (2 497) (9 098)
Short-term debt issuance / (repayment) 21 750 19 074 10 593 14 937 10 083 11 227 6 900 (8 577) (15 534) (10 010)
Repayment of obligations under finance leases (604) (188) (13) (1) 0 0 0 0 0 0
Net cash from financing activities 34 953 6 818 1 087 6 143 (10 739) (14 683) (24 366) (46 456) (77 077) (98 047)
Net increase (decrease) in cash and cash equivalents 13 163 (4 753) (6 521) 11 760 384 (8 003) 2 922 3 725 3 513 15 915
Cash at the beginning of the year 4 042 17 205 12 453 5 931 17 691 18 075 10 072 12 994 16 719 20 232
Cash at the end of the year 17 206 12 453 5 931 17 691 18 075 10 072 12 994 16 719 20 232 36 147
Appendix 3: Cash flow statement
Sources: Company data, team estimates 23 Higher School of Economics 2016
National Research University
Higher School of Economics
APPENDIX
Financial Statements
Business Overview Appendix
Industry Analysis Appendix
Financial Analysis Appendix
Valuation Appendix
No share
<10%
10%-15%
15%-20%
>20%
Magnit’s market
share by regions
Appendix 4: Market share by regions
Sources: Company data, team estimates 25 Higher School of Economics 2016
Start: wholesale trading 1994-1998
• Sergey Galitskiy founded the company selling household
products
• Tander LLC became one of the leaders in distributing
cosmetics and household products in Russia
• Plan for retail expansion was created
1998-2001 Entering retail market
• The first retail store in Krasnodar
• Experiments with store formats
• Stores are combined in retail chain
Intensive growth
• 1500 stores at the end of 2005
• IFRS, strong financial control and motivation labor
system implementation
2001-2005
Appendix 5: Magnit’s History 1/2
Sources: Company data 26 Higher School of Economics 2016
2006-2009 IPO, SPO, Multiformat stores
• Russian retail leader by traffic
• IPO in 2006, SPO in 2008 and 2009
• Start of hypermarkets construction
• First non-executive director
• 3228 stores at the end of 2009
Firm position in retail sector
• First Drogerie store “Magnit Cosmetic”
• Market expansion: Ural and Siberia regions
• SPO in 2011 – $475 mln. attracted
• Value of stock traded at LSE is more than $21 bln.
• Start of vegetables cultivation
2010-2012
TODAY Magnit today
• Magnit is Russia's largest retail company in Russia
by market share, revenues, employees, earnings,
market capitalization, geographic coverage,
customers served operating 12089 retail stores in
over 2361 cities, supported by 33 distribution
centres and over 5882 trucks
Appendix 6: Magnit’s History 2/2
Sources: Company data 27 Higher School of Economics 2016
North
Caucasian
1 2
7
43
5
6
South
Volga
Siberia
Central
Ural
North
West
2,361 Cities
& Towns
7Federal
Regions
Convenience
Stores
Hypermarkets
Magnit Family
Drogerie Stores
Distribution
Centers (DCs)
9594
219
155
2121
33
1
2587 1648
336353936
2877
866
37 62 61
518 444 593
9 8 8
14 7 30 8
30 42 4911 6 9 8
205 85 200 76
2 1 3 2
12,089 Retail
Stores
5,882 Trucks
1,292 ‘000 m²
Centralization Ratio, %
Convenience Stores
From DC – 90
From supplier - 10
Hypermarkets
From DC – 73
From supplier - 27
Warehousing Space
2 3 4 5 6 7
Geographical Coverage
Logistics System
366
669
366
1428
2396
3101
3763Central
Volga
Southern
Urals
North Caucasus
North West
Siberia
Warehousing Space
4,414 ‘000 m²Selling Space
Appendix 7: Geographical coverage & Logistics
Sources: Company data, as of December 31, 2015 28 Higher School of Economics 2016
Convenience Stores
455 sq.m.Total
325 sq.m.Selling Space
89% Food
11% Non-food
25% Owned
75% Leased
Format Description Key Operational Statistics OpeningSize of the Store Average Ticket Payback
Store Ownership Structure
Sales Mix
Traffic
tickets/sq.m./day
Sales Density
sales/sq.m./year
LFL 12M2015 –12M2014,%
244,01P=$4,00
245 306P=$4 024
8,14 AverageTicket, RUB
-0,79 Traffic
7,29 Sales
2,8
3 years
If Leased
If Owned
Cost of New Store
per sq.m. of Total Space, ‘000 RUB
Time to Maturity
6 months
4-6 years
Owned 35 - 105
Leased 10 - 19
Number of SKUs
3 500
Appendix 8: Store formats description 1/4
29 Higher School of Economics 2016Sources: Company data, as of December 31, 2015
Hypermarket
80% Food
20% Non-food
75% Owned
25% Leased
Size of the Store Average Ticket
Store Ownership Structure
Sales Mix
Traffic
tickets/sq.m./day
Sales Density
sales/sq.m./year
LFL 12M2015 – 12M2014,%
614,3P=$10,1
272 278P=$4 467
1,2
6 615 sq.m.Total
2 918 sq.m.Selling Space
5,53 AverageTicket, RUB
-3,80 Traffic
1,51 Sales
Payback
6-9 years
Cost of New Store
per sq.m. of Total Space, ‘000 RUB
Owned 56-98
Leased 31-41
8-15 months
Time to Maturity
S: up to 3 000M: 3 000-6 000L: over 6 000
Number of SKUs
15 500 – 25 200
Format Description Key Operational Statistics Opening
Appendix 9: Store formats description 2/4
30 Higher School of Economics 2016Sources: Company data, as of December 31, 2015
Magnit Family
2 161 sq.m.Total
1 098 sq.m.Selling Space
85% Food
15% Non-food
36% Owned
64% Leased
Format Description Key Operational Statistics OpeningSize of the Store Average Ticket Payback
Store Ownership Structure
Sales Mix
Traffic
tickets/sq.m./day
Sales Density
sales/sq.m./year
LFL 12M2015 – 12M2014,%
446,9P=$7,3
349 703P=$5 737
2,0
6-9 years
Cost of New Store
per sq.m. of Total Space, ‘000 RUB
Owned 71-112
Leased 31-54
8-15 months
4,33 AverageTicket, RUB
-3,55 Traffic
0,62 Sales
Time to Maturity
Number of SKUs
8 800
Appendix 10: Store formats description 3/4
31 Higher School of Economics 2016Sources: Company data, as of December 31, 2015
Drogerie Stores
298 sq.m.Total
229 sq.m.Selling Space
100% Non-food
13% Owned
87% Leased
Format Description Key Operational Statistics OpeningSize of the Store Average Ticket Payback
Store Ownership Structure
Sales Mix
Traffic
tickets/sq.m./day
Sales Density
sales/sq.m./year
LFL 12M2015 – 12M2014,%
287,6P=$4,7
114 924P=$1 885
13,24 AverageTicket, RUB
5,62 Traffic
19,61 Sales
1,0
3 years
If Leased
If Owned
Cost of New Store
per sq.m. of Total Space, ‘000 RUB
Time to Maturity
6 months
Owned 20-70
Leased 9-16
4-6 years
Number of SKUs
1 500
Appendix 11: Store formats description 4/4
32 Higher School of Economics 2016Sources: Company data, as of December 31, 2015
9%
Suppliers
Import
International
Direct import 757 Open
Contracts
5 800Domestic Suppliers
4 600Local Suppliers
1 200Federal Suppliers
Appendix 12: Suppliers & Import
33 Higher School of Economics 2016Sources: Company data, as of December 31, 2015
Employees
265 982 Employees
29 636AverageMonthlySalary* 5% Wage Rate
Increase*P=
194 723In-storePersonnel
40 369People Engagedin Distribution
19 108People in RegionalBranches
9 342People Employedby Head Office
1000 employees
2 440Other
Private Label
% Shareof Revenue596
PLSKUs 84% Food
Items11
Appendix 13: Private Label & Employees
34 Higher School of Economics 2016Sources: Company data, as of December 31, 2015
New Stores
New Stores
900-950ConvenienceStores 80
Hyper-markets 1 200
DrogerieStores
Annual number of expected and actual store openings
250 250 400-6
394
1041
2013 2014 2015Expected Actual
1100 1350 12001154 1144 1181
60 50 5035 29 27
Hypermarkets
Drogerie stores
Convenience storesCentralization Ratio, %
90
10
92
8
Convenience Stores
FY2015 Future Targets
73
27
80
20
Hypermarkets
Delivered from DC
Delivered from supplier
Delivered from DC
Delivered from supplier
Appendix 14: Plans for 2016
35 Higher School of Economics 2016Sources: Company data, as of December 31, 2015
(Ownership interest = 100% for every company)
CJSC
“Tander”LLC
“BestTorg”
LLC
“Tander-Magnit”
LLC
“TK Zelenaya
Liniya”
LLC
“MagnitEnergo”
LLC
“Star”
LLC
“Tandem”
LLC
“Alkotrading”
LLC
“ITM”
LLC
“Logistica
Alternativa”
LLC
“Retail Import“
“TD-holding”
company
limited
LLC
“Selta”
Magnit PJSC
Import operations
Retail
Maintenance, infrastructure
Supply
Magnit’s organization structure
Appendix 15: Organization structure 1/2
36 Higher School of Economics 2016Sources: Company data, as of December 31, 2015
(Ownership interest = 100% for every company)Magnit’s organization structure |
MAGNITENERGO LLC
Founded in February, 2012.
Electric power supplier for Magnit
TANDER CJSC
Food retail and wholesale
BESTTORG LLC
Food retail in the city of Moscow and
еhe Moscow region
RETAIL IMPORT LLC
Import operations
SELTA LLC
Transportation services for Magnit
TK ZELENAYA LINIYA LLC
Greenhouse complex. Production of own
vegetables.
TANDEM LLC
Rent operations for magnit.
TD-HOLDING LTD.
Founded in 1998. Production and
processing of food for Magnit
TANDER-MAGNIT LLC
Food retail in the Moscow region
ITM LLC
IT operations for Magnit
LOGISTICA ALTERNATIVA LLC
Import operations
STAR LLC
Assets holder, maintenance services for
Magnit
ALKOTRADING LLC
Other operations, retail.
NPF MAGNIT LLC
Founded in 1995.
Non-government pension fund.
Appendix 16: Organization structure 2/2
37 Higher School of Economics 2016Sources: Company data, as of December 31, 2015
Sergey Galitskiy, CEO – 35.1%
Aberdeen Asset Managers Ltd. – 1.6%
OppenheimerFunds, Inc. – 5%
Lavreno Ltd.– 8.0%
Free-float – 55.8%
Magnit’s Shareholder Structure Other investors
April, 2006 April, 2008 October, 2009 December, 2011IPO on RTS & MICEX+ $368 mln
SPO on LSE+ $480 mln
SPO on LSE, RTS & MICEX + $370 mln
SPO on LSE, RTS & MICEX + $475 mln
1common
share= 5 GDRs
LSE - LondonStock Exchange
MICEX - MoscowStock Exchange
Free float, %
February, 2015 & 2016
Investment history
Investor Share
Vladimir Gordeychuk 2.76%
JPMorgan Asset Management UK Ltd. 1.14%
NBIM 1.01%
Aberdeen Asset Managers (Asia) Ltd. 0.8%
APG Asset Management 0.62%
Swedbank Robur Founder AB 0.34%
29.9%
25.9%
Appendix 17: Funding story, free-float & shareholders
38 Higher School of Economics 2016Sources: Company data, Forbes, Kommersant, Thomson Reuters
Mr. Galitskiy sold 1% of Magnit and planned to do it annually
Other minority investors– 1.1%
Rachel
Dark
CONSULT
ANTDate of birth: 14.08.1967
Education: higher - 1992 - Kuban State
University - Economics.
Positions held in the last five years:
1) 04.2004 – present day -PJSC “Magnit” -
member of the Board of Directors;
2) 04.2006 – present day - PJSC “Magnit” -
CEO;
3) Period: 08.2009 – 10.2014 - NP “FC
“Krasnodar” - President;
4) Period: 07.2010 – present day - PJSC
“Magnit” - Chairman of the Management
board;
5) Period: 10.2014 - present day - LLC
“Football Club “Krasnodar” President.
38.6659 % (as of 31.12.2015)*.
38.6659 % (as of 31.12.2015)**.
Sergey
Galitskiy
Khachatur
Pombukhchan
Date of birth: 16.03.1974.
Education: higher - 1996 - Kuban State
University -Applied Mathematics; 2000 -
All-Russian Distance Institute of Finance
and Economics, Economics.
Positions held in the last five years:
1) 06.2008 – 05.2012 LLC “Magnit
Finance” - CEO;
2) 06.2008 – 06.2010 PJSC “Magnit” -
Member of the BOD;
3) 07.2008 – present day - JSC “Tander” -
Chief Financial Officer;
4) 07.2008 – present day PJSC “Magnit” -
Chief Financial Officer;
5) 06.2010 – present day PJSC “Magnit” -
Chairman of the BOD.
Date of birth: 02.01.1964
Education: higher – 1990 - Tajik
State University n.a. Lenin -
Chemistry and Biology.
Positions held in the last five
years:
1) 08.2008– present day
JSC "Tander« - Business
Director (Head Office);
2) 10.2012 – present day
PJSC "Magnit« Member of the
Management Board;
0.001058% (as of 31.12.2015)
0.001058% (as of 31.12.2015)
Marina
Ivanova
11 Members5 Executive Directors
including the Chairman (Mr.
Pobukhchan, CFO)
6 Non-Executive
Directors, including 3
independent ones
Appendix 18: Board of directors 1/3
39 Higher School of Economics 2016Sources: Company data
Alexander
Barsukov
Ilya
Sattarov
Date of birth: 08.07.1977
Education: higher - 1998 -
Rostov Law Institute of Ministry
of Internal
Affairs of the Russian Federation
with a degree in Law.
Positions held in the last five
years:
1) 07.2008 – 12.2012
Organization: JSC “Tander”
Position: Hypermarkets Sales
Director;10
2) 07.2010 – present day
PJSC “Magnit” - Member of the
Management Board;
3) 12.2012 - present day
JSC “Tander” - Director of
Hypermarkets Sales
Department;
0.000888% (as of 31.12.2015).
0.000888% (as of 31.12.2015).
Date of birth: 13.07.1976
Education: higher – 1998 - Kuban State
University, Economics.
Positions held in the last five years:
1) 07.2007 – 12.2010
Organization: Commercial Joint- Stock Bank
“Societe Generale Vostok Bank”, JSC - CEO
(JSC “SGVB” Krasnodar Branch);
2) Period: 12.2010 – 01.2011
JSC “Tander” - Director for Assets
Acquisition and Management (Head Office);
3) 02.2011 – 07.2011
JSC “Tander” - Director for Transport;
4) 08.2011 – present day
JSC “Tander” - Deputy CEO for Logistics
(Head Office);
5) 10.2012 – present day
PJSC “Magnit"
Member of the Management Board.
0.002957% (as of 31.12.2015).
0.002957% (as of 31.12.2015).
Date of birth: 12.01.1969.
Education: higher -1993 - Kuban
State University - Economics.
Positions held the last five
years:
1) 12.2003 – present day.
PJSC “Magnit” - First Deputy
CEO;
2) 06.2008 – present day.
PJSC “Magnit” - Member of the
Board;
3) 07.2009 – present day
JSC “Tander” - Deputy Chief
Executive Officer in Charge of
Development.
0.215686 % (as of 31.12.2015).
0.215686 % (as of 31.12.2015).
Andrey
Arutyunyan
Appendix 19: Board of directors 2/3
40 Higher School of Economics 2016Sources: Company data
Alexey
Pshenichniy
Alexander
Zayonts
Date of birth: 23.02.1967
Education: higher – 1990 -
Krasnodar State Institute of
Physical Culture - Teaching
and Organization of culture
and health activity and
tourism;
MBA - 2004 - the Government
of the Russian Federation;
Positions held the last five
years:
1) 02.2010 - present day
Bazis LLC, Director;
2) 02.2010 – present day
Yunior LLC – Director;
3) 01.2004 - present day
Sports goods chain Visshaya
LIGA LLC - Director;
4) 12.2012 – present day
Sport Plyus LLC – Director;
5) 05.2014 - present day
PJSC “Magnit”
Member of the Board of
Directors.
Date of birth: 10.01.1967
Education: higher – Moscow
Institute of Chemical
Engineering n.a. D.I.
Mendeleev - Chemical
process engineering.
Positions held the last five
years:
1) 01.2008 – present day
Domashniy Interier LLC -
General Director;
2) 12.2009 – 09.2013
Obiedinennye resursy LLC -
Member of the Board of
Directors;
3) 06.2010 – present day
PJSC "Magnit“ - Member of
the Board of Directors;
4) 04.2012 – present day
EDELWEISS LLC - General
Director.
Date of birth: 24.05.1976
Education: Ph.D. - 1998 - Saint Petersburg
University of Economics and Finance,
Economics
Positions held in the last five years:
1) 05.2009– 24.01.2013
CJSC “VTB Capital” - Managing Director,
Head of the Consumer Sector and Retail,
Investment Banking on Global Markets
Department;
2) 06.2009 – present day
PJSC "Magnit“ - Member of the Board of
Director;
3) 01.2013 – present day
CJSC "VTB Capital“ - Head of the
Consumer Sector, Retail and Real Estate,
Corporate and Investment Department;
4) 01.2013 – present day
OJSC "Bank VTB“ - Head of the Trade,
Consumer Goods, Agro and
Pharmaceutical Industries Business Unit of
Market Sector Clients Service Department
– Senior Vice-President;
Alexey
Makhnev
Aslan
Schkhach-
emukov
Date of birth: 22.08.1962
Education: higher – 1987 -
Krasnodar Polytechnic
Institute of the Order of the
Red Banner of Labor,
Industrial Engineering.
Positions held in the last
five years:
1) 10.2007 – 03.2012
JSC “Tander” - Deputy
General Director;
2) 06.2011 – present day
PJSC ”Magnit” - Member
of the Board of Directors;
3) 03.2012 – present day -
JSC “Tander” - Deputy
CEO for Economic
Security and
Organizational Issues.
0.009165% (as of
31.12.2015).
0.009165% (as of
31.12.2015).
Appendix 20: Board of directors 3/3
41 Higher School of Economics 2016Sources: Company data
National Research University
Higher School of Economics
APPENDIX
Financial Statements
Business Overview Appendix
Industry Analysis Appendix
Financial Analysis Appendix
Valuation Appendix
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
2010 2011 2012 2013 2014 2015
Magnit X5 Retail Group Dixy O'key Lenta
Selling space dynamics (‘000 m2))
CAGR (2010-2015)
Lenta 22%
Magnit 21%
X5 Retail Group 14%
O'key 13%
Dixy 6%
0
100
200
300
400
500
600
700
800
900
1000
2010 2011 2012 2013 2014 2015
Magnit X5 Retail Group Dixy O'key Lenta
Revenue dynamics (RUB bln)
CAGR (2010-2015)
Magnit 26%
Dixy 26%
Lenta 23%
X5 Retail Group 15%
O'key 12%
Appendix 21: Key indicators of peer companies
43 Higher School of Economics 2016Sources: Company data
Revenue split by format in 2015 (RUB bln)
701596
219
207
77
18245146
130
33714
40
MagnitX5DixyLentaO'key
Drogerie
Supermarkets
Hypermarkets
Convenience stores
Format Magnit X5 Dixy Lenta O’key
Convenience 225 328 323 n/a n/a
Supermarkets 419 485 416 596 511
Hypermarkets 588 645 616 1241 970
Average tickets in 2015 (RUB)
Appendix 22: Revenue split, average checks and location
44 Higher School of Economics 2016Sources: Company data
X5 Magnit Dixy Lenta
Central FD 17 10 5 2
Northwestern FD 2 2
Southern FD 2 8
North Caucasian FD 1
Volga FD 5 10
Ural FD 5 2 1
Siberian FD 5 1 1
Far Eastern FD
Total 34 34 6 5
Location of distribution centers as of 25.01.2016Retail turnover by Federal District
34.2%
9.0%
9.1%5.1%
18.4%
9.2%
10.2%
4.0% 0.7% Central Federal District
Northwestern Federal District
Southern Federal District
North Caucasian Federal District
Volga Federal District
Ural federal district
Siberian Federal District
Far Eastern Federal District
Magnit X5 Dixy
Average check Traffic Revenue Average
checkTraffic Revenue
Average
checkTraffic Revenue
2013
Convenience stores 5% -2% 4% 4% -4% 0% 7% -2% 5%
Hypermarkets 2% 3% 4% 1% 3% 3% 2% 0% 2%
Supermarkets 5% 7% 13% 2% -2% 0% 4% -2% 2%
Drogerie 4% 11% 15%
2014
Convenience stores 10% 4% 14% 12% 2% 13% 11% 2% 14%
Hypermarkets 8% 6% 14% 5% -2% 5% 7% -4% 3%
Supermarkets 9% 9% 19% 5% -3% 2% 5% 1% 6%
Drogerie 4% 36% 41%
2015
Convenience stores 8% 1% 7% 14% 4% 18% 13% 0% 13%
Hypermarkets 6% -4% 2% 8% 3% 11% 7% -4% 3%
Supermarkets 4% -4% 1% 12% -5% 7% 3% 3% 6%
Drogerie 13% 6% 20%
Appendix 23: LFL indicators by format
45 Higher School of Economics 2016Sources: Company data
20%
42%
23%
15%
Modern retail (top five)
Modern retail (excluding top five)
Kiosks and open markets
Traditional retail
Modern retail penetration vs traditional formats Available retail space per capita (m2 per 1,000 people)
1,450
1,230
1,150
1,100
1,020
690
Germany
France
UK
Spain
Italy
Russia
Appendix 24: Modern retail penetration and space
46 Higher School of Economics 2016Sources: Euromonitor
0%
5%
10%
15%
20%
25%
30%
35%
Jan-14 Mar-14 May-14 Jul-14 Sep-14 Nov-14 Jan-15 Mar-15 May-15 Jul-15 Sep-15
Mo
nth
ly s
ales
gro
wth
(y/y
)
Russian food retail Food CPI X5, MGNT,LNTA, DIXY Avge
Appendix 25: Sales growth and food CPI
47 Higher School of Economics 2016Sources: Company data, Federal State Statistics Service
Economic growth by sector 2003-13 (gross value added), annualized
0.1%
0.5%
0.8%
1.2%
1.3%
1.4%
2.2%
2.3%
2.4%
2.7%
3.1%
3.3%
4.0%
4.0%
4.6%
4.7%
6.0%
6.9%
9.5%
14.7%
Machinery
Government
Utilities
Consumer discretionary
Healthcare
Agriculture
Tradables
Oil and Gas
Transport
Metals and mining
Consumer Staples
Consumer services
Business survices
Total GDP
Non-tradables
Chemicals
Retail
Constructions and real estate
Telecoms
Financials
Appendix 26: Economic growth by sector 2003-2013
48 Higher School of Economics 2016Sources: Federal State Statistics Service
-30%
-10%
10%
30%
Apr 98 Feb 05 Dec 01 Oct 03 Aug 05 Jun 07 Apr 09 Feb 11 Dec 12 Oct 14
Real food retail growth, y/y Real non-food retail growth, y/y
Appendix 27: Dynamics of food and non-food retail growth
49 Higher School of Economics 2016Sources: Federal State Statistics Service
20
25
30
35
40
45
50
55
60
65
700
20
40
60
80
100
120
140
Jan 11 Nov 11 Sep 12 Jul 13 May 14 Mar 15
Brent USD/RUB (inverted)
Appendix 28: Brent prices versus USD/RUB exchange rate
50 Higher School of Economics 2016Sources: Federal State Statistics Service
APPENDIX
National Research University
Higher School of Economics
APPENDIX
Financial Statements
Business Overview Appendix
Industry Analysis Appendix
Financial Analysis Appendix
Valuation Appendix
2011 2012 2013 2014 2015E 2016F 2017F 2018F 2019F 2020FProfitability ratios
Gross margin 24.3% 26.5% 28.5% 28.9% 28.8% 27.2% 27.6% 28.0% 28.9% 29.8%
EBITDAR margin 11.7% 14.2% 15.2% 15.3% 14.2% 12.3% 12.4% 12.4% 13.0% 13.7%
EBITDA margin 8.2% 10.6% 11.2% 11.3% 10.9% 9.6% 10.0% 10.4% 11.3% 12.2%
EBIT margin 5.8% 8.0% 8.7% 8.9% 8.8% 7.4% 7.8% 8.2% 9.1% 10.0%
Net margin 3.7% 5.6% 6.1% 6.2% 6.0% 4.7% 5.2% 5.7% 6.5% 7.3%ROE 18.8% 28.3% 31.6% 35.3% 36.1% 29.0% 32.8% 35.8% 39.9% 43.0%
ROA 8.5% 12.7% 14.6% 15.6% 15.3% 12.5% 14.3% 16.1% 19.0% 22.1%
ROCE 18.9% 26.5% 32.0% 36.8% 38.6% 33.6% 37.3% 40.1% 44.4% 49.0%
Liquidity Ratios
Current ratio 1.06 0.75 0.70 0.72 0.70 0.66 0.68 0.73 0.79 0.87
Quick ratio 0.38 0.18 0.08 0.13 0.12 0.06 0.07 0.08 0.09 0.14
Cash ratio 0.37 0.17 0.07 0.12 0.11 0.05 0.06 0.07 0.08 0.14
Investment Ratios
Capex/ Revenue 14.5% 10.5% 8.6% 7.3% 6.9% 6.0% 5.3% 4.6% 4.2% 3.8%
Capex/D&A 6.10 4.20 3.53 3.16 3.16 2.68 2.31 2.03 1.82 1.65
Solvency Ratios
Debt to Total Capital Ratio 29.7% 28.7% 27.6% 27.8% 28.4% 27.8% 25.9% 22.7% 17.9% 13.6%
Long Term Debt Ratio 26.2% 17.3% 14.1% 12.9% 13.0% 11.9% 10.7% 10.6% 9.3% 7.2%
Long Term Debt to Total Debt 88.1% 60.4% 51.0% 46.5% 45.9% 42.9% 41.4% 46.8% 51.9% 52.8%
D/E 66.1% 63.9% 58.7% 66.7% 65.9% 64.3% 59.0% 49.4% 36.1% 25.4%
Net Debt/Equity 44.3% 51.3% 54.0% 54.4% 55.4% 59.2% 53.3% 43.2% 29.8% 15.8%
Interest Coverage Ratio 5.74 8.90 10.17 10.28 8.80 6.03 7.85 10.72 16.11 23.28
Net Debt/EBITDA 1.26 1.07 1.05 0.91 0.92 1.08 0.91 0.72 0.47 0.24
Efficiency Ratios
Total assets turnover 2.33 2.27 2.37 2.49 2.55 2.65 2.72 2.81 2.91 3.02
Fixed assets turnover 2.66 2.76 2.89 3.19 3.33 3.45 3.61 3.82 4.04 4.28
Receivables Turnover 579 804 954 1057 1109 989 922 999 1088 1143
Average receivables collection period 0.63 0.45 0.38 0.35 0.33 0.37 0.40 0.37 0.34 0.32
Inventory Turnover 9.7 8.8 8.0 7.4 7.4 7.8 7.5 7.5 7.5 7.7
Average inventory processing period 37.79 41.49 45.67 49.21 49.02 46.85 48.55 48.63 48.55 47.63
Trade Payables Turnover 8.6 8.4 8.9 9.3 9.4 10.2 9.8 9.7 9.6 9.9
Payables payment period 42.44 43.55 41.23 39.18 38.93 35.80 37.24 37.75 37.90 37.05Cash conversion cycle -4.02 -1.60 4.82 10.38 10.41 11.41 11.71 11.24 10.98 10.91
Earnings per share
EPS 137.90 265.62 376.69 504.29 603.00 568.17 741.59 945.91 1239.78 1584.05
DPS 11.20 44.59 100.94 319.34 320.00 301.50 348.18 465.10 624.40 834.81
Dividend payout ratio 8% 17% 27% 63% 53% 53% 47% 49% 50% 53%
Appendix 30: Key financial ratios
52 Higher School of Economics 2016Sources: Company data, team estimates
in RUB mln Historical Projected
Period Ending December 31 2011 2012 2013 2014 2015E 2016F 2017F 2018F 2019F 2020F
Current assets
Trades and other receivables 533 584 632 813 897 1 400 1 502 1 626 1 671 1 901
Days receivable 0.58 0.45 0.38 0.35 0.35 0.45 0.41 0.38 0.34 0.34
Inventories 29 144 41 026 56 095 81 476 89 078 110 609 131 294 149 614 167 614 181 277
Inventory turnover days 33.0 41.5 45.7 49.2 51.2 51.9 52.7 51.8 51.3 49.5
Prepaid expenses 380 182 252 243 329 388 390 456 437 498
Days prepaid expenses 1.8 1.0 0.9 0.7 0.6 0.6 0.5 0.5 0.5
Advances paid
Third party suppliers 1 092 1 901 2 236 3 114 3 865 4 631 5 454 6 369 7 314 8 322
as % of Revenue 0.3% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4%
For custioms duties 652 719 882 1 537 1 422 1 703 2 006 2 343 2 690 3 061
as % of Revenue 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2% 0.2%
Advances to employees 50 55 53 60 75 89 105 123 141 160
as % of Revenue 0.02% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01%
To related party suppliers 6 3 1 139 3 3 3 3 3 3
Total advances paid 1 800 2 677 3 171 4 849 5 365 6 427 7 568 8 838 10 148 11 547
Total advances paid as % of Revenue 0.5% 0.6% 0.5% 0.6% 0.6% 0.6% 0.6% 0.6% 0.6% 0.6%
Total current assets 31 857 44 469 60 150 87 381 95 668 118 825 140 754 160 534 179 869 195 223
Current liabilities
Trade and other payables 33 566 42 921 48 171 66 795 70 292 86 547 103 214 118 647 132 785 141 339
Days payable 42.3 40.1 38.6 38.0 38.2 38.9 38.5 38.0 36.0
Accrued expenses 3 946 5 021 6 612 8 185 11 622 14 249 16 713 18 988 21 864 24 184
Days payable 29.0 27.0 26.2 24.7 25.7 25.7 25.0 25.0 24.3
Taxes payable 2 467 3 731 4 629 5 386 6 145 7 242 8 353 9 521 10 703 11 942
Total current liabilities 39 979.9 51 672.9 59 411.8 80 365.5 88 058.7 108 037.1 128 279.7 147 155.4 165 352.3 177 465.5
Total operating working capital -8 122.8 -7 204.1 738.3 7 015.2 7 609.7 10 787.4 12 474.8 13 378.5 14 516.9 17 757.7
Change in total operating working capital 919 7 942 6 277 594 3 178 1 687 904 1 138 3 241
Appendix 31: Working capital
53 Higher School of Economics 2016Sources: Company data, team estimates
in RUB mln Historical Income Statement Projected Income Statement
Period Ending December 31 2011 2012 2013 2014 2015E 2016F 2017F 2018F 2019F 2020F
Property, plant & equipment (beg. of year) 232 968.8
Capital expenditures (beg. of year) 68 250.0 70 297.5 72 406.4 74 578.6 76 816.0 79 120.5
Book (GAAP) depreciation
Useful Life
PP&E Years 15.00
CAPEX Years 15
Depreciation
Existing PP&E 15 531.3 15 531.3 15 531.3 15 531.3 15 531.3 15 531.3
2015E CAPEX 4 550.0 4 550.0 4 550.0 4 550.0 4 550.0 4 550.0
2016F CAPEX 4 686.5 4 686.5 4 686.5 4 686.5 4 686.5
2017F CAPEX 4 827.1 4 827.1 4 827.1 4 827.1
2018F CAPEX 4 971.9 4 971.9 4 971.9
2019F CAPEX 5 121.1 5 121.1
2020F CAPEX 5 274.7
Total book depreciation 7 822.2 11 025.5 13 890.5 17 264.2 20 081.3 24 767.8 29 594.8 34 566.8 39 687.8 44 962.5
Amortization 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00
% of Intengible assets 55% 47% 40% 38% 35% 34% 32% 31% 30% 29%
Amortization 157.7 244.2 293.9 345.5 515.3 716.2 866.6 1 048.6 1 268.9 1 535.3
Appendix 32: Depreciation and amortization
54 Higher School of Economics 2016Sources: Company data, team estimates
Net income (RUB bn)
25.12 35.62 47.69
57.02 53.73 70.13
89.45 117.24 149.80
EBIT (RUB bn)
36.11 50.54 68.30
83.68 83.79 104.53
128.33 162.59 203.59
EBT / EBIT
89% 91% 91%
89% 84% 88%
91% 94% 96%
Net Income / EBT
78% 78% 77%
77% 77% 77%
77% 77% 77%
ROE
28.3% 31.6% 35.3%
36.1% 29.0% 32.8%
35.8% 39.9% 43.0%
Legend
2012 2013 2014
2015E 2016F 2017F
2018F 2019F 2020F
ROA
12.7% 14.6% 15.6%
15.3% 12.5% 14.3%
16.1% 19.0% 22.1%
Assets/Equity
2.23 2.17 2.27
2.35 2.32 2.29
2.22 2.09 1.94
Profit margin
5.6% 6.1% 6.2%
6.0% 4.7% 5.2%
5.7% 6.5% 7.3%
Sales/Assets
2.27 2.37 2.49
2.55 2.65 2.72
2.81 2.91 3.02
Appendix 33: DuPont analysis
55 Higher School of Economics 2016Sources: Company data, team estimates
Cost of goods sold94%
Transportation expenses
3%
Labor cost1%
Less due to inventory shortage
2%
Cost of sales breakdown (2014)
64%
68%
72%
76%
80%
0
500
1000
1500
2000
2011 2012 2013 2014 2015E 2016F 2017F 2018F 2019F 2020F
Cost of sales, RUB bln Cost of sales, % of Revenue (rhs)
0%
7%
14%
21%
0
100
200
300
2011 2012 2013 2014 2015E 2016F 2017F 2018F 2019F 2020F
SG&A, RUB bln SG&A, % of Revenue (rhs)
Labor cost3% Rent
expenses2%
Labor taxes15%
Amortization54%
Other expenses
26%
SG&A breakdown (2014)
Cost of sales dynamics (2011-2020F) SG&A dynamics (2011-2020F)
Appendix 34: Cost of sales and SG&A structure and dynamics
56 Higher School of Economics 2016Sources: Company data, team estimates
RUB mln 2015E 2016F 2017F 2018F 2019F 2020F
Магнит, 01
Coupon Payment 425 213
Principal 5 000
Магнит, 02
Coupon Payment 303 605 605 303
Principal 5 000
Магнит, 03
Coupon Payment 303 605 605 303
Principal 5 000
Магнит, БО-001Р-01
Coupon Payment 1 120 560
Principal 10 000
Магнит, БО-08
Coupon Payment 420 210
Principal 5 000
Магнит, БО-09
Coupon Payment 420 210
Principal 5 000
Магнит, БО-10
Coupon Payment 1 160 1 160 1 160 1 160 1 160
Principal 10 000
Bond 8 1 170 1 170 1 170 1 170 1 170
Coupon Payment 10 000
Principal
Total Coupon Payments 1 870 5 293 4 100 2 935 2 330 2 330
Bond Principal Payments 15 000 10 000 10 000 20 000
Appendix 34: Bonds repayment
57 Higher School of Economics 2016Sources: Bloomberg, team estimates
National Research University
Higher School of Economics
APPENDIX
Financial Statements
Business Overview Appendix
Industry Analysis Appendix
Financial Analysis Appendix
Valuation Appendix
Sources: Company data, Bloomberg, team estimates 59 Higher School of Economics 2016
Discounted Cash Flow(mln RUB, ending period December 31)
Historical Period CAGR Forecasted Period CAGR
2011 2012 2013 2014 ('11-'14) 2015E 2016 2017 2018 2019 2020 ('15-'20)
Sales 335,699.9 448,661.1 579,694.9 763,527.3 31.5% 947,801.0 1,135,604.6 1,337,271.4 1,561,825.1 1,793,344.9 2,040,751.7 15.8%
% growth 42.1% 33.6% 29.2% 31.7% 24.1% 19.8% 17.8% 16.8% 14.8% 13.8%
EBITDA 27,607.6 47,380.5 64,721.2 85,909.7 46.0% 103,759.1 108,558.2 134,123.1 162,892.3 202,282.3 248,555.6 23.0%
% margin 8.2% 10.6% 11.2% 11.3% 10.9% 9.6% 10.0% 10.4% 11.3% 12.2%
Depreciation & Amortization 7,983.4 11,269.7 14,184.3 17,609.7 20,081.3 24,767.8 29,594.8 34,566.8 39,687.8 44,962.5
EBIT 19,624.2 36,110.9 50,536.9 68,300.0 51.5% 83,677.8 83,790.4 104,528.3 128,325.5 162,594.5 203,593.1 24.9%
% margin 5.8% 8.0% 8.7% 8.9% 8.8% 7.4% 7.8% 8.2% 9.1% 10.0%
Taxes 4,186.5 7,195.8 10,133.7 14,340.7 17,148.2 16,157.8 21,089.8 26,900.6 35,258.2 45,049.3
EBIT*(1-Tax) 15,437.7 28,915.1 40,403.2 53,959.3 51.8% 66,529.7 67,632.6 83,438.5 101,424.9 127,336.3 158,543.8 23.7%
Plus: Depreciation & Amortization 7,983.4 11,269.7 14,184.3 17,609.7 20,081.3 24,767.8 29,594.8 34,566.8 39,687.8 44,962.5
Less: Capital Expenditures - 48,691.3 - 47,309.8 - 50,051.2 - 55,711.8 - 65,000.0 - 68,250.0 - 70,297.5 - 72,406.4 - 74,578.6 - 76,816.0
Less: Inc./Dec. in Net Working Capital - 3,177.7 - 1,687.3 - 903.8 - 1,138.4 - 3,240.8
20,972.7 41,048.5 62,681.5 91,307.1 123,449.6
Free Cash Flow to the Firm (FCFF)
WACC (Forecast Peiod) 16.60%
WACC (Terminal Peiod) 14.60%
Discount Period (Mid-Year Convention) 0.5 1.5 2.5 3.5
Discount Factor 0.93 0.79 0.68 0.58
Present Value of Free Cash Flow 34,564.0 46,983.7 60,000.6 70,326.7
Appendix 35: Discounted Cash Flow Analysis (1/3)
Sources: Company data, Bloomberg, A. Damodaran, team estimates 60 Higher School of Economics 2016
Appendix 35: Discounted Cash Flow Analysis (2/3)
Maturity date 24.06.2028Face value, USD 1,000Close price on valuation date, USD 1,054.28Coupon annual rate, % 12.75Number of coupons per year 2Number of coupons remaining 24Russia-12Yr Eurobond yield to maturity, % 6.475
US risk-free rate, % 2.03%US ERP, % 6.00%Levered beta (US peers) 1.04Unlevered beta (US peers) 0.76Magnit D 0.10Magnit E 0.89Re-levered beta (Magnit D/E) 0.82CoE, USD 6.98%CDS spread, % as of 20/01/2016 4.44Inflation, Russia 8%Inflation, USA 2%CoE, RUB 17.53%
10.00
10.10
10.20
10.30
10.40
10.50
10.60
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
0
1
2
3
4
5
6
7
8
9
0 5 10 15 20 25 30
USD denominated 12-Yr Government Eurobond
Risk-free rate: US 10-Yr T-bond yield [Source: U.S. Department of treasury]Beta: US Food retail beta (Lev./ Unlev.) including 17 companies [Source: A. Damodaran]MRP: US market risk premium [Source: A. Damodaran]
CAPM (US market + Country risk premium)
Ret
urn
, %
Maturity, Y
Ret
urn
, %Maturity, Y
Russian Government Bonds return curve
Russian Government Eurobonds return curve
Sources: Company data, Bloomberg, team estimates 61 Higher School of Economics 2016
Implied Equity Value and Share Price
Cumulative Present Value of FCF 211,874.5
Terminal Value 1,021,656.6
Enterprise Value 1,234,104.1
Less: Total Debt 127,167.0
Plus: Cash and Cash Equivalent 27,272.4
Implied Equity Value 1,134,809.5
Shares Outstaning 94,561.0
Implied Share Price Value 12,000.8
Terminal Period GrowthInflation 5.3%Real GDP growth 1.1%Growth rate 6.4%
Share price sensitivity analysisWACC Terminal Growth Rate
#DIV/0! 4.4% 5.4% 6.4% 7.4% 8.4%12.6% 11,798 13,386 15,486 18,394 22,68713.6% 10,645 11,899 13,501 15,620 18,55414.6% 9,719 10,736 12,001 13,617 15,75515.6% 8,958 9,801 10,826 12,102 13,73316.6% 8,322 9,032 9,882 10,917 12,204
Appendix 35: Discounted Cash Flow Analysis (3/3)
All else being equal, price level is crucial for consumers:
Appendix 45: Business model differes Magnit from other local retailers
62 Higher School of Economics 2016Sources: Company data, team estimates
The real difference is on the operational level and strategy:
In Russian consumers’ eyes, Magnit and its closest competitors do not differ from each other representing typical grocery store
221 222
Quality control of products on the shelf
Delivery WarehouseStores
Own logistics reduces delivery costs and delays
High level of centralization and stores servings
Key parts of Magnit’s business model:223
Unique developed business model is what really differ Magnit from local peers by:
In-House innovative logistic
Organic growth strategy at the core of the business
Advanced merchandising at stores
Overall control by developed IT system
Unique ability of fast expand in distant areas with lower level of competition
10.1x
11.7x
7.0x
3.8x
6.6x
6.2x
0.0x 5.0x 10.0x
Magnit’s premium over peers is justified
Sources: Company data, Bloomberg, team estimates
Trading multiples analysis1
Magnit is trading with premium regarding to:
18.7x
22.1x
13.6x
9.3x
12.7x
13.0x
0.0x 10.0x 20.0x
Magnit (local shares)
Magnit (GDR)
Lenta
Dixy Group
X5 Retail Group
O'Key Group
7.6x
8.9x
7.3x
3.0x
4.1x
4.4x
0.0x 5.0x
0.9x
1.1x
0.4x
0.2x
0.4x
0.7x
0.0x 0.5x 1.0x
P/E 2016F EV/EBITDA 2016F EV/EBITDAR 2016F PEG 2016F
Expectations of further dividends growth
Strong corporate governance
High FCFF growth
63 Higher School of Economics 2016
13.0x 6.6x 4.4x 0.4x
Unique developed business model
CompanyCurrent price,
RUBMcap, RUB bln
P/E EV/EBITDA EV/EBITDAR
2015E 2016E 2015E 2016E 2015E 2016E
Magnit (local shares) 10,655 1,006 17.66x 18.74x 10.52x 10.06x 8.05x 7.63x
Russian peers
Lenta 19.60x 13.56x 9.19x 7.33x 9.16x 7.33x
Dixy Group nmf. 9.29x 5.23x 3.83x 3.45x 2.95x
X5 Retail Group 20.10x 12.66x 8.42x 6.57x 5.05x 4.07x
O'Key Group 14.55x 13.02x 6.35x 6.21x 4.55x 4.45x
Russian peers, median 19.60x 12.84x 7.39x 6.39x 4.80x 4.26x
Magnit premium / (discounts) -10% 46% 42% 58% 68% 79%
Magnit (local shares) upside 2015E 2016E 2015E 2016E 2015E 2016E
11% -32% -30% -37% -40% -44%
Magnit (local shares) target price 2015E 2016E 2015E 2016E 2015E 2016E
11,829.6 7,298.6 7,479.7 6,765.0 6,348.6 5,942.7
Weights 0% 50% 0% 50% 0% 0%
Target price, RUB 7,032
Current price, RUB 10,655
Downside -34%
Appendix 36: Trading Multiples Analysis (local shares)
64 Higher School of Economics 2016Sources: Bloomberg, team estimates
CompanyCurrent
price, USDMcap, USD mln
P/E EV/EBITDA EV/EBITDAR
2015E 2016E 2015E 2016E 2015E 2016E
Magnit (GDR) 33.3 15 738 20.78x 22.05x 12.24x 11.70x 9.36x 8.88x
Russian peers
Lenta 19.60x 13.56x 9.19x 7.33x 9.16x 7.33x
Dixy Group nmf. 9.29x 5.23x 3.83x 3.45x 2.95x
X5 Retail Group 20.10x 12.66x 8.42x 6.57x 5.05x 4.07x
O'Key Group 14.55x 13.02x 6.35x 6.21x 4.55x 4.45x
Russian peers, median 19.60x 12.84x 7.39x 6.39x 4.80x 4.26x
Magnit premium / (discounts) 6% 72% 66% 83% 95% 109%
Magnit (GDR) upside 2015E 2016E 2015E 2016E 2015E 2016E
-6% -42% -40% -45% -49% -52%
Magnit (GDR) target price 2015E 2016E 2015E 2016E 2015E 2016E
10,053.1 6,202.5 6,431.8 5,817.3 5,459.2 5,110.1
Weights 0% 50% 0% 50% 0% 0%
Target price, USD 16.0
Current price, USD 33.3
Downside -52%
Appendix 37: Trading Multiples Analysis (GDRs)
65 Higher School of Economics 2016Sources: Bloomberg, team estimates
CompanyP/E EV/EBITDA EV/EBITDAR FCF yield Dividend yield PEG
2015E 2016E 2015E 2016E 2015E 2016E 2015E 2016E 2015E 2016E 2015E 2016E
Magnit (local shares) 17.7x 18.7x 10.5x 10.1x 8.1x 7.6x 1.4% 2.9% 4.7% 4.6% 0.9x 0.9x
Magnit (GDR) 20.8x 22.1x 12.2x 11.7x 9.4x 8.9x 1.2% 2.5% 3.7% 3.6% 1.0x 1.1x
Lenta 19.6x 13.6x 9.2x 7.3x 9.2x 7.3x -8.7% -7.4% 0.0% 0.0% 0.5x 0.4x
Dixy Group nmf. 9.3x 5.2x 3.8x 3.4x 3.0x -5.5% -1.9% 0.0% 0.0% nmf. 0.2x
X5 Retail Group 20.1x 12.7x 8.4x 6.6x 5.0x 4.1x -5.5% 1.9% 0.0% 0.0% 0.8x 0.4x
O'Key Group 14.6x 13.0x 6.4x 6.2x 4.5x 4.4x -0.2% 1.8% 3.5% 4.7% 1.5x 0.7x
Peers median 19.6x 12.8x 7.4x 6.4x 4.8x 4.3x -5.5% 0.0% 0.0% 0.0% 0.8x 0.4x
Trading multiples
Key financials (2014)
CompanyCurrent market
capitalization (RUB bln)Sales (RUB bln) EBITDA margin Net profit margin ROA ROE CapEx / Sales
Net debt / EBITDA
Magnit (local shares) 1006.9 763.5 11.3% 6.2% 15.6% 35.3% 7.3% 0.91x
Lenta 202.6 194.0 11.0% 4.6% 7.9% 53.0% 17.5% 2.80x
Dixy Group 34.4 229.0 7.1% 2.0% 5.3% 17.0% 3.5% 1.50x
X5 Retail Group 357.7 633.9 7.2% 2.0% 3.9% 15.1% 4.8% 2.30x
O'Key Group 32.4 152.0 7.4% 3.4% 6.9% 22.9% 12.2% 2.30x
Peers median 118.5 211.5 7.3% 2.7% 6.1% 20.0% 8.5% 2.30x
Appendix 38: Peer Group Analysis (Russian retailers)
66 Higher School of Economics 2016Sources: Bloomberg, team estimates
CompanyMarket
capitalization (USD bln)
P/E EV/EBITDA FCF yield Dividend yield PEG
2015E 2016E 2015E 2016E 2015E 2016E 2015E 2016E 2016E
Magnit (local shares) 13.4 17.7x 18.7x 10.5x 10.1x 1.4% 2.9% 4.7% 4.6% 0.9xMagnit (GDR) 15.7 20.8x 22.1x 12.2x 11.7x 1.2% 2.5% 3.7% 3.6% 1.1x
South AfricaShoprite 4.4 16.9x 15.7x 8.3x 7.4x 3.7% 5.8% 3.0% 3.2% 1.4xSpar 1.9 18.8x 16.5x 11.9x 10.5x 5.7% 7.1% 3.8% 3.9% 1.4xPick 'n Pay 1.9 29.2x 23.3x 12.4x 10.4x 2.2% 3.5% 2.3% 2.9% 0.9xMassmart 1.3 17.5x 13.7x 7.6x 6.2x 2.4% 4.5% 3.5% 4.5% 0.6xClicks 1.3 21.4x 18.8x 12.5x 11.1x 3.4% 4.9% 2.9% 3.2% 1.5x
South Africa peers median 1.9 18.8x 16.5x 11.9x 10.4x 3.4% 4.9% 3.0% 3.2% 1.4x
TurkeyBIM 5.0 26.1x 24.5x 17.2x 15.5x 2.1% 3.1% 2.7% 2.9% 1.2xMigros Ticaret 0.9 na 24.9x 8.1x 7.1x -0.1% 6.4% N/A N/A 0.6xTurkey peers median 3.0 26.1 24.7 12.6 11.3 0.0 0.0 0.0 0.0 0.9
PolandEurocash 1.7 33.9x 24.6x 15.8x 13.0x 7.0% 4.7% 1.6% 2.0% 1.3x
USAKroger 37.5 18.7x 19.3x 8.9x 7.8x 3.1% 3.9% 1.1% 1.0% 1.8xWhole Foods Market 10.2 18.0x 19.2x 8.1x 7.4x 2.6% 2.5% 1.8% 1.7% 2.0xSysco 22.5 23.4x 22.5x 14.0x 10.2x 2.9% 4.5% 3.1% 3.1% 2.2xUSA peers median 22.50 18.7x 19.3x 8.9x 7.8x 2.9% 3.9% 1.8% 1.7% 2.0x
Appendix 39: Peer Group Analysis (International retailers)
67 Higher School of Economics 2016Sources: Bloomberg, team estimates
Actuals Estimates
2011A 2012A 2013A 2014A 2015E 2016F 2017F 2018F 2019F 2020F1 Marginal revenue method
Stores gain YoY, net 5 6 7 8 9 10 11 12 13 14
Convenience stores 1 004 1 040 1 154 1 144 1 250 900 1 000 1 000 950 900 dRev/dStores 75 74 75 111 99 80 85 85 85 85
Hypermarkets 40 36 35 29 29 30 25 20 20 20 dRev/dStores 560 812 879 1 154 756 950 1 090 1 210 1 210 1 300
Family stores 2 17 26 51 58 51 45 40 40 40 dRev/dStores 446 285 236 155 351 382 220 255 285 285
Drogerie 208 482 - 6 394 1 041 1 200 1 150 1 100 1 000 1 000 dRev/dStores 4 10 - 1 023 20 20 16 21 21 22 23
New stores, total 1 254 1 575 1 209 1 618 2 378 2 181 2 220 2 160 2 010 1 960 Number of stores, eop
Convenience stores 5 006 6 046 7 200 8 344 9 594 10 494 11 494 12 494 13 444 14 344 Rev per store 57 60 63 69 73 74 75 75 76 77
Hypermarkets 90 126 161 190 219 249 274 294 314 334 Rev per store 513 599 659 735 738 749 764 780 804 834
Family stores 3 20 46 97 155 206 251 291 331 371 Rev per store 266 155 232 263 296 317 300 294 293 292
Drogerie 210 692 686 1 080 2 121 3 321 4 471 5 571 6 571 7 571
Rev per store 4 8 17 18 19 18 19 19 20 20
Total selling space, sq. m.
Convenience stores 1 637 830 1 977 456 2 312 198 2 673 310 3 119 489 3 412 124 3 737 274 4 062 424 4 371 317 4 663 952
Hypermarkets 278 445 387 616 482 877 559 089 639 042 726 582 799 532 857 892 916 252 974 612
Family stores 3 798 24 357 53 262 109 071 170 035 225 982 275 347 319 227 363 107 406 987
Drogerie 50 091 159 827 163 040 249 166 484 649 758 849 1 021 624 1 272 974 1 501 474 1 729 974
Total selling space, sq. m. 1 970 164 2 549 256 3 011 377 3 590 636 4 413 215 5 123 537 5 833 777 6 512 517 7 152 149 7 775 524
Total selling space, sq. m. – Company’ projection 4 345 090 5 235 090 6 015 090 6 775 090 7 515 090 7 587 090
Appendix 40: Revenue Calculations (Marginal Revenue)
68 Higher School of Economics 2016Sources: Company, Bloomberg, team estimates
Actuals Estimates
2011A 2012A 2013A 2014A 2015E 2016F 2017F 2018F 2019F 2020F1 9 10 11 12 13 14
Total revenue per type, mln RUB
Convenience stores
Revenue by old/new add. Rev method 287 732 364 236 450 801 577 776 701 275 814 184 947 475 1 094 664 1 252 956 1 422 815
Revenue growth, % 35.52% 26.59% 23.77% 28.17% 21.4% 16.1% 16.4% 15.5% 14.5% 14%
Like-for-like growth, % 11.6% 5.3% 3.7% 13.9% 7.3% 7.3% 7.3% 7.3% 7.3% 7.3%
Like-for-like growth, mln RUB 24 606.9 15 105.9 13 476.7 62 436.0 42 119.9 51 093.4 59 798.4 69 361.1 79 919.4 91 155.9
Revenue growth contributed by new stores, % 23.93% 21.34% 20.07% 14.32% 14.1% 8.8% 9.0% 8.2% 7.2% 6.3%
Revenue growth contributed by new stores, mln RUB 50 813.3 61 398.7 73 088.3 64 538.3 81 379.3 61 815.7 73 492.0 77 828.1 78 372.87 78 702.86
Revenue growth contributed by new stores per 1 new store 50.61 59.04 63.33 56.41 65.10 68.68 73.49 77.83 82.50 87.45
Average Additional Revenue per 1 new store 51.54 54.82 61.19 59.87 60.76 66.89 71.09 75.66 80.16 84.97
Revenue per 1 new store growth, % -4% 17% 7% -11% 15% 6% 7% 6% 6% 6%
Additional Revenue per 1 old store 6.15 3.02 2.23 8.67 5.05 5.33 5.70 6.03 6.40 6.78
Revenue estimation from the Regression model 701 275 773 275 858 275 943 275 1 024 025 1 100 525
Average Revenue 701 275 793 730 902 875 1 018 969 1 138 490 1 261 670
2
Hypermarkets
Revenue by old/new add. Rev method 46 185 75 419 106 176 139 655 161 579 186 436 209 393 229 291 252 487 278 693
Revenue growth, % 94.1% 63.3% 40.8% 31.5% 15.7% 15% 12% 10% 10% 10%
Like-for-like growth, % 6.7% 5.4% 4.6% 14.1% 1.5% 2% 2% 2% 3% 3%
Like-for-like growth, mln RUB 1 582 2 476 3 477 14 918 2 109 3 232 3 674 3 562 5 880 7 850
Revenue growth contributed by new stores, % 87.5% 57.9% 36.2% 17.5% 14.2% 13% 10% 8% 8% 7%
Revenue growth contributed by new stores, mln RUB 20 811 26 758 27 280 18 562 19 815 21 625 19 283 16 336 17 316 18 355
Average Additional Revenue per 1 new store 520 743 779 640 683 721 771 817 866 918
Revenue per 1 new store growth, % 56% 43% 5% -18% 7% 6% 7% 6% 6% 6%
Additional Revenue per 1 old store 32 28 28 93 11 15 15 13 20 25
L-f-L Revenue per 1 old store, mln RUB 507 541 626 752 746 791 846 897 951 1008
Revenue by marginal rev method 161 579 190 079 213 686 233 593 253 491 278 487
Average Revenue 161 579 188 257 211 539 231 442 252 989 278 590
Appendix 41: Revenue Calculations (L-f-L Forecasting)
69 Higher School of Economics 2016Sources: Company, Bloomberg, team estimates
Actuals Estimates
2011A 2012A 2013A 2014A 2015E 2016F 2017F 2018F 2019F 2020F3
Family storesRevenue 798 3 099 10 678 25 534 44 825.3 61 062 78 350 95 250 114 390 135 484 Revenue growth, % 288% 245% 139% 76% 36% 28% 22% 20% 18%Like-for-like growth, % 7.4% 8.9% 0.6% 0.0% 0.0% 0.0% 0.0% 0.0%Like-for-like growth, mln RUB 230 947 158 9 14 15 17 20 Revenue growth contributed by new stores, % 237% 130% 75% 36% 28% 22% 20% 18%Revenue growth contributed by new stores, mln RUB 7 350 13 909 19 133 17 749 16 758 15 774 16 721 17 724 Average Additional Revenue per 1 new store 282.7 272.7 329.9 348.0 372.4 394.4 418.0 443.1Revenue per 1 new store growth, % 11.5 20.6 1.6 6% 7% 6% 6% 6%Revenue per 1 old store 166 253 265 279 299 317 336 356Revenue by marginal rev method 52% 45 899 65 399 75 299 85 499 96 899 108 299 Average Revenue 45 362 63 230 76 825 90 374 105 645 121 892
4DrogerieRevenue 893 5 733 11 873 19 757 40 122 81 856 150 622 156 715 178 722 191 722 Revenue by marginal rev method 74 124 141 130 143 968 164 985 183 188 Average Revenue 77 990 145 841 150 341 171 853 187 455 Revenue growth, % 542% 107% 66% 103% 94% 87% 75% 70% 65%
5
Wholesale 93 175 166 806 200
Appendix 41: Revenue Calculations (L-f-L Forecasting)
70 Higher School of Economics 2016Sources: Company, Bloomberg, team estimates
0
50
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2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Positive scenario Negative scenario Neutral scenario
Revenue forecast with linear regression and seasonality
-25%
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-5%
5%
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35%
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2007 2008 2009 2010 2011 2012 2013
2014 2015 2016 2017 2018 2019 2020
Seasonality effects on revenue dynamics
Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecSeasonal indices
0.84 0.86 0.96 0.94 0.98 0.98 1.03 1.02 0.97 1.02 1.03 1.35
_cons -8450.21 1359.707 -6.21 0.000 -11142.8 -5757.62
season 660.0675 19.50382 33.84 0.000 621.4446 698.6904
sales Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 6.9198e+10 119 581497205 Root MSE = 7400.9
Adj R-squared = 0.9058
Residual 6.4633e+09 118 54773646.9 R-squared = 0.9066
Model 6.2735e+10 1 6.2735e+10 Prob > F = 0.0000
F( 1, 118) = 1145.35
Source SS df MS Number of obs = 120
. reg sales season
We applied linear regression model to forecast Magnit revenue. We use resultsfrom regression as sanity check to the main approach of revenue forecast.Regression was applied for three different scenarios. We tended to use Neutralscenario in our forecasting purposes.
Obtained seasonality coefficients tended to stay relatively stable through theperiod 2007-2015E.
The linear regression equation from the model estimation:
𝑅𝑒𝑣𝑒𝑛𝑢𝑒𝑖 = 𝛼 + 𝛽 ∗ 𝑝𝑒𝑟𝑖𝑜𝑑𝑖
With seasonality adjustments:
𝑅𝑒𝑣𝑒𝑛𝑢𝑒𝑎𝑑𝑗𝑢𝑠𝑡𝑒𝑑 = 𝛼 + 𝛽 ∗ 𝑝𝑒𝑟𝑖𝑜𝑑𝑖 ∗ 𝑠𝑒𝑠𝑜𝑛𝑎𝑙𝑖𝑡𝑦 𝑖𝑛𝑑𝑖𝑐𝑒𝑠.
Regression outputs
Appendix 43: Revenue Calculations (Regression Analysis)
71 Higher School of Economics 2016Sources: Company, team estimates
Appendix 44: Revenue Analysis
-
2,000
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Revenue dynamics (left) Share performance (right)
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Revenue, USD mln (lhs) Revenue, RUB bln (rhs)
USD nominated
RUB nominated
Revenue nominated, RUB vs USD Revenue dynamics and Ordinary Shares track record
Appendix 44: Revenue analysis
72 Higher School of Economics 2016Sources: Company data, Bloomberg, team estimates
0%
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2009 2010 2011 2012 2013 2014 2015Revenue (RUB, bln) lhs Revenue y/y growth, % rhs
Nominal revenue and revenue growth dynamics
Appendix 44: Revenue AnalysisAppendix 45: Stock correlation analysis
73 Higher School of Economics 2016Sources: Moscow Stock Exchange, team estimates
MGNT MCX SBR GAZP GMKN ROSN SNGS LKOH NVTK VTBR TATN CHMF ALRS URKA
MGNT 1
MCX 0.64 1
SBR 0.38 0.71 1
GAZP 0.51 0.87 0.63 1
GMKN 0.28 0.54 0.16 0.38 1
ROSN 0.38 0.74 0.52 0.70 0.35 1
SNGS 0.41 0.68 0.45 0.54 0.35 0.59 1
LKOH 0.43 0.78 0.42 0.65 0.47 0.65 0.55 1
NVTK 0.47 0.75 0.44 0.62 0.42 0.50 0.43 0.54 1
VTBR 0.25 0.54 0.49 0.49 0.18 0.37 0.33 0.36 0.34 1
TATN 0.35 0.66 0.41 0.54 0.40 0.58 0.58 0.62 0.48 0.27 1
CHMF 0.25 0.49 0.24 0.38 0.39 0.24 0.26 0.35 0.46 0.26 0.29 1
ALRS 0.16 0.31 0.09 0.25 0.18 0.23 0.26 0.25 0.29 0.22 0.19 0.23 1
URKA 0.27 0.45 0.25 0.36 0.31 0.32 0.28 0.32 0.32 0.16 0.39 0.19 0.11 1
Average correlation of MGNT:ME with Russian Blue-chip stocks is 0.35Correlation of MGNT:ME with Russian broad market index MICEX is 0.64
0
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16
5/5/2009 5/5/2010 5/5/2011 5/5/2012 5/5/2013 5/5/2014 5/5/2015
Appendix 44: Revenue AnalysisAppendix 46: Stock spread between shares and GDRs
74 Higher School of Economics 2016Sources: Moscow Stock Exchange, team estimates
Table 1: Correlation matrix and volatility
MGNT:ME MGNT:LI MGNT**
MGNT:ME 1
MGNT:LI 0.853 1
MGNT** 0.804 0.989 1
MGNT:ME MGNT:LI MGNT** USDRUB
2.43% 3.02% 2.66% 1.28%
27.5
23
33.2
23.1
46.3
33.8
MGNT:LI MGNT:ME
Last 30 Days Last 12 Months Last 3 Years
Table 2: Average value traded, $mn
Exhibit 1: Spread between MGNT:LI and MGNT**, USD
We consider MGNT** as an implied price for GDR (MGNT:LI)
Appendix 44: Revenue AnalysisAppendix 47: GDRs return suffers from RUB devaluation
75 Higher School of Economics 2016Sources: Moscow Stock Exchange
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MGNT:LI MGNT** MGNT:ME USDRUB(rhs)
We consider MGNT** as an implied price for GDR (MGNT:LI)
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