Stern MBA Valuation final project

7/25/2019 Stern MBA Valuation final project

1/31

Valuation Final Project Fall 2015

Member Company Page Number

Amelia Tang JC Penny 2

Chris Yue Wu Activision Blizzard

Francisco Mizgier AcuaChile

Jeffrey ao u Cinda Asset Management

Ji Ming !i !in"ed#n

$icholas M %eichard &ru'u'

(Amelia)s *rite+u, to 'e inserted-

Activision li!!ar" #nc$

1$ Company %vervie&

1


2/31

Activision Blizzard. #nc/ is a *orld*ide develo,er and ,u'lisher of online. PC. video game console.

handheld. mo'ile and ta'let games/ The com,any offers games that o,erate on the Microsoft 0'o1 ne

and 0'o1 345. $intendo Wii 6 and Wii. and 7ony Play7tation 8 and Play7tation 3 console systems9 the

PC9 the $intendo 3:7. $intendo :ual 7creen and 7ony Play7tation ;ita handheld game systems9 and

mo'ile and ta'let devices/

The com,any has three main divisions< Activision. Blizzard and distri'ution/ Activision. #nc/ develo,s.mar"ets and sells interactive soft*are contents through retail sales and digital do*nloads/ &ames include

franchises Call of :uty. 7"ylanders and :estiny/ Blizzard =ntertainment. #nc/ is the ,u'lisher of World of

Warcraft. :ia'lo. 7tarCraft. eroes of the 7torm and earthstone/ The Activision Blizzard :istri'ution

'usiness consists of o,erations in =uro,e that ,rovide *arehousing. logistical. and sales distri'ution

services to third+,arty ,u'lishers/The most recent financial statements used in the analysis are from the third >uarter of 25?@/ Belo* is the

!TM ,erformance of the stoc"ual to 2/?5. as a ,ro1y for the %is" Free %ate/ The 6nlevered Beta. e>ual to ?/@. re,resents the

average !evered Beta for multimedia and gra,hic soft*are industry in the 6/7/. unlevered 'y their total

:e't+to+=>uity ratio/ This num'er. levered 'ased on the com,any)s current ca,ital structure. re,resents

AT;6)s !evered Beta. currently e>ual to ?/253/ The Country %is" Premium ta"es into account the

com,any)s revenue com,osition/ Based on the latest financial statements. @2/3 of its revenues are

generated in $orth America. 3/2D come from =uro,e including =astern =uro,e and %ussia. *hile

D/8? come from Asia Pacific/ As a result. the Weighted Country %is" Premium used in the valuation.

*hich re,resents a *eighted average of these countries) e>uity ris" ,remiums. is e>ual to 5/E32/

#m,lied ris" ,remium. currently @/8?. is calculated from current 7P @55 inde1 and earnings/ Adding

*eighted C%P to #%P. the total e>uity ris" ,remium is 4/?8

2


3/31

As a result. Therefore. the com,any)s Cost of =>uity in 67 is e>ual to D/8D/

2/2 Cost of :e'tThe com,any)s Cost of :e't is calculated in 67/ 7ince AT;# does not have a 'ond rating availa'le. the

analysis considers the firm)s credit rating as a ,ro1y for default s,read to 'e added to the ris" free rate/The com,any)s current credit rating is BBG. *hich translates into a credit default s,read of 2/E@/ The

cost of de't. as a result. is 8/@. as detailed 'elo*

2/3 Cost of Ca,italThe com,any)s Cost of Ca,ital. calculated in 67 'ased on the *eighted average of the Cost of =>uity

and Cost of :e't/ Currently. AT;#)s Cost of Ca,ital is e>ual to /EE/ The details are descri'ed 'elo*uaculture concessions that o*n a total area of ?48/4 hectares/

The com,any o,erates three stores in 7outhern Chile/ #t serves its customers in a,,ro1imately 35

countries. including Costa %ica. Panama. and the 6nited 7tates/ A>uaChile 7/A/ is 'ased in Puerto Montt.Chile/

HPac"aged Foods and Meats. $egative earningsI

2$ 'CF Valuation

We im,lemented a 2+stage FCFF discount model *ith normalized earnings 'ecause historically

the ,rice of 7almon fish. A>uchile)s main ,roduct. has 'een very volatile Hsee chart 'elo*I/ Currently.

high costs and lo* ,rices are creating a O,erfect storm for 7outh American country)s farmers and

,rocessors/ Moreover. the industry suffered a maor 'usiness loss and re,utation 'lo* *hen Costco

s*itched to $or*egian fish and ditched Chilean su,,lies 'ecause of the amount of anti'iotics used in

Chilean farms/

o*ever. there is a consensum amid anayst that gro*th *ill continue to accelerate/ Much of that demand

for salmon *ill come from the *orld)s gro*ing middle class/ The Broo"ings #nstitution thin"s the middleclass *ill gro* 'y @5 to 3/ 'illion ,eo,le in ust ?5 years/ We also e1,ect that A>uaChile *ill

e1,erience a consolidation of the Chilean 7almon #ndustry as com,anies go out of 'usiness and that the

com,any *ill 'etter control its cost and re'uild trust in the mar"et/ We e1,ect that earnings *ill recover

>uic"ly to normal levels from ne1t year/

7


8/31

To value this com,any. *e normalized not only its current revenues. 'ut also the return on ca,ital and

reinvestment rate/ We estimated the normalized values 'y loo"ing at average earnings over a ,eriod of ?5

years and considered some analystsQ e1,ectations of com,any gro*th and salmon fish ,rices/

The in,uts for the high gro*th and sta'le gro*th ,eriods are listed 'elo*/

a. Inputs

.ig, /ro&t, -table /ro&t,

!ength of igh &ro*th Period ?5 Forever

&ro*th %ate ?5/55 2/2

:e't %atio used in Cost of

Ca,ital Calculation8/88 35/55

Beta used for stoc" ?/4E ?/55

%is"free rate 2/2 2/2

%is" Premium 4/88 4/88Cost of :e't E/E D/55

=ffective Ta1 rate Hfor cash

flo*I25/55 2@/55

Marginal ta1 rate Hfor cost of

de'tI25/55 2@/55

%eturn on Ca,ital ?3/55 E/55

%einvestment %ate 8/33 32/@E

b. Output

Firm ;alue ?2.?48.EE4 million

;alue of o,erating assets of the firm [email protected] million

;alue of Cash. Mar"eta'le 7ecurities $on+

o,erating assets

??.455.555 million

Current Mar"et Price Kshare 5/2

=stimated Mar"et Price Kshare 5/2?

Price as of =stimated ;alue ?33

8


9/31

c. Commentary

A>uachile 'ehaves li"e commodity com,anies/ When 7almon fish ,rices are on the u,s*ing. the

com,any and its ,eers have high earnings. *hereas during a do*nturn. the industry e1,eriences lo*

returns/ 7o its value is highly lin"ed to the ,rice of 7almon fish and *e see very volatile earnings and

cash flo*s/ &iven the lo* 7almon ,rices it is not a sur,rise that the com,any re,orted a net loss for R3 of25?@ of 2?/2D million. com,ared to a loss of 2/54m in the same >uarter of the ,rior year/

With volatile earnings over time and current negative earnings. *e tried to ans*er *hat *ould A>uaChile

earn in a normal year/ As mentioned 'efore. *e e1,ect that earnings *ill recover >uic"ly to normal levels

H25?4I/

c. Sensitivity Analysis

The "ey drivers for A>uaChile are the normalized =B#T and sta'le gro*th rate/

HCurrent ,rice

,er share L 5/2

and =B#T L 2

millionI

($ )elative Valuation

a. Summary

We ran regresions against a sam,le of ?5 Pac"aged Fish com,anies in order to com,are A>uaChile)s

mar"et ,rice to the sector generally/ =nter,rise ;alue to 7ales H=;K%evenuesI against ust one varia'le.

=B#T:A margin. ,roduced the highest %+s>uared/ The =;K%evenues is versatile enough 'ecause there are

significant differences in margins across com,anies/

The resulting e>uation and its a,,lication to A>uaChile are re,roduced 'elo*/

9

Revenue Growth (year 1

BIT(nora!"#e$) ?5 ?2

?@ million 5/?8 5/?@ 5/?E

?E million 5/?4 5/? 5/25

25 million 5/?D 5/2? 5/28


10/31

b. Regression Analysis

=;KTotal %evenues L 5/3DD4@ G 4/DD34 =B#T:A Margin

Coefficient 7tandard =rror T 7tat P+!evelConstant 5/3DD4@ 5/2@D2@ ?/@8?@D 5/?4?E8

%evenue &ro*th 4/DD34 ?/D2D42 3/4283 5/554E8

R 5/E3@

R-square 5/42?@

Adjusted R-square 5/@E8?D

S 5/@243E

N ?5

Actual =;K7ales 5/D51

Predicted =;K7ales 5/421

Predicted ;alue Kshare 5/?2

*$ Maret Valuation

We regressed A>uaChile against the entire mar"et/ We used =;K=B#T:A. using :amodaran

nline)s January 25?@ full mar"et regression e>uation/

=;K=B#T:AL ?D/?2 G 4/3@ g + 3/D2 :F% + ?/58 Ta1 %ate

Actual =;K7ales 21

Predicted =;K7ales ?8/?1

Predicted ;alue Kshare 5/23

5$ Final Analysis

a. Summary of ata

;alue Mar"et Price as of ;alue

Current Price 5/2 +

:CF ;alue 5/2? ?33

7ector %egression ;alue 5/?2 233

Mar"et %egression ;alue 5/23 ?22

10


11/31

b. Recommendation

The com,any is overvalued under all metrics and our recommendation is to 7=!! A>uachile/

Why it seems so overvaluedS We have strong reasons to 'elieve that A>uaChile is 'eing under the radar

of larger ,layers/ We mentioned 'efore that the industry *ould li"ely enter into a consolidation ,rocess

and then larger and more consolidated com,anies can get a 'etter hold of the mar"et/ #f this is the real

reason. A>uachile)s stoc" ,rice might seem overvalued 'ecause of s,eculation that an ac>uisition deal is

imminent/

Cinda Asset Management ;aluationCinda Asset Management *as founded in ?DDD. initially created to hel, dis,ose of 'ad de'ts on

maor Chinese Ban"s follo*ing the Asian Financial Crisis/ #t is largest of the four state+mandated 'ad+

de't) 'an"s and the only one to 'e listed aside from uarong Asset Management/

Cinda)s core 'usiness is to 'uy loans from 'an"s and financial institutions at a discount and then

either hold to maturity or renegotiate the terms *ith the issuing com,anies/ ther than its core distressed

11


12/31

de't management 'usiness. Cinda has also e1,anded into 'ro"erage. insurance. commercial 'an"ing. and

other asset management services/

Cinda is listed as ?3@D U on the ong Uong stoc" e1change. 'ut the maority of its 'usiness

Hmore than DDI is from mainland China/ 7ince its #P in 25?8. its stoc" ,rice has fallen to U:2/E?/

:CF ;aluation?/ Cost of =>uity L %is" Free %ate G

!am'da C%P G Beta H=>uity %is"

PremiumI

7ince the maority of Cinda)s 'usiness is in

mainland China. *e *ill do the valuation in %MB

'efore converting the im,lied stoc" ,rice to U:/

12

)is Free )ate

&C$Y?5Y% China ?5 Year Bond

Yield< 3/54

67&&?5Y% 67 ?5 Year Bond

Yield 2/2?

China C:7 ?/@8

67 C:7 5/38

A"j$ 'eault -prea" ?/25

C'- ase" )M ) 1$34


13/31

#n order to find the cost of e>uity. *e *ill first find the %MB ris"+free rate/ 6sing C:7+im,lied

sovereign default s,reads. *e get a %MB ris"+free rate of ?/4/

We also *ant to find the country ris" ,remium for China HC%PI and the Cinda)s e1,osure to that

ris" H!am'daI/

We *ill use 7C=# #nde1 as a measure of

e>uity mar"et volatility/ We chose 7C=# over the

generic 7# #nde1 for all ong Uong listed firms

'ecause 7C=# e1clusively trac"s mainland Chinese

firms listed in ong Uong. *hich is more a,,ro,riate

to our analysis/

7ince the management recognizes that there

are effectively 3 se,arate divisions *ithin the

com,any N distressed asset management. asset

management. and other financial services/ We *ill use

three sets of com,ara'les to find Cinda)s levered 'eta/

And. 'ecause Cinda)s distressed asset management

division 'uys loans mostly from 'an"s. *e decided to

use 'an"s as that division)s com,ara'le set/

)esults rom

Comparables

Me"ian

C,ina eta

-tan"ar

"

6rror

6merging

Maret

eta

-tan"ar

"

6rror

Me"ian P7

)atio

Ban"s 5/D3 8 5/D@ 2 ?/33

Asset Management ?/@4 35 5/D E 2/?5

Financial 7ervices ?/2? 2 5/D8 8 ?/52

While finding a 'ottoms+u, levered 'eta for each division. *e noticed that there *as significant

difference 'et*een Chinese and =merging Mar"et 'etas. es,ecially for Asset Management and Financial

7ervices/ We s,eculate that 'eta for Chinese firms are high due to the e>uity 'u''le 'uild+u, and the

su'se>uent colla,se this ,ast year/ o*ever. *e e1,ect this to 'e an anomaly. so in the long term. levered

'eta for Chinese firms *ill move to the emerging mar"et average/

13

Country )is Premium

China :efault 7,read ?/25

6+uity Maret Volatility 8(40'9

7C=# #nde1 2@/E3

C,ina -overeign on" Volatility

8(40'9

?5+year &overnment Bond ??/2

C)P 2$:4

China =1,ort &:P 2@/@

Cinda verseas %evenue ?/?5

;amb"a 1((

6+uity )is Premium

#m,lied Mature Mar"et =%P 4/5E


14/31

Cost o 6+uity

oo Value

8)M ear

1

)e

>ear

10

:istressed Asset Management [email protected]

?/3

3 8@2.@[email protected] 8E?? ??

#nvestment Asset Management [email protected].?55

2/?

5 [email protected]? 34?@ ??

Financial 7ervices ?4.E@@.?55

?/5

2 ?E?.E54.48@ ??3 ??

?otal 1( 11

6sing median PKB values from the three com,ara'le sets. *e estimated the a,,ro1imate mar"et value

for each 'usiness division and used them as *eights to find the com'ined cost of e>uity for Cinda in year

? and year ?5/

2/ :CF ;aluation N FCF= ModelCinda has gro*n at a 'rea"+nec" s,eed for the ,ast fe* years/ #ts total asset has gro*n 'y an

average of 8@ and its net income has gro*n @3yoy in the most recent re,orting >uarter/ To

finance its gro*th. Cinda has issued ne* shares every year in addition to ta"ing on more leverage/

The com,any has consistently re+invested more than its net+income and its ca,ital ade>uacy ratio has

'een falling every re,orting cycle/

HThousands %MBI

:ec+3?+

25?2

:ec+3?+

25?3

Jun+35+

25?8

:ec+3?+

25?8

Jun+35+

25?@ TTM

Net #ncome E.2?E.?34 D.?55.DE2 @[email protected] ?2.?82.E8D .2@@.442 [email protected].

A"justments

G ,erating !ease =1,ense H?+

tI ?E8.2E [email protected]@3 ?22.42E 2.242 ?88.?3? 35D.

A"juste" Net #ncome E.3D?.823 D.384.22@ @.82.@35 ?2.83?.5?? .3DD.ED3 [email protected].

14


15/31

! "o" #ro$t% 24 33 @3

:ividends Paid ?.54.8?5 [email protected] 3.@E?.28

7hares #ssued +?5.34.48 +?8.428.23 +2.?3.E85

$et :ividends Paid [email protected] +??.5.D45 ?.3E.@88

! &ayout Ratio -''(! -')(! ''!

! Reinvestment Rate )'(! ))(! *+!

Boo" =>uity 45.8.E83 2.E42.?2? D5.EE.38? ?5?.43.242 ??5.@@@.E4@ ??5.@@@.

+ #nvestment %evaluation %eserve 854.5@8 E35.@E8 ?.58D.54E 3.DE5.D53 4.E8.88? 4.E8.

A"juste" oo 6+uity 45.8E.4D 2.53?.@8E D.E2D.2E8 DE.D2.3@D ?53.5E.328

?53.5

)%6 12 11 1( 1

Total Assets [email protected]?8.3@ [email protected] 82.?@@.@D5 @88.82E.8?E [email protected]@E.833

[email protected]@

6+uity7?otal Assets 2* 22 1@ 1@ 1:

We have made several adustments to Cinda)s re,orted num'ers/ We have added 'ac" o,erating

lease less ta1es to its net income and ca,italized o,erating leases as additional de't lia'ilities/ We have

also ta"en out #nvestment %evaluation %eserve from its 'oo" e>uity 'ecause that figure re,resents

unrealized gains on availa'le+for+sale securities/

Cinda)s gro*th has coincided *ith the ra,id ram,+u, in de't in China since 255. es,ecially inthe ,rivate sector/ Follo*ing the &FC. the Chinese government has turned to credit+fueled gro*th to

"ee, u, economic activity/ #n turn. chea, credit has led to less scru,ulous lending 'y the maor 'an"s/

o*ever. as economic gro*th has slo*ed do*n nevertheless. many lenders faced trou'le meeting its

o'ligations. leading to an e1,losion in the su,,ly of 'ad+de't/

We reasoned that since the Ministry of Finance o*ns E@ of Cinda and the com,any has a state+

mandate to manage 'ad de't accrued 'y the maor 'an"s. Cinda *ill continue to soa" u, the gro*ing

$on+Performing !oans/ 6sing #MF ,roections and assuming that Cinda *ill maintain its current

mar"et+share. *e estimate the gro*th of Cinda)s assets in the follo*ing ta'leuisition gro*th. *e 'elieve this is the most

reasona'le estimate of Cinda)s future decisions/

Before calculating for Free Cash+Flo*+to+=>uity. *e need to account for t*o other varia'les N

reinvestment rate and return on e>uity/ 7ince *e have already estimated for Cinda)s total assets. *e can

use e>uity+to+total+assets ratio to 'ac"+trac" ho* much Cinda needs to reinvest in e>uity each year/ As

mentioned ,reviously. Cinda has 'een 'oth issuing shares and levering u, to su,,ort its asset gro*th/

o*ever. Cinda)s leverage is limited 'y P%C regulation to maintain at least ?2/@ e>uity for maor

financial institutions/ Thus. *e assume that Cinda *ill continue to lever u, to the regulatory minimum

'efore coming 'ac" to ,resent levels/

Cinda)s overall %= at ?@ is significantly 'elo*

industry average. and even 'elo* its direct

com,etitor uarong. the 2ndlargest state+o*ned

distressed asset management firm. *hose %= is

at ?D/ o*ever. *hen *e se,arate Cinda)s

'usiness divisions. *e notice that it is its ne*

entry into Hnon+distressedI asset management and

financial services that is dragging its overall %=/

#n the medium term. *e assume that Cinda)s recent e1,ansions into asset+management and financial

services *ill catch u, to industry averages to achieve around ? %= 'efore falling to e>ual cost of

ca,ital in sta'le gro*th/

16

turnon6+uity ans

Asset

Managemen

t

Financial

-ervices

merging Mar"ets ?@/2D ?D/D ?E/D

ina ?E/?8 25/52 ?/?

nda 2?/E8 E/44 ?5/3


17/31

From our :CF valuation. Cinda should 'e trading at U:3/2?. *hich im,lies a ?@ u,side on

the current stoc" ,rice/ o*ever. 'ecause FCF= is negative for most of the gro*th stage. this model isvery sensitive to the sta'le+stage varia'les that determine the terminal value/ 7o. *e *ill run a sensitivity

ta'le for sta'le stage gro*th and cost of e>uity/ The sensitivity analysis sho*s that there is a large

variance to ,rice as cost to e>uity changes/

-table -tage /ro&t,

-table B($21 0 2 ( 5 4

-tage : 4/42 4/E3 4/@ 4/DE E/5

Cost @ 8/83 8/@? 8/45 8/4 8/E4

o 11 3/5E 3/?3 3/25 3/24 3/326+uity 1( 2/?4 2/25 2/2@ 2/35 2/3@

15 ?/@? ?/@8 ?/@ ?/42 ?/44

#n addition. *e *ill also chec" the sensitivity of our valuation to the t*o assum,tions made *hen

calculating Cinda)s total asset gro*th N $P! &ro*th in China and Cinda)s mar"et+share in distressed+

de't management/ This analysis sho*s that Cinda)s ,rice could ,lummet due to either increased

17

F 8Million

M9

TTM

?2K3?

K?@

?2K3?

K?4

?2K3?K

?E

?2K3?K

?

?2K3?K

?D

?2K3?K

25

?2K3?K

2?

?2K3?K

22

?2K3?K

23

?2K3?K

28 7ta'le

al Assets

[email protected]

@E

E28.@

55

D@?.5

32

?.25@.

4D3

?.@53.

?5

?.@5.

3

2.25.

854

2.2D4.

E82

2.3.

4?2

2.88.

?@4

2.@3.

@23

uityKTotal Assets ?E ?4 ?@ ?8 ?3 ?3 ?3 ?@ ?E ?D ?D ?D

o" =>uity

??5.@

@4

[email protected]

25

?82.4

@@

?4.ED

E

[email protected]

8

285.4?

@

2E.5D

3

388.@?

?

854.54

8

8E?.DD

5

8D5.4

D

nvestment Rate

116

%

181

% 131% 103% 141% 116% 125% 118% 113% 30% 30%

#ncome

[email protected]

8

?8.EE

5

25.53

2

[email protected]

32.53

?

85.?4

D

[email protected]

D

@2.32

D

@.2D

2

43.43

@

4?.@8

8

43.@@

3

F6

1(3

3

2(23

1422

:

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10@*

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:1@@

1(21

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102:

*

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*(23

5

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= ?@ ',! '(! '! '*! '*! '! '(! ',! '! '/! ''!

et #ncome

*th

'*.*

!

/,.(

!

)*.

!

).,

!

),.

!

'.'

!

'.)

!

''.

! +.)! -/./! /./!

st o 6+uity ?3 '/! '/! '/! ')! ')! ')! ')! ')! ''! ''! ??

sent Value

21@0

12:(

1

5*43 4:3

@1(1

(551

53((

*042

2@53

1(31

5

12@4

34

um of P;< D4.D

+uity Value D4.D

hares utstanding HmillionI< 34.2@E

m,lied 7hare Price H%MBI< 2/4E

MB to U: HCurrentI< ?/25

mplie" -,are Price 8.D'9 3/2?

urrent -toc Price 8.D'9 2/5

mplie" Epsi"e ?@


18/31

com,etition in the sector or a s,iraling deterioration of de't >uality that over*helms the Cinda)s a'ility to

a'sor' them/

Cin"a a" 'ebt Maret -,are

B($21 20 2( 24 2@ (2

0$05 2/2@ 2/@4 2/2 3/52 3/?E

a" 0$10 2/@? 2/2 3/54 3/23 3/33

;oan 0$25 2/48 2/D2 3/?2 3/23 3/24

/ro&t, 0$*0 2/4 2/D2 3/54 3/?5 3/58

0$55 2/4E 2/8 2/D? 2/@ 2/4

0$:0 2/45 2/E5 2/4 2/@2 2/22

3/ 7ector %egression N Price+to+Boo" %atio

We *ill use ,rice+to+'oo" ratio to do relative valuation 'ecause more than other sectors. ,rofita'ilityof financial services firms are driven 'y their financial assets. *hich are often mar"ed+to+mar"et on the

'alance sheet/ We ran regression against 2E@ glo'al financial services firms including 'an"s. asset

managers. 'ro"erages. and other distressed+de't managers/ :es,ite trying a variety of different varia'les.

from 'eta to ,ayout ratio to different gro*th metrics. it *as difficult to achieve a high %+s>uared/ We

sus,ect this is 'ecause of the diverse range of financial services firms. 'ut since Cinda *as involved in so

many different as,ects of finance. *e had to use a 'road definition/

After com,aring different regressions. *e found that %eturn+on+=>uity. %einvestment %ate. Cost of

=>uity. 3Yr Asset &ro*th. and a dummy =merging+Mar"et varia'le gave the 'est P+value and highest %+

s>uared/ The ta'le 'elo* sho*s the regression resultsuity ?3 +5/?? 5/5@ 5/58

3Yr Total Asset &ro*th 8@ 5/5 5/5? 5/55

=M H:ummy ;aria'leI ? +?/8E 5/@@ 5/5?

6pecte" P7 5/5@1

Actual P7 5/EE1

18


19/31

'CF #mplie" P7 5/1

Based on the regression. Cinda should have a Price+to+Boo" value of 5/5@. 'ut its actual Price+to+

Boo" ratio is currently at 5/EE/ The dis,arity is mostly due to Cinda)s e1traordinarily high %einvestment

%ate at D/ According to the regression. the mar"et is ,unishing firms in the financial services sector for

reinvesting too much and not giving 'ac" to e>uity investors/ =ven if the 5/5@ regression result seems too

lo*. the data over*helmingly suggests that Cinda should trade at a very lo* PKB multi,le/

2

14

36 35 39

28

20

12 15

5 9 7 7

%r"&e'to'Boo Rat"o "*tor+ra

#f *e loo" at a histogram of all

PKB ratios in our sam,le. Cinda is already trading at left+end of the range H5/EE1I/ Thus. the regression

result may not necessarily conflict *ith our :CF valuation. *hich im,lies a PKB of 5// =ven at 5/1

PKB. Cinda is still trading at the left+tail of the PKB range *here only @ of the com,anies in our sam,le

are trading at that level or 'elo*/

8/ Mar"et+Wide %egressionsere. *e *ill use :amodaran January 25?@ nline !i'rary)s mar"et+*ide ,rice+to+'oo"

regression e>uation< PB;L 5/4? G ?5/28 g=P7+ ?/3? Beta G ?/33 Payout G ?2/D2 %=

We find that the e1,ected PKB ratio using the

mar"et+*ide regression should 'e @/DE1. much higher

than the other valuation methods/

19

Cin"a

Coeicien

t

Constant 5/4?

gH=P7I =1,ected ?4/4 ?5/28

Beta ?/2 ?/3?Payout ?? ?/33

%= ?@ ?2/D2

6pecte" P7 @/DE1


20/31

@/ Conclusion N Buy

Met,o"ology .D'B per -,are #mplie" Epsi"e 8'o&nsi"e9

'CF 3/2? ?@

-ector )egression 5/? +D8

Maret&i"e )egression 2?/3 45

Current Maret Price 2/5

Though the three methodologies give a *ide range of valueK,er share that seemingly do not agree

*ith each other. *e can gain useful insights from each of the three e1ercises/ The sector regression

suggests that Cinda should 'e trading at significantly lo*er PKB ratio than the industry average. *hich is

ha,,ening already/ Cinda)s PKB ratio at 5/EE1 is at the 'ottom @ of our sam,le of 2E@ financial services

com,anies/ n the other hand. the mar"et+*ide regression suggests that. given Cinda)s high gro*th and

relatively high %=. its share ,rice should 'e trading much higher than its current level/ ur :CF

valuation confirms this vie*< though Cinda should trade at a lo* PKB multi,le. the mar"et has over+

,unished the com,any/

#ndeed. Cinda)s credit ,osition has deteriorated and its FCF= has 'een negative for consecutive

years/ o*ever. the reason for levering+u, and issuing more e>uity is not 'ecause the com,any is in

trou'le 'ut 'ecause there has 'een a ra,id e1,ansion of distressed+de't in China/ The e1,losion in the

su,,ly of $P! from maor Chinese 'an"s. according to the #MF. should continue at least until 2525/ As

the current mar"et+leader. Cinda is *ell+,ositioned to ta"e advantage of the 'ooming mar"et size and

come out of the Chinese de't+crisis *ith handsome ,rofits/ We recommend to 'uy Cinda Asset

Management/

20


21/31

;ine"#n Corporation

1$ Company %vervie&

!in"ed#n o,erates an online ,rofessional net*or" through *hich the Com,any)s mem'ers are

a'le to share their ,rofessional identities online. engage *ith their ,rofessional net*or"s. access shared

"no*ledge and insights. and find 'usiness o,,ortunities/ The Com,any is the *orld)s largest ,rofessional

net*or" on the #nternet. *ith a,,ro1imately 855 million mem'ers in over 255 countries and territories/

Competition

!in"ed#n holds a dominant ,osition in the ,rofessional social net*or" mar"et/ o*ever. entry to

'arrier is lo*. as any net*or" *ith e1isting user 'ase could develo, directly com,etitive ,roducts/

=1isting com,etitors include ;iadeao from France and 0#$& from &ermany/

;iadeao *as founded in 2558 in Paris/ #t had gro*n its ,resence through ac>uisition into China

HTiani/comI. 7outh America H#CTnetI. #ndia HA,naCircleI. and Canada Huny"/comI/ Based on the latestavaila'le figures from :ecem'er 25?8. ;iadeo has 4@ million mem'ers *orld*ide/ H2@ million in ChinaI/

0#$&. a ,u'licly traded com,etitor 'ased in &ermany. has an estimated 3@ million users as of

Mid+25?8/ The com,any has siza'le ,resence in and only in &ermany. Austria. and 7*itzerland/ 0#$&

had e1ited closed offices in China. 7,ain. and Tur"ey 'ac" in 25??/

These t*o ,roducts are very similar to !in"ed#n 'ut have only regional dominance in certain

mar"ets + ;iadeao in franco,hone countries and select emerging mar"ets/ !in"ed#n also com,etes *ith

online recruiting com,anies including #ndeed and Monster/

&iven !in"ed#n)s esta'lished and gro*ing user 'ase. and its e1hi'ition of net*or" effect. *hich

ma"es its services more valua'le as more ,eo,le use it. # foresee !in"ed#n 'ecoming the uggernaut in the

,rofessional social net*or" industry/ Achieving glo'al dominance is e1tremely challenging. 'ut # 'elieve

!in"ed#n *ill guard its ,osition in e1isting mar"ets. and that it can effectively enter ne*er mar"ets/

Furthermore. # see !in"ed#n dis,lacing traditional online recruiting tools li"e #ndeed and Monster/

usiness mo"el

Uey value ,ro,osition< connection to o,,ortunity

7ources of revenue< Talent 7olutions. Mar"eting 7olutions. and Premium 7u'scri,tions

21


22/31

Talent 7olutions< driven 'y su'scri,tion model

o iring N solutions for recruiters to access ,rofessional data'ases. ,ost o's. create

career ,ages. or to ,lace ,ersonalized ads

o !earning :evelo,ment N individual and enter,rise su'scri,tion to recently

ac>uired !ynda/com ,latform

Mar"eting 7olutions< cost ,er clic" or cost ,er advertisement model9 mi1 shifting to cost ,erclic"9 ty,ical duration of advertising contract is a,,ro1imately t*o months

o Advertisements Hcontent+'ased. gra,hic dis,lay. or te1t lin"I sho*n on *e'site and

on mo'ile ,latforms

Premium su'scri,tions< driven 'y length of contract ,eriod Hmonthly or annual su'scri,tionsI

o &rants users ,remium features including #nMain and visi'ility to a *ider net*or"

2$ 'CF Valuation

&uided 'y the ,rofessor)s model+selection tem,late. # elected to use an n+stage FCFF model for a

gro*th ,eriod of ?5 years/ !in"ed#n is a negative+earning. high gro*th com,any/

Narrative !in"ed#n *ill maintain its dominant ,osition in the ,rofessional social net*or" s,ace in

countries in *hich it already o,erate. and *ill effectively enter ne* mar"ets/ #t *ill moderately e1,and

the mar"eting solutions and sales solutions industry. su'stantially e1,and the talent solutions industry. and

have little effect on the online learning develo,ment industry/ #t *ill ta"e advantage of net*or" effect

to get a dominant mar"et share. and effectively monetize on its user 'ase through a com'ination of

freemium G talent solution G mar"eting solution 'usiness model/

Addressa'le mar"et< ??@ 'illion HMar"eting solutions< 8@ 'illion9 learning develo,ment< 35

'illion9 talent solutions< 2E 'illion9 sales solutions< ?@ 'illion9 of these mar"ets. 7ales solutions and talent

solutions are 7ales+as+a+service 'ased. and mar"eting solutions and learning develo,ment are consumer

*e' 'asedI (7ource< !in"ed#n A,ril 25?@ ,resentation-

&iven !in"ed#n)s user 'ase of 855 million users across 255 countries and territories. the regional

reach of its e1isting com,etitors. and the net*or"+effect nature of the ,rofessional social net*or"

'usiness. # foresee !in"ed#n ca,turing the maority of the talent solutions Htargeting recruiters and %

,rofessionalsI mar"et/ Furthermore. # do not 'elieve there are social net*or" ,latforms that have the

o,tion of e1,anding into the ,rofessional social net*or" s,ace. since it is un,rofessional) to com'ine

,ersonal and ,rofessional *e'+identities/ Thus. the threat of. say. Face'oo" entering the mar"et is limited/

H2K3 of mar"et L ? 'illionI #n 25?8. talent solutions generated ?/3 'illion in revenue/

7ales solutions is 'ased on Osocial selling< the ,rocess of using ,rofessional 'rand to fill your

,i,eline *ith the right ,eo,le. insights. and relationshi,s/ This solution *ould target ,remium+su'scri'ers

and enter,rise users/ # see !in"ed#n ca,turing half of the addressa'le mar"et/ H?K2 of mar"et L E/@ 'illionI

#n 25?8. sales solutions generated ??8m in revenue/

Mar"eting solutions< mar"eting to ,rofessionals for B2B or B2C considerations/ # have trou'le

seeing !in"ed#n 'alancing the amount andKor efficacy of advertisements *ith its clean. ,rofessional

,latform/ # see !in"ed#n ca,turing only a fifth of the addressa'le mar"et/ H?K@ of mar"et L D 'illionI #n

25?8. mar"eting solutions generated 8@@m in revenue/

!earning develo,ment< advancing ,rofessional develo,ment e+learning/ Currently. this

segment constitutes only !ynda/com/ # see an o,,ortunity for !in"ed#n to ,rovide an authoritative.

22


23/31

standardized e+learning model. allo*ing ,rofessionals to learn through online ,latforms and 'e

recognized for their *or"/ o*ever. # thin" this s,ace is very com,etitive/ HThin" of online university.

courser etc/I # *ill assume !in"ed#n can tri,le its e1isting revenue of ?8Dm over the ne1t ?5 years to

8@5m/

Target mar"et share< H?GE/@GDG5/8@IK??@L35/8

%evenue target 'y year ?5 L 3@ 'illion

a. Inputs

/ro&t, Perio"

810 years o ,ig, gro&t,9

?erminal year

8-table /ro&t,9

!ength of ,eriod ?5 Forever

%evenue 2.EE2 million HBase YearI 38.E?D million

%ev &ro*th %ate HCA&%I 2/@ 2/?

,erating Margin E/5 HBase YearI

25/8 HYear ?5I

25/8

%eturn on Ca,ital 2/8 HBase YearI

?/2 HYear ?5I

?3/?3

%einvestment %ate ? HYear ?I

?D HYear ?5I

?4/2

Cost of Ca,ital ?5/8E /?3

b. Output

=nter,rise ;alue 22.E@ million

=>uity ;alue 23.28@ million

=stimated ;alue Kshare ?44/D


Price as of =stimated ;alue ?3/2

c. Commentary

Cost o Capital

For cost of e>uity. # used the glo'al average unlevered 'eta for 7oft*are H#nternetI com,anies.

*ith a value of ?/3@/ =>uity %is" Premium *as calculated as a *eighted =%P 'ased on source of revenue.

arriving at 4/35/ The Com,any has no straight de't. 'ut does have converti'le de't/ #ts converti'le de't

is 'ro"en do*n into straight de't and e>uity ,ortions. *ith the former added to de't value of o,erating

leases to arrive at amount of de't in the ca,ital structure/ An actual rating of BBG *as used to com,ute

cost of de't. giving a ,re+ta1 cost of de't of 8//

23


24/31

%is"free %ate 2/?3

=>uity %is" Premium 4/35

!evered Beta ?/8?

Cost of =>uity ??/53

:e'tKCa,ital 4/D

Ta1 %ate 85

Credit %ating BBG

Pre+Ta1 Cost of :e't 8/D

After+Ta1 Cost of :e't 2/D

Cost of Ca,ital ?5/@

Dey assumptions

&ro*th rate *as 'ac"trac"ed from target mar"et share 'y year ?59 revenue gro*s at 85 CA&%

in the ne1t @ years/ 6sed #ndustry average of 25/8? for target =B#T margin/ For sales to ca,ital.

assumed that the com,any can achieve a ratio of 3/51 in the first year. *hich is an average for last 3years) salesKca,ital ratio/ &oing for*ard. ste,,ed do*n to 5/D?1. *hich is the industry average. 'y year

?5/

%t,er inormation

Cost of ca,ital after year ?5 calculated as ris" free rate G 4 considering the com,any is in a

ris"y. cyclical 'usiness

%eturn on ca,ital after year ?5 at ?3. a ,remium to terminal cost of ca,ital as # 'elieve !in"ed#n

*ill have long+lasting com,etitive advantages

$um'er of shares outstanding incor,orates Class A. B. and %76

Calculated mar"et value of $on+controlling interest 'ased on glo'al industry+average PKB; ratio

of 8/@@1 Ca,italized %:9 3 year amortization

Ca,italized o,erating leases

($ )elative Valuation

a/ 7ummary

For relative valuation. # selected a sam,le of 2? com,anies/ The commonality among these com,anies is

net*or" effect N the more users. the higher the value ,ro,osition/

!ist of com,aniesuity %is" Premium 4/??

:e'tKCa,ital 5/ED

#nterest Coverage %atio ?4?1

7ynthetic Credit %ating AAA

Pre+Ta1 Cost of :e't 2/8

Cost of =>uity D/55

Cost of Ca,ital /D8

2/2 :CF Model

28


29/31

We im,lemented a 3+stage FCFF discount model 'ecause the firm is still in high gro*th/ The

in,uts for the high gro*th and sta'le gro*th ,eriods are listed 'elo*/ The interim @+year ,eriod sees a

gradual transition do*n to sta'le gro*th levels in terms of gro*th. cost of ca,ital and return on ca,ital/

.ig, /ro&t, -table /ro&t,

!ength of ,eriod @ Forever

&ro*th %ate 24/?@ 2/?3%evenue 822.3?/5E million HYear ?I ?.E.2?4/8@ million HYear ??I

=B#T H? N tI 43.58/53 million HYear ?I 2?.E83/8E million HYear ??I

,erating Margin ?/43 ?@/55

Ta1 %ate 85 85

%eturn on Ca,ital ?E/? 4/@

%einvestment %ate ?5D/3 35/EE

Cost of Ca,ital /D8 4/@5

2/3 ut,ut

Terminal ;alue HYear ?5I 2.455.45E/2D=nter,rise ;alue [email protected]/8@ million

=>uity ;alue [email protected]?/43 million

=stimated ;alue Kshare ?E/


Price as of =stimated ;alue ?34/42

2/8 Commentary

%evenue gro*th and terminal year after+ta1 margin HATMI are im,ortant drivers of value. 'ut

difficult to ,redict/ &ru'u' descri'es their mar"et as the E5 'illion ,er year restaurant ta"e+out mar"et/

We revised this figure do*n to 3@ 'illion to reflect our 'elief that &ru'u')s current 'usiness model

only *or"s in dense ur'an areas/ Although &ru'u' is the clear leader in its s,ace. it only earns a small

,ercentage of each sale for its service and therefore *ill not 'e a'le to achieve a huge mar"et share/ We

assumed that they *ould get to 2 of domestic ur'an ta"e+out 'y year @ and 3 'y year ?5/ We also

'elieve that the o,erating margin *ill erode due to increased com,etition/ As the num'er of com,ara'le

firms increases. restaurants *ill have to a'ility to sho, for the ta"e+out ,latform that charges them the

lo*est fees/ 7till. &ru'u' has a su'stantial com,etitive advantage at the moment 'ecause it has the

'iggest 'ase of restaurants and users. *hich should allo* it to "ee, relatively high margins for the

foreseea'le future/

2/8 7ensitivity Analysis

Because are difficult to ,redict. *e loo"ed at sensitivity of our valuation to changes in each/

6ltimately *e are comforta'le *ith the in,uts *e selected. for the reasons discussed a'ove/

29

Revenue Growth (year 15)

er"na!,T- 2? 24 3?

?5 ?5/5? ??/@4 ?3/8?

?@ ?8/@3 ?E/ 2?/24

25 ?D/54 23/48 2D/??


30/31

Current< Terminal ATM L ?@. %evenue &ro*th L 24

($ )elative Valuation3/? 7ummary

We ran regresions against a sam,le of EE #nternet service com,anies in order to com,are

&ru'u')s mar"et ,rice to the sector generally/ #t *as difficult to find a regression *ith a materially high

%+s>uared. 'ecause many of the com,anies in the sam,le are money losing com,anies/ After regressing

=nter,rise ;alue to 7ales H=;K7alesI and Price to Boo" ;alue against a num'er of different varia'le

com'inations. ultimately a regression of =;K7ales against ust one varia'le. =1,ected %evenue &ro*th.

,roduced the highest %+s>uared/ The resulting e>uation and its a,,lication to &ru'u' are re,roduced

'elo*/

3/2 %egression AnalysisEV/Sales=2.1561+0.0978(Expected Revenue Growth)

Coefficient 7tandard =rror T 7tat P+!evel

Constant 2/?@4? 5/388E4 4/2@3@ 2/2853=+

%evenue &ro*th 5/5DE 5/5?858 4/D433? ?/5EE4=+D

7 L 2/82D83 %+7>uared L 5/3D24@ Adusted %+7>uared L 5/38@@

Actual =;K7ales @/2?1Predicted =;K7ales 8/E?1

Predicted ;alue Kshare 22/3?

*$ Maret Valuation

We regressed &ru'u' against the entire mar"et/ For consistency. *e again used =;K7ales. using

:amodaran nline)s January 25?@ full mar"et regression e>uation/

EV/Sales=1.17+1.40g+6.35(Operating Margin)+5.26DFR0.10Tax rate

Actual =;K7ales @/2?1

Predicted =;K7ales @/E51

Predicted ;alue Kshare 24/23

30


31/31

5$ Final Analysis

@/? 7ummary of :ata

;alue Mar"et Price as of ;alue

Current Price 28/83 +

:CF ;alue ?E/ ?34/42

7ector %egression ;alue 22/3? ?5D/@5

Mar"et %egression ;alue 24/23 D3/?8

@/2 %ecommendation

&ru'u' seems overvalued under all metrics e1ce,t the full mar"et regression/ This full mar"et

regression seems ,ro'a'ly the least im,ortant9 es,ecially given that &ru'u' is overvalued com,ared to

its sector/ The :CF value is li"ely the most accurate< =ven if the driving estimates ,rove to 'e

,essimistic. &ru'u' still may not 'e a good value at the current ,rice 'ecause its value only e1ceeds the

current ,rice in one of the nine scenarios considered/

For these reasons. our recommendation is to 7=!! &ru'u'/

Documents

Stern MBA Valuation final project