Business School W O R K I N G P A P E R S E R I E S Working Paper 2014-103 Are hedge funds uncorrelaed wih financial markes? An empirical assessmen Khaled Guesmi Saoussen Jebri Abdelkarim Jabri Frédéric Teulon hp://www.ipag.fr/fr/accueil/la-recherche/publicaions-wp.hml IPAG Business School 184 Boulevard Sain-Germain 75006 Paris France IPAG working papers are circulaed for discussion and commens only. They have no been peer-reviewed and may no be reproduced wihou permission of he auhors.
Are hedge funds uncorrelaed wih financial markes? An empirical assessmen Khaled Guesmi ab Saoussen Jebri b Abdelkarim Jabri b and Frédéric Teulon a a: IPAG Business School Paris and Nice France b: EconomiX-Universiy of Paris Wes la Défense France ABSTRACT In his paper we examine he correlaions beween hedge fund sraegy indices and asse classes. Based on he Dynamic Condiional Correlaion (DCC) GARCH Model we esimae he correlaions beween hedge fund sock and bond indices during bull and bear markes. The resuls reveal ha here are significan correlaions beween hedge funds and he sock marke especially during he recen financial crisis ha ook place from 2007 o 2009. Keywords : Hedge funds Sock marke. 1. INTRODUCTION According o popular percepion hedge funds are invesmen vehicles whose main objecives are o deliver absolue reurns o invesors during boh bull and bear markes resuling from heir allegedly weak correlaions wih bond and sock markes. The benefi mos ofen cied by porfolio managers is ha hedge funds generae reurns ha are weakly correlaed wih he reurns of muual funds and sandard asse classes. Having addiional asses wih weak or even negaive correlaions wih markes allows for he diversificaion of risk in a mean-variance environmen. This advanage explains he growing populariy of hedge funds among invesors since he mid-1990s. However during he recen financial crisis ha ook place from 2007 o 2009 he bankrupcies of some hedge funds led he hedge fund indusry o be severely criicized by regulaors invesors and he financial press expressing heir concerns regarding his indusry. These evens naurally raise he quesion of wheher hedge fund performance is really uncorrelaed wih markes. This is an imporan issue because invesors need o know wheher he claims of uncorrelaed reurns made by he hedge fund indusry are acually rue or merely a markeing gimmick. Alhough numerous research papers have been wrien abou he correlaions beween hedge funds and financial markes heir resuls vary widely. Some auhors have found weak correlaions including Fung and Hsieh (1997) and Ka and Lu (2002). Fung and Hsieh (1997) showed ha he weak correlaion beween he monhly reurns of hedge funds and hose of radiional asse classes are aribuable o he naure of he rading sraegies employed by hedge funds o achieve heir goal of absolue performance. Ka and Lu (2002) noed ha hedge funds have a weak correlaion wih he S&P 500 index and a near-zero correlaion wih he Salomon Brohers index. However oher sudies have found srong correlaions beween hedge funds and sandard asses (Michell and Pulvino 2001; Brooks and Ka 2002; Agarwal and Naik 2004; Capocci e al. 2005; Boyson e al. 2010). Brooks and Ka (2002) showed ha here are srong correlaions beween he majoriy of hedge fund and equiy indices paricularly he Russell 2000. Agarwal and Naik (2004) also found srong correlaions beween merger arbirage funds during bearish sock markes. This 1
resul is aligned wih he findings of Michell and Pulvino (2001). Capocci e al. (2005) found a posiive and significan correlaion beween hedge fund indices and equiy marke reurns. Boyson e al. (2010) confirm hese resuls finding a srong correlaion beween he reurns of hedge fund indices and he Russell 3000. This paper herefore aims o fill he gap in he exising empirical research regarding he claim ha hedge funds generae uncorrelaed reurns. Our analysis is based on he monhly reurns of en hedge fund sraegy indices (emerging marke dedicaed shor bias equiy hedge sraegy equiy marke neural converible arbirage even-driven merger arbirage muli-sraegy and fund of funds). As main asse classes he repor uses global socks US socks European socks and US bonds. The performance of he asse classes is measured using he MSCI World Toal Reurn Index (MSCI W) he S&P 500 Toal Reurn Index (SPX 500) he MSCI Europe Toal Reurn Index (MSCI EUR) he JP Morgan Global Aggregae US Bond Toal Reurn Index (JPMGG) and he JP Morgan Global Aggregae ex US Bond Toal Reurn Index (JPMGGxUS).The sample period ranges from June 1997 o December 2011. The remainder of he paper is organized as follows. Secion 2 describes he daa. Secion 3 presens he empirical mehodology. The resuls are repored and discussed in Secion 4. Secion 5 concludes. 2. DATA DESCRIPTION AND SELECTION OF HEDGE FUNDS The daa are obained from Hedge Fund Research Inc. (HFR) one of he larges hedge fund daabases available for academic research. We seleced en hedge fund indices for examinaion: four direcional sraegies indices wo arbirage indices hree even-driven indices and one fund of funds index. Marke Trend (Direcional/acical) Index Global macro (GM) hedge funds aim o profi from changes in he global economy as influenced by major economic rends and/or evens. They use leverage and derivaives o accenuae he impac of marke moves. In consequence heir expeced volailiies are very high. Emerging marke (EM) hedge funds inves in equiy or deb in emerging markes. There are no viable fuures or oher derivaive producs ha can be used for hedging. EM hedge funds can be parially hedged via US reasury fuures and currency markes bu heir expeced volailiies are very high. Dedicaed shor bias (DSB) hedge funds are specialized in he shor sales of over-valued securiies. Because losses on shor-only posiions are heoreically unlimied (since sock prices can increase indefiniely) hese sraegies are paricularly risky. Funds following equiy hedge sraegies (EH) mainain posiions primarily in equiy and equiy derivaive securiies. Equiy hedge managers ypically mainain a leas 50 percen exposure o equiies alhough hey may in some cases be enirely invesed in equiies aking boh long and shor posiions. Managers aim o idenify over-valued socks ha can be sold shor. Arbirage Index Equiy marke neural (EMN) hedge funds aim o eliminae end o negae he impac and risk of general marke movemens and heir sraegies can be classified ino wo main subcaegories: marke neural arbirage which aemps o hedge ou mos marke risk by aking offseing posiions and marke neural securiies hedging which invess equally in long and 2
shor equiy porfolios generally in he same marke secors. Due o heir deep exposure o he sock marke he expeced volailiies of hese ypes of funds are generally low. Converible arbirage (CA) hedge funds buy corporae converible bonds while simulaneously shor-selling he common sock of he same companies ha issued he bonds. Arbirageurs seek o ake advanage of anomalies ha can appear beween he price of a bond ha is converible ino shares and he price of hese shares. The idea is o make money from he bond s yield if he bond price increases bu also make money from shor sales if he price of he sock decreases. Because converible bonds and socks can move independenly from each oher his invesmen sraegy is very risky. The expeced volailiy is herefore high. Even-Driven Indices Even-driven (ED) hedge funds focus on price movemens observed in anicipaion of corporae even such as leveraged buy-ous mergers and hosile akeovers. The mos common even-driven sraegies involve disressed securiies and merger arbirage. Merger arbirage (MA) sraegies focus primarily on opporuniies in he equiy and equiyrelaed insrumens of companies ha are currenly engaged in corporae ransacions. Merger arbirage sraegies ypically have over 75% of heir posiions in announced ransacions over a given marke cycle. Muli-sraegy (MS) hedge funds are ypically quaniaively driven and seek o idenify aracive posiions ha exploi spreads involving combinaions of fixed income derivaives equiies real esae and oher insrumens. Managers inves in several hedge fund sraegies promoing he diversificaion of risk. These sraegies require more han 30% of porfolio exposure o be mainained in wo or more disinc sraegies. Fund of Funds Index Fund of Funds (FoF) hedge funds mix and mach hedge funds. This blending of differen sraegies and asse classes aims o provide a high level of diversificaion and more sable long-erm invesmen reurns han any individual fund. Reurns risk and volailiy can be conrolled by he mix of underlying sraegies and funds. 3. EMPIRICAL STRATEGY To illusrae he dynamic condiional correlaion model for our purposes le x be a vecor conaining he reurn volume and implied volailiy series in he following condiional mean equaion: x μ + ε = where ε Ω ~ N( 0 Η ) where μ [ x Ω ] 1 = E 1 is he condiional expecaion of (1) x given he pas informaion Ω 1 and ε is a vecor of errors in auoregression AR(1). Boh are assumed o have condiional mulivariae normal disribuions wih means of zero and a variance-covariance marix Η { h ij }. Assuming ha he reurn volume and implied volailiy series x are deermined by he informaion se available a ime -1 he model may be esimaed using maximum likelihood mehods subjec o he requiremen ha he condiional covariance marix Η be posiive for all values of ε in he sample. We also assume ha μ akes he following form: μ = Φ + Φ x i 0 1 i 1 i (2) 3
where Φ 1 measures he ARCH effec in he daa series. In he radiional mulivariae GARCH framework he condiional variance-covariance marix can be wrien as: Η = D R D where D = diag{ } (3) h i where h i is he esimaed condiional variance. This is calculaed hrough he individual sandard univariae GARCH(11) models as follows: h 2 i = i + α iε i 1 + β ihi 1 ω i (4) where R is he ime-varying condiional correlaion coefficien marix. According o he specificaions in equaion (4) each marke s variance is modeled as a funcion of he consan he square of las period s own residualsε 2 i 1 and he lagged condiional variance h i 1. Afer he basic consrucion above he dynamic correlaion coefficien marix of he DCC model can be furher defined by: R 1 [ ( )] 1 diag Q 2 Q [ diag( Q )] 2 = ( ) Q = q ij [ diag( Q )] = diag 1 1 1 1 2 q 11 q 22... q 1010. 4. RESULTS Figure 1 repors he condiional correlaions beween hedge fund sraegies and he S&P 500 index as esimaed by he asymmeric DCC-GARCH model. The figure shows ha he dynamic condiional correlaions vary over ime beween being posiive and negaive. This resul is consisen wih he findings of Brooks and Ka (2002) Ka and Lu (2002) and Liang (2004) show ha correlaion vary in differen marke condiions. Considering periods of crisis such as during he Asian (June 1997) inerne bubble (March 2000) sub-prime morgage (July 2007) and global financial crises (Sepember 2008) figure 1 repors ha mos hedge fund sraegies are highly correlaed wih he S&P 500 sock index wih he excepions of he DSB and GM sraegies. This finding is in line wih Forbes and Rigobon (2002) who show ha he correlaions beween hedge funds and global socks increase during crisis periods due o he corresponding increases in he volailiy of global equiy markes. Similarly Abugri and Dua (2009) find significan correlaions wih benchmark asses during he pre-2007 period and overwhelmingly insignifican correlaions during he pos-2006 period. Boyson e al. (2010) find evidence ha adverse funding and liquidiy shocks significanly affec hedge fund performance. The decreased correlaions of he DSB and GM sraegies wih he S&P 500 index which are explained by heir negaive equiy marke exposure illusrae he power of he diversificaion employed by hese sraegies in allowing hem o ouperform markes during downurns. I is noeworhy ha he correlaion beween he examined sock index and he majoriy of sraegies is mos significan during he 2007-2008 crisis period. This allows us o conclude ha his laes crisis had a greaer impac on hedge fund reurns han oher crises. These resuls confirm our previous findings. Figure 2 summarizes he monhly sock reurns and condiional variances esimaed by he DCC-GARCH model. From he reurns of differen hedge funds sraegies he presence of (5) 4
clusering volailiy can be recognized: large (small) changes in sraegies end o be followed by large (small) changes of he same or opposie sign. The condiional variance varies beween wo saes: he firs corresponds o recessions characerized by high volailiy and low reurns and he second corresponds o periods of expansion characerized by low volailiy and high yields. 5. CONCLUSION The presen sudy aimed o analyze he correlaions beween hedge funds and passive asse classes (bonds and equiies) over economic cycles conaining criical evens for hedge funds such as he Asian crisis in 1998 he bursing of he echnology bubble in 2000 and he subprime morgage crisis in 2007. The resuls indicae ha in general some hedge funds end o ouperform he examined passive benchmarks making hem seem very aracive from he poin of view of invesors. Insiuional invesors and high-ne-worh individuals have pu significan amouns of money ino hedge funds seeking he high reurns and diversificaion benefis promised by hedge fund managers (see Fung e al. 2008). However during he subprime morgage crisis he hedge fund indusry was unable o generae posiive reurns (independen of marke condiions). Hence in conras o oher research (Fung and Hsieh 1997; Ka and Lu 2002) his sudy finds ha hedge funds have greaer correlaions wih passive asse classes han previously hough especially during periods of recession. Alhough here is evidence ha hedge funds are affeced by financial marke disress i seems ha hedge funds have been more significanly impaced by he recen financial crisis han by previous sress evens. In fuure research we hope o discuss poenial reasons for he increased sensiiviy of hedge funds o marke disress including he increasing size of he hedge fund indusry securiizaion shor-sale bans and he applicaion of forced sales. REFERENCES Abugri B. and Dua S. (2009) Emerging marke hedge funds: Do hey perform like regular hedge funds? Journal of Inernaional Financial Markes Insiuions & Money 19 (5) 834-849. Agarwal V. and Naik N. (2004) Risk and porfolio decisions involving hedge funds Review of Financial Sudies 17 (1) 63-98. Boyson N. Sahel C. and Sulz R. (2010) Hedge Fund Conagion and Liquidiy Shocks Journal of Finance 65 (5) 1789-1816. Brooks C. and Ka H. (2002) The Saisical Properies of Hedge fund Index Reurns and heir Implicaions for Invesors The Journal of Alernaive Invesmens 5 26-44. Capocci D. Corhay A. and Hubner G. (2005) Hedge fund Performance and Persisence in Bull and Bear Markes European Journal of Finance 11 (5) 361-392. Forbes K. and Ribogon R. (2002) No Conagion Only Inerpendence: Measuring Sock Marke Co-Movemens The Journal of Finance 57 (5) 2223-2261. Fung W. and Hsieh D. (1997) Empirical Characerisics of Dynamic Trading Sraegies: The Case of hedge funds Review of Financial Sudies 10 275-302. Fung W. Hsieh D. Naik N. and Ramadorai T. (2008) Hedge funds: Performance risk and capial formaion Journal of Finance 63 (4) 1777-1803. Ka H. and Lu S. (2002) An Excursion ino he Saisical Properies of Hedge Fund Reurns Working paper. Liang B. (2004) On he Performance of Alernaive Invesmens: CTAs Hedge funds and FoF Journal of Invesmen Managemen 2 76-93. Michell M. and Pulvino T. (2001) Characerisics of Risk and Reurn in Risk Arbirage Journal of Finance 56 (6) 2135-2175. 5
Figure 1. Hedge fund dynamic correlaion wih SP500 CORR_SP500_DLEVENT DRIVEN CORR_SP500_DLM ERGER ARBITRAGE CORR_SP500_DLCONVERTIBLE ARBITRAGE - CORR_SP500_DLSHORT BIAS CORR_SP500_DLEM ERGING M ARKETS CORR_SP500_DLEQUITY HEDGE - - - CORR_SP500_DLM ULTI- STRATEGY CORR_SP500_DLM ACRO 0.1 CORR_SP500_DLMARKET NEUTRAL - -0.1 CORR_SP500_DLFOF - Figure 2. Hedge fund monhly reurns volailiy 2 SP500 DLEVENT DRIVEN 015 1 010 005 004 DLMERGER ARBITRAGE 003 002 001 3 20 075 DLCONVERTIBLE ARBITRAGE DLSHORT BIAS DLEMERGING MARKETS 2 15 050 10 1 05 025 050 025 DLEQUITY HEDGE 04 02 DLMULTI- STRATEGY 006 DLMACRO 004 002 003 DLMARKET NEUTRAL DLFOF 02 002 001 01 6