(2009) Credit Suisse 130 30 Index White Paper

7/31/2019 (2009) Credit Suisse 130 30 Index White Paper

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Jasmna HasanhozcAlphaSimplex Goup, LLC

The Credit Suisse 130/30 Index:A Summary and Performance Comparison

Sptmb 2

Anw W. LoAlphaSimplex Group, LLC

and MIT Sloan School

o Management

Pankaj N. PatlCredit Suisse


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2 THe CrediT SuiSSe 130/30 iNdex

ExEcutivE Summary

Long-only potolo manags an nvstos hav acknowlg that th long-only constant s a potn-

tally costly ag on pomanc, an loosnng ths constant can a val. Howv, th magnt

o th pomanc ag s clt to mas wthot a pop bnchmak o a 130/30 potolo. in thspap, w smmaz th appoach takn by Lo an Patl (2008) n whch thy pov a passv bt

ynamc bnchmak consstng o a plan-vanlla 130/30 statgy sng smpl actos to ank stocks

an stana mthos o constctng potolos bas on ths ankngs. in ths atcl, w pov

both n-sampl an ot-o-sampl pomanc o ths 130/30 bnchmak that llstat ts avantags

an savantags n vaos makt contons, an compa t to oth 130/30 ns that hav

bn popos.

This is a redacted and edited version o Lo and Patel (2008), and includes a perormance comparison to other 130/30 indexes during the out-o-sample

period rom October 2007 to December 2008. The views and opinions expressed in this article are those o the authors only, and do not necessarily rep-

resent the views and opinions o AlphaSimplex Group, Credit Suisse, MIT, any o their afliates and employees, or any o the individuals acknowledged

below. The authors make no representations or warranty, either expressed or implied, as to the accuracy or completeness o the inormation contained

in this article, nor are they recommending that this article serve as the basis or any investment decisionthis article is or inormation purposes

only. This research was supported by AlphaSimplex Group, LLC and Credit Suisse. We thank Varun Dube, Michael Gorun, and Souheang Yao, or excellent

research assistance, and Jerry Chakin, Arnout Eikeboom, Kal Ghayur, Balaji Gopalakrishnan, Ronan Heaney, James Mar tielli, Steve Platt, Phil Vasan,and seminar participants at Credit Suisse and JP Morgan Asset Management or many stimulating discussions and comments.

Jsn Hsnhz, Senior Research Scientist, AlphaSimplex Goup, LLC, One Cambridge Center, Cambridge, MA 02142,

(617) 4757100 (voice), [email protected] (email).

anew W. L, Chie Investment Strategist, AlphaSimplex Group, LLC, and Harris & Harris Group Proessor, MIT Sloan School o Management.

Corresponding author: Andrew W. Lo, AlphaSimplex Group, LLC, One Cambridge Center, Cambridge, MA 02142,


Pnkj N. Pel, Managing Director, Quantitative Equity Research, Credit Suisse, 11 Madison Avenue, New York, NY 10010,



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THe CrediT SuiSSe 130/30 iNdex 3

1. iNtroductioN

On o th astst gowng aas n nstttonal nvstmnt managmnt s th so-call actv tn-

son o 130/30 class o statgs n whch th shot-sals constant o tatonal long-only potolos

s la. Fl both by th hstocal sccss o long/shot qty hg ns an th ncasngstaton o potolo manags at th appant mpact o long-only constants on pomanc, 130/30

pocts hav gown to ov $50 bllon n assts.

dspt th ncasng poplaty o sch statgs, th s stll consabl conson among manag-

s an nvstos gang th appopat sks an pct tns o 130/30 pocts. Fo ampl,

by constcton, th typcal 130/30 potolo has a lvag ato o 1.6-to-1, nlk a long-only potolo

that maks no s o lvag. Lvag s sally assocat wth hgh-volatlty tns, howv, th

typcal 130/30 potolos volatlty s compaabl to that o ts long-only contpat, an ts makt

bta appomatly th sam. Nvthlss, th a lvag o a 130/30 poct sggsts that th

pct tn shol b hgh than ts long-only contpat, bt by how mch? By nton, a

130/30 potolo hols 130% o ts captal n long postons an 30% n shot postons, tho, t may

b vw as a long-only potolo pls a makt-ntal potolo wth long an shot poss that a

30% o th long-only potolos makt val. Howv, th actv poton o a 130/30 statgy s typ-

cally vy nt om a makt-ntal potolo, hnc ths composton s, n act, nappopat.

Ths nq chaactstcs sggst that stng ns sch as th S&P 500 an th rssll 1000

a nappopat bnchmaks o lvag ynamc potolos sch as 130/30 ns. A nw bnchmak

s n, on that ncopoats th sam lvag constants an potolo constcton algothms as

130/30 ns, bt s othws tanspant, nvstabl, an passv. W pov sch a bnchmak n

ths pap.

in patcla, sng 10 wll-known an commcally avalabl valaton actos om Ct Ssss

Qanttatv eqty rsach Gop om Janay 1996 to Sptmb 2007, w constct a gnc

130/30 u.S. qty potolo sng th S&P 500 nvs o stocks an a stana potolo optmz.

Th hstocal smlaton o ths smpl 130/30 statgybalanc on a monthly bassyls a

bnchmak tm-ss o tns that can b vw as a 130/30 n. By sng only nomaton

avalabl po to ach balancng at to omlat th potolo wghts, w cat a tly nvstabl

n. An by povng both th ata an th algothm o comptng th potolo wghts, w n

th n passv an tanspant.

in Scton 2, w pov a ltat vw o long/shot qty nvstng, an obsv that only cntly

hav th analytcs o 130/30 statgs bn omally vlop. Ths analytcs pov th motva-

ton o a 130/30 n, whch capts n a mo ct ashon than collctons o htognos

130/30 manags th agggat pomanc o actv-tnson statgs. Howv, w acknowlg

that poposng a statgy as an n s ath nothoo, an pov som hstocal pspctv oths bak om taton n Scton 3. in Scton 4, w psnt th basc amwok o constctng a

gnc 130/30 statgy. Th mpcal popts o ths statgy a smmaz n Scton 5, an w

concl n Scton 6.


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2. LitEraturE rEviEW

Althogh 130/30 statgs a latvly nw, th ltat on long/shot qty statgs s wll-vl-

op, an Gnol an Kahn (2000) an inchn (2002) pov a sl chonology o ths ltat.

Th cnt stag o th long/shot bat has ocs on whth th a cncy gans that slt

om lang th long-only constant. Fo ampl, Bsh (1997) shows that ang a long/shot statgy

to a long statgy pans th man-vaanc cnt ont, pov that long/shot statgs hav

postv pct alphas. Gnol an Kahn (2000) show that th nomaton atos cln as w

go om long/shot to long-only, bt shot o vng an analytcal psson o th loss n cncy

sltng om th long-only constant, thy s a compt smlaton to stmat th magnt o

th mpact. Jacobs, Lvy, an Sta (1998, 1999) th laboat on th loss o cncy that can

occ as a slt o th long-only constant. An Matll (2005) llstats mpcally how movng

th long-only constant mpovs th pct nomaton ato o u.S. lag-cap qty ns, vn

at accontng o th atonal costs assocat wth shotng stocks.

Clak, Slva, an Tholy (2002) vlop a amwok o masng th mpact o constants onval a an pomanc analyss o constan potolos. Thy pov a gnalz vson o

Gnols (1989) namntal law o actv managmnt whch lats th manags pct po-

manc an th nomaton cocnt o th ocastng pocsss, by cognzng that to vaos

mplmntaton constants, manags cannot lly plot th ablty to ocast tns. To capt th

mpact o ths constants thy ntoc a tans cocnt nto th namntal law as a ma-

s o how ctvly th manags nomaton s tans nto potolo wghts. Clak, Slva,

an Tholy (2002) s ths amwok to pov th sppot o long/shot statgs by showng

that th tans cocnt alls mo by mposton o th long-only constant than by any oth sngl

stcton. Clak, Slva, an Sapa (2004) gag th mpact o vaos constants mpcally, an

concl that th long-only constant s otn th most sgncant n tms o nomaton loss. Thy

show that ltng ths constant s ctcal o mpovng th nomaton tans om stock-slctonmols to actv potolo wghts. Sonsn, Ha, an Qan (2007) s nmcal smlatons o long/

shot potolos to monstat th nt bnts o shotng an to compt th optmal g o shotng

as a ncton o alpha, s tackng o, tnov, lvag, an tang costs. Johnson, Kahn, an

Ptch (2007) th mphasz th costs to cncy o th long-only constant an th mpotanc

o choosng gang an sk n conct n th cton o long/shot potolos.

Wth th champons o long/shot nvstng ncasngly otnmbng ts avsas, th n o a o-

mal mol to analyz th actos that tmn th sz o th shot tnson n th long/shot potolos

has bcom mo pssng, an Clak, Slva, Sapa, an Tholy (2007) hav ll ths gap. Bas

on som smplyng assmptons abot th scty covaanc mat an th concntaton pol o

th bnchmak, thy v an qaton that shows how th pct shot wght o a scty pns

on th latv sz o th sctys bnchmak wght an ts assgn actv wght n th absnc o

constants. Thy ag that th long/shot ato shol b allow to vay ov tm to accommoat

changs n nval scty sk, scty colaton, an bnchmak wght concntaton, n o to

mantan a constant lvl o actv sk. Vayng th long/shot ato, howv, blongs to th oman o

actv 130/30 statgs, an s not appopat o th pposs o th 130/30 n wh th goal s to

capt th sks an oppotnts assocat wth th 130/30 nvstmnt omat n a passv way.


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Fially, Martielli (2005) a Jacobs a Levy (2006) provie a excellet practical perspective o the

mechaics o the ehace active equity portolio costructio a a umber o operatioal cosier-

atios, a the avatages o ehace active equity over equitize log/short strategies are summarize

i Jacobs a Levy (2007).

3. Can a Strategy Be an Index?

Although Sectio 2 illustrates a substatial itellectual history that motivates this paper, we o epart

rom staar termiology i oe importat respect: We are proposig a strategy as a passive bechmark

or 130/30 proucts, ot a static or buy-a-hol basket o securities. This eparture eserves urther

iscussio a elaboratio.

The origial motivatio behi xig the set o securities a value-weightig them was to reuce the

amout o traig eee to replicate the iex i a cash portolio. Apart rom aitios a eletios

to the iex, a value-weighte portolio ee ever be rebalace sice the weights automatically ajustproportioally as market valuatios fuctuate. These buy-a-hol portolios are attractive ot oly

because they keep traig costs to a miimum, but also because they are simpler to implemet rom a

operatioal perspective. It is easy to orget the ormiable challeges pose by the back-oce, accout-

ig, a trae recociliatio processes or eve moerate-size portolios i the ays beore persoal

computers, FIX egies, a electroic traig platorms.

However, the eitio o passive has chage i recet years with techological avaces: A ivest-

met process is calle passive i it oes ot require ay iscretioary huma itervetio. Oe o

the beets o techology is the ability to create passive portolios capable o capturig more complex

risk/retur proles, such as those o a agig populatio preparig or retiremet. I this paper, we are

proposig aother passive iex that ivolves a mechaical ivestmet process, oe that leas to a

plai-vailla 130/30 portolio. However, the cocept o a strategy as a iex is ar more geeral, a

we believe that there is a broa array o such iexes that woul provie useul iormatio or ivestors.

Iee, the burgeoig literature a iustry applicatios ivolvig hege-u beta replicatio is just

oe maiestatio o this tre towar trasparecy through mechaical portolio costructio rules (see,

or example, Hasahozic a Lo, 2007), a we expect more yamic strategies to become passive

bechmarks as the ivestor base becomes more sophisticate a emaig.

4. Index ConStruCtIon

There are two basic compoets o ay 130/30 strategy: orecasts o expecte returs or alphas or each

stock i the portolio uiverse, a a estimate o the covariace matrix use to costruct a eciet porto-

lio. I Sectio 4.1, we escribe a set o 10 composite alpha actors evelope by the Creit Suisse Quatita-

tive Equity Research Group a istribute regularly to its cliets, coverig a broa rage o valuatio moels

ragig rom ivestmet style to techical iicators, a we use a simple equal-weighte average o these

10 actors as our geeric expecte-retur orecast. The covariace matrix use to costruct a mea-variace

eciet portolio is give by the Barra U.S. Equity Log-Term Risk Moel, a i Appeix 7.1 (page 21)

we escribe the parameter settigs we use to etermie the portolio weights o our 130/30 iex.

THE CREdIT SUISSE 130/30 IndEX 5


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7. Earnings Momentum. We ee earigs mometum i terms o earigs estimates, ot

historical earigs. The earigs-mometum alpha portolio buys stocks with positive earigs

surprises a upwar estimate revisios a shorts those with egative earigs surprises a

owwar estimate revisios.

8. Price Momentum. The price-mometum alpha portolio buys stocks with high returs over thepast 612 moths a shorts those with low or egative returs over the past 612 moths.

9. Price Reversal. Price reversal is the patter whereby short-term wiers ote suer owsie

reversals a short-term losers te to bouce back to the upsie. These reversal patters are

eviet or horizos ragig rom oe ay to our weeks.

10. Small Size. The small-size alpha portolio buys the smallest ecile stocks i the iex a shorts

the largest ecile i the iex. We measure size usig the ollowig metrics: market capitalizatio,

assets, sales, a stock price.

Stocks with high exposure to the 10 alpha actors are orecast to provie positive alpha; stocks with low

exposure shoul geerate egative alpha. Hece, we invert all the traitioal-value a relative-value

ratios, with the exceptio o the ivie yiel, so that a high umber meas positive alpha. For the same

reaso, all o the price-reversal a small-size iiviual alpha measuremets, as well as the ollowig

two prot-tres iiviual alpha measuremetsIustry-Relative Trailig 12-Moth (Receivables +

Ivetories) / Trailig 12-Moth Sales a Trailig 12-Moth Overhea / Trailig 12-Moth Salesare

multiplie by 1.

As escribe above, each compay i the S&P 1500 uiverse has 10 composite-alpha-actor time se-

ries associate with it, each o which cosists o its costituet alpha measuremets. For example, the

traitioal-value composite alpha actor is compose o the ollowig ve costituet actors: price/book

value, ivie yiel, price/trailig cash fow, price/trailig sales, a price/orwar earigs. We ow

escribe the algorithm use to combie these iiviual alpha measuremets ito composite-alpha-

actor z-scores. Ater, say, the P/BV ratio is compute or a particular compay o a particular ate, theollowig two-step ormalizatio proceure is use to compute its z-score (we start with a sample o all

the compaies i the S&P 1500):

1. First the P/BVs z-score is compute by ormalizig that ratio usig the ratios cap-weighte mea

across the S&P 500 compaies a its staar eviatio across the S&P 1500 compaies (this

staar eviatio is compute usig the cap-weighte mea, but the square eviatios rom

the mea are ot cap-weighte).

2. The compaies with z-scores compute i step 1 that are greater tha 10 i absolute value are

roppe rom the sample, a the cap-weighte S&P 500 mea a the S&P 1500 staar

eviatio are re-compute base o this smaller sample, a the each compays (rom the

origial sample) P/BV ratio is re-ormalize.

We compute the z-score o ivie yiel, price/trailig cash fow, price/trailig sales, a price/orwar

earigs i the same way. To compute the traitioal-value composite-alpha-actor z-score, we rst take

a equal-weighte average o the z-scores o its ve costituets where ay costituet z-score that

is greater tha 10 or less tha 10 is set to 10 or 10, respectively, a the ormalize that equal-

weighte average i two steps as escribe above.


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8 THE CREdIT SUISSE 130/30 IndEX

Category Composite alpha FaCtor Underlying alpha measUrement equ Fc l

tValUe

t Vu

Price / Forwar Earigs

Price / Trailig Sales

Price / Trailig Cash Flow

divie Yiel

Price / Book Value

rv Vu

Iustry Relative Price / Trailig Sales (Curret Sprea vs. 5-Year Average)

Iustry Relative Price / Trailig Earigs (Curret Sprea vs. 5-Year Average)

Iustry Relative Price / Trailig Cash Flow (Curret Sprea vs. 5-Year Average)

Iustry Relative Price / Trailig Sales

Iustry Relative Price / Forwar Earigs

Iustry Relative Price / Trailig Cash Flow

t

g

roWth hc gw

Cosecutive Quarters of Positive Chage i Trailig 12-Moth Cash Flow

Cosecutive Quarters of Positive Chage i Quarterly Earigs

12-Moth Chage i Quarterly Cash Flow

3-Year Average Aual Sales Growth

3-Year Average Aual Earigs Growth

12-Quarter Trelie i Trailig 12-Moth Earigs

Slope of Trelie through Last 4 Quarters of Trailig 12-Moth Cash Flows

exc gw5-Year Expecte Earigs Growth (I/B/E/S Cosesus)

Expecte Earigs Growth: Fiscal Year 2 / Fiscal Year 1 (IBES)

t

proFitaBility

pf t

Cosecutive Quarters of declies i (Receivables+Ivetories) / Sales

Cosecutive Quarters of Positive Chage i Trailig 12-Moth Cash Flow / Sales

Cosecutive Quarters of declies i Trailig 12-Moth Overhea / Sales

Iustry Relative Trailig 12-Moth (Receivables+Ivetories) / Sales

Iustry Relative Trailig 12-Moth Sales / Assets

Trailig 12-Moth Overhea / Sales

Trailig 12-Moth Earigs / Sales

acc s3-Moth Mometum i Quarterly Sales

6-Moth Mometum i Trailig 12-Moth Sales

Chage i Slope of 4-Quarter Trelie through Quarterly Sales

t

momentUm

e mu

4-Week Chage i Leaig 12-Moth Cosesus Estimate / Price

8-Week Chage i Leaig 12-Moth Cosesus Estimate / Price

Last Earigs Surprise / Curret Price

Last Earigs Surprise / Staar deviatio of Quarterly Estimates (SUE)

pc mu

Slope of 52-Week Trelie (20-day Lag)

Percet above 260-day Low (20-day Lag)

4-/52-Week Price Oscillator (20-day Lag)

39-Week Retur (20-day Lag)

51-Week Volume Price Tre (20-day Lag)

t

teChniCal pc rv

5-day Iustry Relative Retur

5-day Moey Flow / Volume

10-day MACd Sigal Lie

14-day RSI (Relative Stregth Iicator)20-day Stochastic

4-Week Iustry Relative Retur

s sz

Log of Market Capitalizatio

Log of Market Capitalizatio Cube

Log of Stock Price

Log of Total Assets

Log of Trailig 12-Moth Sales

Fu 1: Creit Suisse Alpha Factors i more etail. Source: Creit Suisse Quatitative Equity Research


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Th compost-alpha-actoz-scos o ach o th oth nn compost alpha actos a obtan n

th sam way gvn ts cosponng consttnt ncatos. Thn, o ach company n th S&P 500

an o ach at, w compt th qal-wght avag o ts cosponng 10 compost-alpha-

actoz-scos, an s t as th css-tn npt nto th potolo optmz (s Appn 7.1, pag

21). W wsh to stss h that whl an actv 130/30 statgy may mploy ngnos ways o ynam-

cally wghtng th actos, qal wghtng s mo appopat o an n wh w a not tyng to

mak bts on any on acto wth th goal o mantanng tanspancy an passvty.

5. EmPiricaL rESuLtS

usng th css-tn calclatons otln n Scton 4 an th potolo constcton algothm n

Appn 7.1 (pag 21) wth ata om Janay 1996 to Sptmb 2007, w constct th tns

o o 130/30 statgy assmng a on-way tansacton cost o 0.25% an an annal shot-sals cost

o 0.75%, o an annal tnov o 100%. Whl th abov-mnton tansacton an shotng cost

constants a appl wthn th optmzaton pocss to achv th s lvl o tnov, th Ct

Sss 130/30 tns a pot goss o costs thoghot ths pap. Gvn that o nvs s th

S&P 500, a on-way tansacton cost o 0.25% s lkly to b an ovstmat o most 130/30 poto-

los. Howv, tansacton costs tn to b hgh o potolos constct ply om namntal o

sctonay consatons, hnc w s a mo consvatv val to cov ths cass as wll as

th mo typcal qanttatv 130/30 potolos. Snc th S&P 500 gnally has an annal tnov o

2% to 10% (s Tabl 5, pag 14), a tnov lvl o 100% psvs th passv nat o o 130/30

potolo whl allowng t to spon ach month to changs n th nlyng alpha actos. Scton 5.1

smmazs th basc pomanc chaactstcs o th 130/30 n, an Scton 5.2 contans tang

statstcs o th 130/30 potolo.

5.1 hrc Rk Reur

Tabl 1 (pag 10) smmazs th pomanc o th 130/30 n, an o compason also ncls

th smmay statstcs o th S&P 500 n. Fo th n-sampl po om Janay 1996 to Sptmb

2007, th athmtcally compon avag tn o th 130/30 n s 15.19%, whch compas

avoably wth th cosponng avag tn o 10.50% o th S&P 500 ov that sam po. Th

volatlty o th 130/30 n s appomatly 15% an s smla to th 14.68% stana vaton o

th S&P 500. Ths volatlty lvl mpls a Shap ato o 0.67 o th 130/30 n, assmng a 5%

sk- at, whch compas avoably wth th S&P 500 ns Shap ato o 0.37. O cos, som

hav ag that sch a compason s nappopat bcas th 130/30 statgy s lvag, an ths

agmnt s th vy motvaton o o n. By contollng th volatlty an bta o o 130/30 statgy,

w hop to cat a bnchmak that s as compaabl to th S&P 500 as possbl whl allowng thnq chaactstcs o long/shot qty nvstng to mg.


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sc

Cs 130/30 index (gross) s&p 500 index

sl p sl p

1996-2007 2002-2007 2004-2007 2007 1996-2007 2002-2007 2004-2007 2007

aulz gc m (%) 14.99 10.05 12.72 13.03 9.84 6.98 10.82 12.36

aulz ahc m (%) 15.19 10.25 12.30 12.66 10.50 7.49 10.58 12.09

aulz sd (%) 15.14 11.34 7.42 8.85 14.68 12.00 7.35 9.38

aulz sh* 0.67 0.46 0.98 0.86 0.37 0.21 0.76 0.76

skw -0.49 -0.62 -0.28 -0.45 -0.56 -0.61 -0.32 -0.26

Ku 3.86 3.99 2.42 1.67 3.65 4.36 2.12 1.69

1 -3.36 0.13 -5.37 13.59 -0.9 5.2 -1.3 18.3

2 -7.70 1.01 -21.17 -64.57 -5.0 5.5 -16.6 -71.1

3 5.63 3.64 -17.49 -40.08 4.0 3.9 -24.8 -44.4

mdd (%) -35.16 -22.75 -4.83 -4.83 -44.7 -28.3 -4.7 -4.7

dd B 2 00 00 831 2 00 20 32 8 2 007 05 31 2 007 05 31 2 00 00 831 2 00 20 32 8 2 007 05 31 2 007 05 31

dd e 2 00 20 93 0 2 00 20 93 0 2 007 0731 2 007 0731 2 00 20 93 0 2 00 20 93 0 2 007 0731 2 007 0731

*A risk-free rate of 5% is assume.

tbl 1: Summary statistics for the mothly returs of the Creit Suisse 130/30 Iex (Gross), a the S&P 500 Iex, fromJauary 1996 to September 2007.

Figure 2 (below) plots the cumulative returs of the Creit Suisse 130/30 Iex a other popular iexes

such as the S&P 500, the Russell 2000, a the Creit Suisse/Tremot Hege-Fu Iex. These plots

show that the 130/30 iex behaves more like traitioal equity iexes tha the Creit Suisse/Tremot

Hege-Fu Iex, but oes exhibit some performace gais over the S&P 500 a Russell 2000.

0

1

2

3

4

5

6

CS 130/30 Index (Gross) S&P 500 (Large Cap) Russell 2000 CS/Tremont Hedge-Fund Index

Jan

1996

Jan

1997

Jan

1998

Jan

1999

Jan

2000

Jan

2001

Jan

2002

Jan

2003

Jan

2004

Jan

2005

Jan

2006

Jan

2007

COMPOUNDR

ETURN

Fu 2: A compariso of the cumulative returs of the Creit Suisse 130/30 Ivestable Iex a other iexes,from Jauary 1996 to September 2007.


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A ya-by-ya compason o th 130/30 statgy wth th S&P 500 psnt n Tabl 2 (blow) sg-

gsts that th ncas fblty o th 130/30 potolo os sm to yl bnts ov an abov th

S&P 500. Howv, th a pos sch as 2006 wh th 130/30 statgy npoms th S&P

500, whch s not spsng snc n th bll makt sch as that o 2006 mo skll may b n to

pck goo shotng canats than that capt by tanspant actos. Pomanc o alpha actos n

2006 was not boaly consstnt. Fo nstanc, pomanc o th hstocal gowth acto was pvs

n 9 ot o 10 sctos an o th pot tns acto t was pvs n 7 ot o 10 sctos. Ths hawn

aganst namntal actos cas slght npomanc n th 130/30 statgy. Tabl 2 contans th

monthly an annal tns o th 130/30 an th S&P 500 ns, an a ct compason shows

that th annalz tackng o o th 130/30 n s 2.62% an th avag css tn assocat

wth ths 130/30 n s 4.69%, mplyng an nomaton ato (ir) o 1.79.5 Howv, gvn th passv

an tanspant nat o th 130/30 statgy w hav popos, ths mpssv ir shol not b

ntpt as a sgn o alpha,6 bt ath as th bnts o ncas fblty pov by th 130/30

omat. Apat om ths pomanc ncs, Tabl 1 (pag 10) shows that th manng statstcal

popts o 130/30 n tns a vtally nstngshabl om thos o th S&P 500.

yer

Cs 130/30 indEx monthly REtURns (gRoss) s&p 500 indEx monthly REtURns

J Feb mr ar m Ju Ju au se oc nv decau(ge) J Feb mr ar m Ju Ju au se oc nv dec

au(ge)

1996 4.0 1.3 1.4 2.2 3.1 0.7 -4.3 3.3 5.5 3.3 7.7 -1.3 29.7 3.4 0.9 1.0 1.5 2.6 0.4 -4.4 2.1 5.6 2.8 7.6 -2.0 23.0

1997 6.6 0.4 -4.3 7.1 7.0 4.2 8.6 -4.0 6.5 -3.7 5.2 1.1 39.1 6.2 0.8 -4.1 6.0 6.1 4.5 8.0 -5.6 5.5 -3.3 4.6 1.7 33.4

1998 1.1 8.4 5.4 2.6 -1.7 5.1 -1.3 -15.2 7.4 8.2 5.6 8.2 36.2 1.1 7.2 5.1 1.0 -1.7 4.1 -1.1 -14.5 6.4 8.1 6.1 5.8 28.6

1999 6.5 -3.7 3.1 4.5 -1.3 6.1 -2.4 -0.5 -2.7 7.6 1.7 7.7 28.8 4.2 -3.1 4.0 3.9 -2.4 5.6 -3.1 -0.5 -2.7 6.3 2.0 5.9 21.0

2000 -4.5 0.3 12.0 -2.2 -1.9 3.6 -0.4 -5.2 -9.3 2.3 7.5 2.1 -5.6 -5.0 -1.9 9.8 -3.0 -2.1 2.5 -1.6 6.2 -5.3 -0.4 -7.9 0.5 -9.1

2001 4.5 -8.5 -5.6 10.1 0.4 -1.6 -0.4 -5.2 -9.3 2.3 7.5 2.1 -5.6 3.5 -9.1 -6.3 7.8 0.7 -2.4 -1.0 -6.3 -8.1 1.9 7.6 0.9 -11.9

2002 -0.9 -0.3 3.4 -5.0 0.9 -6.6 -7.3 2.8 -9.5 8.3 5.8 -5.2 -14.3 -1.5 -1.9 3.8 -6.1 -0.7 -7.1 -7.8 0.7 -10.9 8.8 5.9 -5.9 -22.1

2003 -3.0 -1.8 1.5 7.3 5.8 1.5 1.9 2.4 -0.4 5.3 0.8 4.9 29.2 -2.6 -1.5 1.0 8.2 5.3 1.3 1.8 2.0 -1.1 5.7 0.9 5.2 28.7

2004 2.7 1.1 -0.6 -0.8 2.3 2.6 -3.4 -0.6 1.9 1.0 5.4 3.3 15.6 1.8 1.4 -1.5 -1.6 1.4 1.9 -3.3 0.4 1.1 1.5 4.0 3.4 10.92005 -2.0 2.5 -1.1 -2.7 3.6 0.6 4.4 -0.1 1.5 -1.1 4.0 0.6 10.5 -2.4 2.1 -1.8 -1.9 3.2 0.1 3.7 -0.9 0.8 -1.7 3.8 0.0 4.9

2006 2.5 -0.2 1.1 1.8 -3.0 -0.1 0.5 1.6 1.9 2.6 1.2 1.5 11.9 2.6 0.3 1.2 1.3 -2.9 0.1 0.6 2.4 2.6 3.3 1.9 1.4 15.8

2007 2.3 -1.5 1.4 3.5 3.1 -2.0 -2.9 1.5 4.0 9.6 1.5 -2.0 1.1 4.4 3.5 -1.7 -3.1 1.5 3.7 9.1

me 1.7 -0.2 1.5 2.4 1.5 1.2 -0.6 -0.5 0.1 2.9 3.3 2.2 1.1 -0.6 1.1 1.8 1.1 0.8 -0.9 -1.0 -0.2 3.0 3.3 1.5

sd 3.6 3.9 4.5 4.5 3.2 3.5 4.2 5.7 5.7 4.1 4.6 3.8 3.3 3.8 4.3 4.4 3.1 3.4 4.1 5.4 5.6 3.9 4.3 3.5

tbe 2: Monthly tns o th Ct Sss 130/30 in (Goss) an th S&P 500 in, n pcnt, om Janay 1996to Sptmb 2007. Plas not that th annal tns o 2007 a ya-to-at tns.

5 Note that the annualized tracking error o 2.62% is computed directly rom the monthly excess returns o the 130/30 strategy, whereas the tracking errors

in Tables 4 and 9 (pages 13 and 20) are based on the monthly annualized tracking-error estimates produced by the MSCI Barra Aegis Portolio Manager..

6 Recall that the actors used in constructing the 130/30 portolio are based on well-known accounting variables and have been available to Credit

Suisse clients or several years.


12/24


ie Cs 130/30 indEx (gRoss) s&p 500 indEx

Crre (based on monthly returns to Sept. 07)

Rue 1000 99 100

Rue 1000 grw 94 94

Rue 1000 Vue 88 90Rue 2000 73 72

Rue 2000 grw 73 71

Rue 2000 Vue 68 67

Rue 3000 98 99

Rue 3000 grw 94 94

Rue 3000 Vue 88 90

s&p 500 (lre C) 99 100

s&p 500 grw 95 96

s&p 500 Vue 92 94

s&p 400 (m C) 88 85

s&p 400 grw 85 82

s&p 400 Vue 79 78s&p 600 (s C) 74 72

s&p 600 grw 71 68

s&p 600 Vue 73 72

Crre oer mrke iee (based on monthly returns to Aug. 07)

msCi Wr ie 93 95

nasdaQ 100 sck ie 82 81

BBa liBoR Usd 3-m -1 0

dJ le B C glBl -5 -6

U.s. treur n/B (gt10) 17 18



g (s $/) -2 -4

U.s. dr s ie 5 6

nymEx Crue Fuure ie C V -18 -16

Crre Cs/tre iee (based on monthly returns to Aug. 07)

a Fu 52 50

Cverbe arbre 15 13

dece sr B -78 -76

Eer mrke 54 55

Equ mrke neur 44 42

Eve drve 55 55

Fe ice arbre 2 0

gb mcr 25 23l/sr Equ hee 62 59

me Fuure -10 -8

mu-sre 16 15

Crre 75% Crre -25%

tbe 3: Colatons o th Ct Sss 130/30 in (Goss) to vaos makt an hg-n ns, om Janay 1996to Sptmb 2007.


13/24


in Tabl 3 (pag 12), w pot th colatons o th 130/30 n to vaos makt ns, ky nancal

assts, an hg-n ns. Fo compason, w pot th sam colatons o th S&P 500. Not

spsngly, th 130/30 n s hghly colat wth all o th qty ns, an th colaton

cocnts a naly ntcal to thos o th S&P 500. Th ght panls o Tabl 3 show th sam

pattnsth 130/30 n an th S&P 500 hav almost ntcal colatons to stock, bon, c-

ncy, commoty, an hg-n ns.

5.2 tr sc

To vlop a sns o th mplmntaton sss sonng th 130/30 n, Tabl 4 (blow) pots

th monthly an annal tnov an yaly avags o th annalz tackng os (obtan om th

yerCs 130/30 indEx total tURnoVER Cs 130/30 indEx long-sidE tURnoVER

J Feb mr ar m Ju Ju au se oc nv dec annul* J Feb mr ar m Ju Ju au se oc nv dec annul*

1996 130.010.4 8.0 7.3 11.4 6.8 4.9 12.1 6.2 6.8 10.8 5.4 98.4 115.0 7.1 6.0 5.4 7.8 4.4 4.0 9.0 4.5 5.0 7.7 3.5 70.2

1997 6.2 8.9 5.4 6.8 9.0 8.0 6.6 10.7 6.2 6.9 9.3 6.8 90.8 4.4 6.3 3.8 4.6 5.9 5.8 4.5 7.1 3.8 5.5 7.1 4.8 63.6

1998 6.1 10.1 8.0 7.4 10.5 7.4 4.7 11.4 7.8 7.7 11.4 5.0 97.5 4.5 7.2 5.5 5.0 8.1 4.9 3.1 8.3 5.6 5.4 7.7 3.3 68.51999 5.3 11.4 6.5 7.0 11.6 8.1 7.3 8.9 6.4 6.8 9.6 6.5 95.5 3.9 8.5 4.4 4.8 7.7 5.8 5.2 6.4 4.9 4.8 6.5 4.8 67.6

2000 7.2 9.1 5.6 6.1 8.7 7.8 8.0 8.9 6.8 6.9 12.1 7.5 94.7 4.6 6.5 4.2 4.4 6.5 5.6 6.3 6.3 5.1 4.9 8.3 5.1 67.8

2001 7.2 9.6 7.2 6.6 9.2 5.9 5.9 12.1 7.9 6.8 9.6 8.7 96.8 5.2 6.7 5.4 4.5 6.7 4.2 3.7 8.8 5.2 4.6 7.0 6.2 68.2

2002 6.6 10.4 7.8 6.7 8.6 7.4 7.2 9.6 6.8 6.8 9.1 9.3 96.4 5.1 7.3 5.5 4.5 5.4 4.8 5.4 7.2 4.7 4.4 6.5 6.1 66.8

2003 6.2 9.2 6.5 5.8 10.1 7.6 7.6 8.8 6.4 8.8 9.7 5.5 92.1 4.1 6.2 4.7 4.3 7.1 5.1 4.6 6.3 4.7 6.6 6.3 3.9 63.8

2004 6.9 9.1 6.3 6.5 7.6 8.7 6.4 6.4 5.7 5.3 8.2 6.3 83.5 4.6 6.8 4.8 4.7 5.3 5.7 4.4 4.0 3.7 3.8 6.1 4.3 58.2

2005 6.4 5.8 6.5 7.3 8.7 6.4 4.6 7.3 6.4 5.8 7.4 7.3 79.8 4.6 4.5 4.1 5.2 5.8 4.0 3.1 4.7 4.4 4.4 5.1 4.7 54.5

2006 6.1 6.1 6.0 6.1 7.2 6.9 6.4 7.7 5.6 7.3 6.2 7.0 78.6 4.5 4.6 4.0 4.4 5.5 4.6 4.4 5.6 4.2 5.3 5.1 4.7 57.1

2007 5.7 5.8 7.6 7.3 6.2 8.8 5.8 6.6 7.5 81.7 3.8 4 .3 4 .9 5 .0 4 .2 6 .2 3 .9 4 .9 5 .5 57.0

me 16.7 8.8 6.8 6.7 9.1 7.5 6.3 9.2 6.7 6.9 9.4 6.8 13.7 6.3 4.8 4.7 6.3 5.1 4.4 6.6 4.7 5.0 6.7 4.7

sd 35.7 1.9 0.9 0.5 1.6 0.9 1.1 2.0 0.8 0.9 1.7 1.3 31.9 1.3 0.7 0.4 1.2 0.7 0.9 1.6 0.6 0.7 1.0 0.9

yerCs 130/30 indEx annUalizEd tRaCKing ERRoR Cs 130/30 indEx shoRt-sidE tURnoVER

J Feb mr ar m Ju Ju au se oc nv dec annul* J Feb mr ar m Ju Ju au se oc nv dec annul*

1996 2.0 2.0 2.0 2.0 2.0 1.8 1.8 2.1 1.9 1.9 2.0 1.9 2.0 15.0 3.3 2.0 1.8 3.7 2.4 0.9 3.1 1.7 1.8 3.2 1.9 28.2

1997 2.1 2.0 2.0 1.9 2.0 1.9 2.1 1.9 2.0 1.9 2.1 2.0 2.0 1.7 2.6 1.6 2.3 3.1 2.2 2.2 3.7 2.3 1.5 2.2 2.0 27.2

1998 2.1 2.1 1.9 2.0 2.1 2.0 2.1 2.3 2.4 2.5 2.5 2.4 2.2 1.5 2.9 2.5 2.4 2.5 2.5 1.6 3.1 2.3 2.3 3.7 1.7 29.0

1999 2.2 2.3 2.3 2.4 2.4 2.3 2.2 2.1 2.2 2.1 2.4 2.4 2.3 1.4 2.9 2.1 2.3 4.0 2.4 2.1 2.4 1.6 2.1 3.1 1.7 27.9

2000 2.9 2.8 3.1 3.0 2.9 2.7 2.8 2.7 2.7 2.9 2.9 2.9 2.9 2.6 2.6 1.4 1.7 2.2 2.2 1.7 2.6 1.8 2.0 3.8 2.4 26.9

2001 2.7 2.8 2.8 2.6 2.3 2.3 2.5 2.4 2.3 2.5 2.6 2.5 2.5 2.1 2.9 1.9 2.2 2.5 1.6 2.2 3.3 2.7 2.1 2.6 2.4 28.6

2002 2.5 2.6 2.6 2.5 2.6 2.5 2.6 2.9 2.6 2.7 2.7 2.6 2.6 1.5 3.1 2.3 2.3 3.2 2.6 1.9 2.5 2.1 2.4 2.6 3.2 29.6

2003 2.6 2.4 2.3 2.2 2.2 2.3 2.4 2.6 2.3 2.2 2.3 2.1 2.3 2.1 3.0 1.8 1.5 2.9 2.6 3.1 2.5 1.7 2.2 3.3 1.6 28.3

2004 2.1 2.1 2.1 2.2 2.3 2.1 2.1 2.2 2.1 2.0 2.1 2.1 2.1 2.3 2.3 1.5 1.8 2.3 3.0 2.1 2.4 2.0 1.5 2.2 2.0 25.32005 2.1 2.1 2.0 2.2 2.3 2.1 2.0 2.0 2.1 2.1 2.2 2.1 2.1 1.8 1.4 2.4 2.1 2.9 2.5 1.6 2.6 2.0 2.0 1.4 2.2 25.3

2006 2.0 2.1 2.0 2.0 2.0 21 2.0 2.0 2.1 2.0 1.8 1.7 2.0 1.7 1.5 1.9 1.7 1.7 2.3 1.9 2.0 1.4 1.9 1.1 2.4 21.5

2007 1.6 1.7 1.7 1.6 1.6 1.6 1.7 1.8 1.8 1.7 1.9 1.5 2 .6 2 .3 2 .0 2 .6 1.9 1.7 2 .0 24.7

me 2.2 2.3 2.2 2.2 2.2 2.2 2.2 2.2 2.2 2.3 2.3 2.3 3.0 2.5 2.0 2.0 2.7 2.4 1.9 2.6 2.0 1.9 2.7 2.1

sd 0.4 0.4 0.4 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 3.8 0.7 0.4 0.3 0.7 0.3 0.5 0.6 0.4 0.3 0.8 0.5

*Annal tnov vals o 1996 cl th month o Janay.

tbe 4: Monthly tnov an annalz tackng o o th Ct Sss 130/30 in, n pcnt, om Janay 1996to Sptmb 2007.


14/24


MSCI Barra Aegis Portfolio Maager each moth) of the 130/30 portfolio.7 The turover of the 130/30 i-

ex rages from a high of 98.4% i 1996 to a low of 78.6% i 2006, a is typically 8% per moth. For

compariso, Table 5 (below) cotais the turover of several S&P iexes. I cotrast to the 130/30 iex

which is itee to be a yamic basket of securities, the S&P iexes are static, chagig oly

occasioally as certai stocks are iclue or exclue ue to chages i their characteristics. Therefore,

as a buy-a-hol iex, the turover of the S&P 500 is typically much lower tha that of the 130/30

iex, but Table 5 shows that eve for the S&P 500, there are years whe this static portfolio exhib-

its higher turover levels, e.g., 1998 whe the turover i the S&P 500 iex was 9.5%. Moreover,

for other static S&P iexes such as the Mi Cap 400, the turover levels are eve higher, hece the

practical challeges of implemetig the 130/30 iex are ot much greater tha those pose by may

other popular buy-a-hol iexes.

ye s&p 500 s&p midCap 400 s&p smallCap 600

1993 2.6 10.3

1994 3.8 9.9

1995 5.0 15.6 13.7

1996 4.6 14.4 16.4

1997 4.9 17.9 21.8

1998 9.5 31.4 24.4

1999 6.2 28.9 24.4

2000 8.9 37.1 36.4

2001 4.4 17.0 15.6

2002 3.8 10.7 11.0

2003 1.5 8.6 11.0

2004 3.1 13.1 13.0

2005 5.7 14.5 13.8

2006 4.5 12.2 12.9

tbe 5: Turover of various S&P iexes, i percet. Source: Creit Suisse Equity derivatives Group.

5.3 ou-f-se reu

I Lo a Patel (2008), the sample perio ee i September 2007, hece ow we have a 15-moth

out-of-sample perio i which to observe the performace of the Creit Suisse 130/30 Iex a com-

pare its performace to other 130/30 iexes that were recetly itrouce.8 The various iexes are

escribe i Figure 3 (page 15), a the results are cotaie i Figures 45 (page 16 a 18) a

7The total, long-side, and short-side turnover in Tables 4 and 9 (page 13 and 20) are computed as one-way turnover against the total absolute value

of the initial portfolio positions, whereas in the MSCI Barra Aegis Portfolio Manager, the long-side (short-side) turnover is computed against the value

of the long (short) positions of the initial portfolio. Also, each time a portfolio is constructed, the MSCI Barra Aegis Portfolio Manager provides an

annualized tracking-error forecast based on the Barra multiple-factor risk model.

8 After the launch of the Credit Suisse 130/30 Index in April 2008, the live index returns are used. Please note that the portfolio constructed in any given

month is implemented in production around the 18th day of that month.


15/24


Firmname

annoUnCementdate

Comments

t

CreditsUiise

oc. 2, 2007

Uv: About 500 Largest US compaies

130/30: Itegrate 130/30 at each rebalace usig a optimizer

sck rkg: 10 actor composites usig uametal, price a volume ata

rbc p: Mothlytg tckg e: 1.5 to 3% with respect to the uiverse, max +/- 40 bps active exposure to

uiverse foate ajuste weights

etF/etn avb: Yes, ETF is available by ProShares, Ticker CSM

suc: http://www.creit-suisse.com/iices/13030

ts&p

nv. 19, 2007

Uv: S&P 500 Compaies, stocks remove rom S&P 500 remove rom 130/30 iex,

a ew aitios to S&P 500 are eligible at ext rebalace.

130/30:Long Basket: The weight o the highest rake 30 stocks is icrease by 1% relative

to the S&P500 a is the overweight or log basket. Short Basket: The weight o the lowest

rake 30 stocks is ecrease by 1% relative to the S&P500 a is the uerweight or short

basket. Aggregate short positio is always less tha 30%. Log positio is +30% at rebalace.

sck rkg: S&P STARS ratigs a two uametal actors: 1) iustry relative exteral

acig, 2) iustry relative valuatio

rbc p: Quarterly

tg tckg e: n/AetF/etn avb: no

suc: S&P 500 130/30 Strategy Iex, July 2008, www.iices.staarapoors.com

t

doWj

ones

m. 11, 2008

Uv: dow Joes 750 Large Cap Iex Compaies

130/30: Leaig Iex: The 30 stocks with the highest RBP probability scores become

compoets o the dow Joes RBP Large-Cap Leaig 30 Iex.

lggg ix: The 30 stocks with the lowest RBP probability scores become compoets

o the dow Joes RBP Large-Cap Laggig 30 Iex.

sck rkg: RBP probability rakigs

rbc p: Quarterly

tg tckg e: n/A

etF/etn avb: no

suc: dow Joes RBP US Large-Cap 130/30 Iexes, February 2008, www.jiexes.com

t

indexiq

a. 30, 2008

Uv: Top 1000 stocks highest rake compaies i terms o 52-week average aily ollartraig volume a i terms o market capitalizatio

130/30: Log exposure o up to 100 stocks a short exposure with about 60 stocks. Log

weights are scale to 130% a short weights are scale to egative 30%.

sck rkg: Usig proprietary o-market-cap methoology

rbc p: Log exposure aual rebalace, short exposure quarterly rebalace

tg tckg e: Maximum weight o sigle stock is cappe at 5% at aual rebalace

a moitore each quarter, sigle stock weight more tha 10% at e o quarter is cappe

at 10% a excess weight allocate to other iex compoets. Maximum short positio al-

lowe is 1% at quarterly rebalace.

etF/etn avb: no

suc: Methoology or IQ 130/30 Iex, http://www.iexiq.com/

t

FirsttrUst

my 21, 2008

Uv: Start with largest 2500 US trae stocks a stocks that are at least as large as the

smallest stock i the largest 20% o nYSE liste stocks. These stocks are use or large cap

iex with aitioal requiremet o miimum o 500,000 shares trae i each o the lastsix calear moths.

130/30: Top 30% rake stocks are log equal weighte a bottom 30% stocks are short

equal weighte, a logs a shorts scale to 130/30 at each quarterly rebalace.

sck rkg: For log sie: Growth actors are 3, 6, a 12 moth price mometum a 1

year sales growth. Value actors are book value a cash fow multiples a retur o assets.

F h : 3 a 6 moth price mometum, book value a cash fow multiples a retur

o assets a short iterest .10 or less are use.

rbc p: Quarterly

tg tckg e: n/A

etF/etn avb: Yes, ETn by JP Morga, Ticker JFT

suc: First Trust Ehace 130/30 Large Cap Iex Iex Methoology, www.tportolios.com

Fgu 3: descriptio o other 130/30 iexes/strategies/ETns.


16/24


Tabls 69 (pags 1720). Both th monthly tns an tang statstcs a consstnt wth th

n-sampl contpats. Fo ampl, Tabl 6 (pag 17) shows that o th ot-o-sampl po th

Ct Sss 130/30 in has otpom th S&P 500 in by abot 4 pcntag ponts ann-

ally,9 bt ths s not spsng snc th 130/30 n taks on atonal sks, .., thos assocat

wth shot-sllng an lvag, whch a not accont o solly by makt bta. Th ccal pont s

that th val-a o th Ct Sss 130/30 in s not to any poptay nvstmnt acmn,

bt to oth socs o sk pma that th 130/30 omat can plot mo ctvly than th long-only

omat. Tabls 69 (pags 17 20) an Fg 5 (pag 18) also contan compasons wth oth 130/30

ns that w cntly ntoc. Th bggst ncs btwn th Ct Sss 130/30 in

an th oths a obsv o th Fst Tst 130/30 in an th iQ 130/30 in, both o whch

hbt annalz stana vatons mch gat than th 20.53% o th Ct Sss 130/30 in

ng th ot-o-sampl po, an mch gat than th S&P 500 ins 19.35% volatlty ng

ths sam po.

CS 130/30 Index (Gross) S&P 500 (Large Cap) Russell 2000 CS/Tremont Hedge-Fund Index

Sep2007

Oct2007

Nov2007

Dec2007

Jan2008

Feb2008

Mar2008

Apr2008

May2008

Jun2008

Jul2008

Aug2008

Sep2008

Oct2008

Nov2008

Dec2008

COMPOUNDR

ETURN

0.55

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

1.05

Fure 4: A compason o th cmlatv tns o th Ct Sss 130/30 in (Goss) an vaos oth ns,om Octob 2007 to dcmb 2008.

9This value reers to the arithmetic mean. The corresponding geometric mean outperormance is around 3%.


17/24


sc

Cs 130/30 indEx (gRoss) s&p 500 indEx s&p 500 130/30stRatEgy indEx

se per se per se per

2007-2008 2008 2007-2008 2008 2007-2008 2008

aue geerc me (%) -30.04 -33.93 -32.75 -37.00 -32.54 -37.76

aue arec me (%) -33.11 -38.24 -37.15 -43.15 -36.59 -44.06

aue sd (%) 20.53 22.63 19.35 21.02 20.56 22.10

aue sre* -1.86 -1.91 -2.18 -2.29 -2.02 -2.22

skewe -0.74 -0.53 -0.90 -0.69 -1.06 -0.87

Kur 3.40 2.80 3.40 2.85 3.95 3.34

1 34.97 38.05 24.85 29.47 23.53 26.92

2 -26.19 -29.77 -34.03 -40.68 -32.27 -39.90

3 -12.12 -10.74 -11.38 -9.74 -8.25 -6.21

mdd (%) -37.86 -35.72 -40.68 -37.66 -41.99 -39.23

dd Be 20071031 20080530 20071031 20071231 20071031 20071231

dd E 20081128 20081128 20081128 20081128 20081128 20081128

sc

s&p 500 130/30 stRatEgytotal REtURn

FiRst tRUst 130/30 indEx iQ 130/30 indEx

se per se per se per

2007-2008 2008 2007-2008 2008 2007-2008 2008

aue geerc me (%) -30.14 -34.00 -44.22 -54.19 -42.00 -49.88

aue arec me (%) -33.38 -38.54 -51.36 -69.73 -48.81 -62.18

aue sd (%) 19.78 21.64 32.89 33.70 29.36 31.27

aue sre* -1.94 -2.01 -1.71 -2.22 -1.83 -2.15

skewe -0.96 -0.77 -0.83 -0.69 -0.86 -0.62

Kur 3.59 2.97 2.83 2.51 3.04 2.57

1 23.66 27.00 31.20 39.59 28.59 34.23

2 -40.50 -46.00 14.86 0.74 9.35 -0.14

3 -12.47 -11.30 -8.49 -7.34 -8.25 -3.91

mdd (%) -39.33 -36.17 -55.50 -55.31 -51.41 -49.99

dd Be 20071031 20071231 20071031 20071231 20071031 20071231

dd E 20081128 20081128 20081128 20081128 20081128 20081128

*A sk- at o 5% s assm.

tbe 6: Smmay statstcs o th monthly tns o th Ct Sss 130/30 in (Goss), th S&P 500 in, anvaos oth 130/30 ns, om Octob 2007 to dcmb 2008. Plas not that th annalz man

tns a athmtc avags o monthly tns mltpl by 12, not compon gomtc avags.


18/24


y

Cs 130/30 index (gross) s&p 500 index

j Fb m a m ju ju au s oc nv dcau(g)


2007 1.3 -3.4 -1.0 -3.2 1.6 -4.2 -0.7 -3.3

2008 -6.1 -2.6 1.3 7.2 1.9 -7.3 -1.0 0.5 10.5 -16.9 -6.4 1.6 -33.9 -6.0 -3.2 -0.4 4.9 1.3 -8.4 -0.8 1.4 -8.9 -16.8 -7.2 1.1 -37.0

m -6.1 -2.6 1.3 7.2 1.9 -7.3 -1.0 0.5 -10.5 -7.8 -4.9 0.3 -6.0 -3.2 -0.4 4.9 1.3 -8.4 -0.8 1.4 -8.9 -7.6 -5.7 0.2

sd 0.0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 12.8 2 .1 1 .9 0.0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 13.0 2 .1 1 .2

y

doW jones rBp U.s. large-Cap 130/30 index s&p 500 130/30 strategy total retUrn



2007 1.7 -4.2 -1.2 -3.7 1.6 -4.2 -0.7 -3.3

2008 -5.5 -3.6 -0.2 4.4 1.3 -7.9 -1.2 1.7 -9.4 -17.2 -6.6 3.1 -35.0 -5.3 -3.3 0.0 4.5 1.5 -7.7 -1.1 1.9 -9.2 -17.1 -6.2 3.4 -34.0

m -5.5 -3.6 -0.2 4.4 1.3 -7.9 -1.2 1.7 -9.4 -7.8 -5.4 1.0 -5.3 -3.3 0.0 4.5 1.5 -7.7 -1.1 1.9 -9.2 -7.6 -5.1 1.2

sd 0.0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 . 0.0 13.4 1 .7 3 .0 0.0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 13.3 1 .6 3 .1

y

First trUst 130/30 index iq 130/30 index



2007 5.7 -5.5 5.4 5.2 3.9 -4.2 1.4 1.0

2008 -7.5 0.0 -4.6 6.6 4.7 -1.6 -12.8 -3.1 -21.0-24.8 -8.3 2.5 -54.2 -9.8 1.7 -4.0 7.5 4.3 -3.0 -9.6 -0.6 -18.3-23.1 -7.5 0.2 -49.9

m -7.5 0.0 -4.6 6.6 4.7 -1.6 -12.8 -3.1 -21.0 -9.6 -6.9 3 .9 -9.8 1 .7 -4.0 7.5 4 .3 -3 .0 -9 .6 -0.6 -18.3 -9.6 -5.9 0.8

sd 0.0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 21.5 2 .0 2 .0 0.0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 0 .0 19.1 2 .3 0 .9

tb 7: Mothly returs of the Creit Suisse 130/30 Iex (Gross), the S&P 500 Iex, a various other 130/30 iexes,i percet, from October 2007 to december 2008. Please ote that the geometrically compoue returs for 2007

iclue the moths of October, november, a december oly, a have ot bee aualize.

-20%

-15%

-10%

-5%

0%

5%

10%

FIRST TRUST

130/30 INDEX

IQ 130/30

INDEX

DOW JONES RBP

U.S. LARGE-CAP

S&P 500

130/30 STRATEGY

CS 130/30 INDEX

(GROSS)

-18.5%

-15.0%

0.6%

4.8% 5.1%

CUMULATIVE

EXCESS

RETURN

Fu 5: A compariso of the out-of-sample cumulative mothly excess returs versus the S&P 500 Iex for the Creit Suisse

130/30 Iex (Gross) a various other iexes, from October 2007 to december 2008.


19/24


ieCs 130/30

indEx (gRoss)s&p 500

indEx

s&p 500 130/30stRatEgy

indEx

s&p 500 130/30stRatEgy

total REtURn

FiRst tRUst130/30 indEx

iQ 130/30indEx

Crre (based on out-of-sample monthly returns from October 2007 to December 2008)

Rue 1000 99 100 99 99 83 83

Rue 1000 grw 98 98 98 98 88 88

Rue 1000 Vue 96 98 98 98 73 73

Rue 2000 92 96 96 96 72 72

Rue 2000 grw 94 96 96 96 81 81

Rue 2000 Vue 87 92 92 92 60 60

Rue 3000 99 100 99 99 82 82

Rue 3000 grw 98 98 98 98 87 87

Rue 3000 Vue 96 98 98 98 72 72

s&p 500 (lre C) 99 100 99 99 81 81

s&p 500 grw 98 97 96 95 67 67

s&p 500 Vue 93 97 96 95 67 67

s&p 400 (m C) 97 98 98 98 87 87

s&p 400 grw 96 96 96 96 91 91s&p 400 Vue 97 98 99 99 80 80

s&p 600 (s C) 91 95 95 95 72 72

s&p 600 grw 94 96 97 96 79 79

s&p 600 Vue 87 92 93 93 64 64

Crre oer mrke iee

msCi Wr ie 97 97 97 97 88 92

nasdaQ 100 sck ie 94 94 93 92 78 83

BBa liBoR Usd 3-m 0 4 -3 -3 -14 -4

dJ le B C glBl -13 -11 2 3 -6 -20

U.s. treur n/B (gt10) 11 12 3 2 6 11

U.s. treur n/B (gt2) 63 60 54 54 52 57

U.s. treur n/B (gt30) 9 10 0 0 4 9g (s $/) 12 14 18 18 34 25

U.s. dr s ie -49 -45 -51 -51 -56 -49

nymEx Crue Fuureie C V

63 61 58 57 80 80

Crre Cs/tre iee

a Fu 72 71 72 72 93 91

Cverbe arbre 74 72 75 75 88 87

dece sr B -51 -58 -55 -55 -33 -40

Eer mrke 76 75 76 76 91 89

Equ mrke neur 21 24 21 20 18 17

Eve drve 75 74 75 75 94 93

Fe ice arbre 76 77 78 78 81 82gb mcr 33 30 34 34 68 60

l/sr Equ hee 77 73 74 74 94 94

me Fuure -46 -50 -48 -48 0 -10

mu-sre 77 75 77 77 93 91

dree 79 79 79 79 91 91

Eve drve mu sre 70 68 69 69 91 91

Rk arbre 71 65 67 67 76 76

Crre 75% Crre -25%

tbe 8: Colatons o th Ct Sss 130/30 in (Goss), th S&P 500 in, an vaos oth 130/30 ns to vaosmakt an hg-n ns, om Octob 2007 to dcmb 2008.


20/24


yerCs 130/30 indEx total tURnoVER Cs 130/30 indEx long-sidE tURnoVER

J Feb mr ar m Ju Ju au se oc nv dec au J Feb mr ar m Ju Ju au se oc nv dec au

2007 4.7 6.7 6.5 71.7 3.5 4.5 4.1 48.4

2008 5.9 9.0 6.7 9.0 7.6 7.2 6.4 10.1 9.4 7.9 12.0 7.4 98.7 3.9 6.3 5.0 6.8 5.1 5.2 4.6 7.5 6.2 5.8 7.8 5.3 69.5

me 5.9 9.0 6.7 9.0 7.6 7.2 6.4 10.1 9.4 6.3 9.4 7.0 3.9 6.3 5.0 6.8 5.1 5.2 4.6 7.5 6.2 4.7 6.2 4.7

sd 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.3 3.7 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.7 2.4 0.8

yerCs 130/30 indEx annUalizEd tRaCKing ERRoR Cs 130/30 indEx shoRt-sidE tURnoVER

J Feb mr ar m Ju Ju au se oc nv dec au J Feb mr ar m Ju Ju au se oc nv dec au

2007 1.8 2.1 2.0 2.0 1.2 2.3 2.4 23.3

2008 2.0 2.2 2.1 2.1 2.2 2.2 2.3 2.6 2.3 2.7 2.8 3.0 2.4 2.1 2.7 1.7 2.2 2.6 2.0 1.8 2.6 3.3 2.0 4.2 2.1 29.2

me 2.0 2.2 2.1 2.1 2.2 2.2 2.3 2.6 2.3 2.3 2.5 2.5 2.1 2.7 1.7 2.2 2.6 2.0 1.8 2.6 3.3 1.6 3.2 2.3

sd 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7 0.5 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 1.3 0.2

tbe 9: Monthly tnov an annalz tackng o o th Ct Sss 130/30 in (Goss), n pcnt,om Octob 2007 to dcmb 2008.

6. coNcLuSioN

in ths pap, w hav ag that o a potolo to b cons a t n, t mst b tanspant,

nvstabl, an passv. Tanspancy qs that th ls o constctng th n b systmatc,

cla, an asly mplmntabl. invstablty qs that th componnts o th potolo consst o

lq chang-ta nstmnts. An passvty qs that th mplmntaton o th n s ply

mchancal, qng lttl o no manal ntvnton an scton. Wth ths cta n mn, w hav

popos a smpl ynamc potolo as an n o th many 130/30 pocts that a now bng o.

Poposng a ynamc statgy as an n s a sgncant pat om taton. Howv, th gowng

complty o nancal pocts copl wth cosponng avancs n tang tchnology an potolo

constcton tools pov compllng motvaton o ths nt gnaton o bnchmaks. Althogh th

ntptaton an mplmntaton o sch ynamc potolos wll q mo ot than th stana

by-an-hol ns, ths s th pc o nnovaton as nstttonal nvstos bcom mo ngag

n altnatv nvstmnts. An as tang tchnology bcoms mo sophstcat, w antcpat th

caton o many mo bnchmaks om ynamc tang statgs, an w hop that th 130/30 n

wll pav th way o that t.


21/24


7. aPPENdix

7.1 prf Cruc ar

W s th MSCi Baa Ags Potolo Manag wth th Baa u.S. eqty Long-Tm rsk Mol toconstct th 130/30 potolo on a monthly bass om Janay 1996 to dcmb 2008. Fo ach

month, w s th S&P 500 as th bnchmak an th nvs n th potolo constcton. W stat

wth $100,000,000 n cash, an thn balanc on a monthly bass (.., o ach month at Janay

1996, w npt th pvos months potolo as th ntal potolo n th optmzaton pocss). Th

pcs spccatons s a smmaz blow.

Constraints: W constan th potolo bta to qal on.

Expected Returns: Fo ach company n th S&P 500 an o ach at, w s th qal-wght

avag o ts cosponng tn compost-alpha-actoz-scos as th css-tn npt nto th opt-

mz whn constctng th nvstabl potolo. W st th sk- at, th bnchmak sk pmm,

an th pct bnchmak sps all to zo.

Optimization Type: W s long/shot potolo optmzaton, wh w st th long an th shot pos-

ton lvag to 130% an 30%, spctvly.

Trading: W o not pt any constants on th holng an tang thshol lvls, an w st th ac-

tv wght to 40 bass ponts. Ths yls a tackng o, n as th annalz stana vaton

o th nc btwn th potolo an th bnchmak aly tn ss, btwn 1.5% an 3%

o ach month.

Risk: W s th Baa alt sttng, whch ncls th ollowng spccatons: man tn o zo,

pobablty lvl o 5%, sk avson val o 0.0075, an AS-CF sk avson ato o 1.

Transaction Costs: W st th on-way tansacton costs to 0.25% an constct th potolo wth thannalz tnov o 100%. Th tnov o appomatly 100% p ya s achv by coplng th

on-way tansacton costs o 0.25% wth a tansacton-cost mltpl o 0.75 n th MSCi Baa Ags

Potolo Manag.

Tax Costs: W o not assm any mol o th ta costs.

un ths paamts, th potolo optmzaton pocss gnats th optmal nmb o shas to

b hl o ach stock n o 130/30 potolo o ach month. Now, o ach stock i n o potolo, w

hav th ollowng monthly nomaton: th nmb o shas S t1 at th n o th pvos month,

th pc p sha Pt1 at th n o th pvos month, an total tn o th month r t. W s ths

nomaton to om th nt-o-cost monthly 130/30 potolo total tn r pt as:

Pjt-1Sjt-1


22/24


Index oF FIgureS and taBLeS

Figure 1: Creit Suisse Alpha Factors i more etail. Source: Creit Suisse Quatitative Equity

Research,page 8.

Figure 2: A compariso of the cumulative returs of the Creit Suisse 130/30 Ivestable Iex

a other iexes, from Jauary 1996 to September 2007,page 10.

Figure 3: descriptio of other 130/30 iexes/strategies/ETns,page 15.

Figure 4: A compariso of the cumulative returs of the Creit Suisse 130/30 Iex (Gross) a

various other iexes, from October 2007 to december 2008,page 16.

Figure 5: A compariso of the out-of-sample cumulative mothly excess returs versus the S&P 500

Iex for the Creit Suisse 130/30 Iex (Gross) a various other iexes, from October

2007 to december 2008,page 18.

Table 1: Summary statistics for the mothly returs of the Creit Suisse 130/30 Iex (Gross),

a the S&P 500 Iex, from Jauary 1996 to September 2007,page 10.

Table 2: Mothly returs of the Creit Suisse 130/30 Iex (Gross) a the S&P 500 Iex,

i percet, from Jauary 1996 to September 2007,page 11.

Table 3: Correlatios of the Creit Suisse 130/30 Iex (Gross) to various market a hege-fu

iexes, from Jauary 1996 to September 2007,page 12.

Table 4: Mothly turover a aualize trackig error for the Creit Suisse 130/30 Iex,

i percet, from Jauary 1996 to September 2007,page 13.

Table 5: Turover of various S&P iexes, i percet. Source: Creit Suisse Equity

derivatives Group,page 14.

Table 6: Summary statistics for the mothly returs of the Creit Suisse 130/30 Iex (Gross), the

S&P 500 Iex, a various other 130/30 iexes, from October 2007 to december 2008,

page 17.

Table 7: Mothly returs of the Creit Suisse 130/30 Iex (Gross), the S&P 500 Iex, a various

other 130/30 iexes, i percet, from October 2007 to december 2008,page 18.

Table 8: Correlatios of the Creit Suisse 130/30 Iex (Gross), the S&P 500 Iex, a various

other 130/30 iexes to various market a hege-fu iexes, from October 2007 to

december 2008,page 19.

Table 9: Mothly turover a aualize trackig error for the Creit Suisse 130/30 Iex (Gross),

i percet, from October 2007 to december 2008,page 20.


23/24


rEFErENcES

Bsh, J. S., 1997, Comparisons and Combinations o Long and Long/Short Strategies,

Fnancal Analysts Jonal 53, 8189.

Clak, r., H. Slva, an S. Sapa, 2004, Toward More Inormation-Efcient Portolios,

Jonal o Potolo Managmnt 31, 5463.

Clak, r., H. Slva, S. Sapa, an S. Tholy, 2007, Long-Short Extensions: How much

is enough?, lctonc copy avalabl at http://ssn.com/abstact=1001371.

Clak, r., H. Slva, an S. Tholy, 2002, Portolio Constraints and the Fundamental Law

o Active Management, Fnancal Analysts Jonal 58, 4867.

Gnol, r. C., 1989, The Fundamental Law O Active Management,


Gnol, r. C. an r. N. Kahn, 2000, The Efciency and Gains o Long-Short Investing,


Hasanhozc, J. an A. W. Lo, 2007, Can Hedge-Fund Returns Be Replicated?: The Linear Case,

Jonal o invstmnt Managmnt 5, 545.

inchn, A. M., 2002, Whos Long? Market-Neutral versus Long/Short Equity,

Jonal o Altnatv invstmnts 4, 6269.

Jacobs, B. an K. Lvy, 2006, Enhanced Active Equity Strategies,


Jacobs, B. an K. Lvy, 2007, Enhanced Active Equity Portolios are Trim Equitized

Long-Short Portolios, Jonal o Potolo Managmnt 33, 1927.

Jacobs, B., K. Lvy, an d. Sta, 1998, On the Optimality o Long-Short Strategies,


Jacobs, B., K. Lvy, an d. Sta, 1999, Long-Short Portolio Management:

An Integrated Approach, Jonal o Potolo Managmnt 25, 2333.

Johnson, S., r. Kahn, an d. Ptch, 2007, Optimal Gearing, Jonal o Potolo Managmnt 33, 1020.

Lo, A. an P. Patl, 2008, 130/30: The New Long-Only, Jonal o Potolo Managmnt 34, 1238.

Matll, J. d., 2005, Quantiying the Benefts o Relaxing the Long-Only Constraint,

Tchncal pot, Sei invstmnts dvlopmnts.

Sonsn, e. H., r. Ha, an e. Qan, 2007, Aspects o Constrained Long-Short Equity Portolios:

Taking O the Handcus, Jonal o Potolo Managmnt 33, 1222.


24/24

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