Hedge Fund Investing in the Aftermath of the Crisis: Where did the Money Go?

Transcription

1 Hedge Fund Investng n the Aftermath of the Crss: Where dd the Money Go? Gudo Bollger, Ivan Gudott, Florent Pochon Ths verson: July 2010 Abstract Ths paper nvestgates the determnants of hedge fund flows after the crss of We show that after the crss, nvestors mantaned ther tradtonal preference for past bestperformers. In that sense money flows were not smart after the crss. We fnd some evdence, albet mxed, that nflows manly went to the most lqud funds and strateges. Fnally, for sngle hedge funds, the domclaton was also a relevant crteron for allocatons, wth EUdomcled funds the most favoured. We fnally fnd weak mpact of fee structures on allocaton decsons. We are grateful to the referee for hs valuable comments. All remanng errors are our own. Gudo Bollger, Ph.D s Chef Investment Offcer at Olympa Captal Management, 25 Rue Balzac, FR Pars, , gudobollger@olympagroup.com; Ivan Gudott s Quanttatve Analyst at Olympa Captal Management, 25 Rue Balzac, FR Pars, , vangudott@olympagroup.com; Florent Pochon s Head of Rsk Management at Olympa Captal Management, 25 Rue Balzac, FR Pars, , florentpochon@olympagroup.com.

2 In 2008, the hedge fund ndustry posted ts worst performance ever. Even f hedge funds sgnfcantly outperformed equtes, they faled to delver a postve return when nvestors needed t the most. Moreover, many hedge funds had to restrct the lqudty of ther funds by mplementng gates or sde-pockets. To top t all off, the bggest fraud n the hstory of the hedge fund ndustry was dscovered leadng to bllons of dollars of losses. The drect consequence of these events was that the hedge fund ndustry experenced sgnfcant outflows. Accordng to Eurekahedge publcatons, the assets managed by the hedge fund ndustry declned by $470bn between June 2008 and Aprl Fortunately, the flght of nvestors from the hedge fund ndustry stopped n May At ths date, nflows to the hedge fund ndustry exceeded outflows for the frst tme snce June Gven the shock experenced by the ndustry n 2008, t s certanly nterestng to understand f and how the fnancal crss altered the determnants of the flows experenced by hedge funds. In order to do so, we nvestgate the relatonshp between hedge fund flows n 2009 and hedge fund characterstcs. Testable hypotheses Several academc studes nvestgate the relatonshp between hedge fund flows and hedge fund characterstcs. The man fndng of these studes s that money flows nto hedge funds prmarly chase recent good performance (see for nstance Agarwal et al. [2004]). Baquero and Verbeek [2009] contrbute to the lterature by usng quarterly fund flows and modellng n- and outflows separately. They also document a postve relatonshp between flows and past performance but, contrary to Agarwal et al. [2004] who fnd a convex relatonshp, they fnd a lnear one. Xong et al. [2007] use quarterly flows of funds of hedge funds and they also fnd a lnear flow-performance relatonshp. More recently, Dng et al. [2009] extend these studes by nvestgatng the effects of share restrctons. They show that the flow- 2

3 performance relatonshp s always postve but more mportantly that t becomes concave n the presence of sgnfcant lqudty restrctons. Besdes performance, the mportance of the other hedge fund characterstcs on nvestor flows s less crucal. Agarwal et al. [2004] show that nvestors are reluctant to nvest n funds that have longer lockup perods. Baquero and Verbeek [2009] demonstrate that lqudty restrctons mpact dfferently money nflows and outflows. Agarwal et al. [2004] analyse also the mpact of hedge fund manager ncentves on flows. They fnd that nvestors allocate more money to hedge funds wth a greater senstvty of ther total compensaton to the fund s performance. Fnally, Agarwal et al. [2004], Baquero and Verbeek [2009] as well as Dng et al. [2009] document that nvestors prefer smaller and younger funds. Overall, past academc research manly focuses on determnng the shape of the relatonshp between flows and performance. Rather than ths, our study focuses on the potental mpact that the fnancal crss may have had on nvestors recent allocaton decsons. Ths s why we focus exclusvely on the 2009 post-crss flows and formulate our testable hypotheses by nsstng on the events that may have had a sgnfcant mpact on allocaton decson. In the rest of ths secton, we develop fve hypotheses, one for each category of hedge fund characterstcs we consder: 1) rsk and return, 2) sze and age, 3) level and structure of fees, 4) lqudty terms and 5) domclaton. Hedge funds are generally not fully transparent regardng ther ndvdual postons. Ths s why nvestors tend to rely on past performance to take captal allocaton decsons to hedge funds. The extraordnarly dffcult market condtons that prevaled durng the fnancal crss have clearly helped at separatng good managers from bad ones. Gven the great dsperson n performance durng the crss, we predct that past performance has become even more mportant. Smlarly, the ablty of hedge fund managers to manage ther volatlty durng the 2008 stress perod wll probably be vewed as a good proxy for ther capacty to control rsks n the future. Fnally, excessve 3

4 leverage was one of the man performance detractors n As a consequence, we predct that nvestors may be reluctant to allocate new money to managers that have the ablty to use leverage for ther nvestment strategy. Note that ths predcton dffers from past research (see Dng et al. [2009]) that documents that funds wth hgher leverage receved hgher nflows. As t was thought that only good managers can get fnancng, leverage was ndeed seen as a good proxy for the qualty of the fund. Wth the hndsght of the fnancal crss, we can say that ths s far from beng true. Ths leads us to our frst hypotheses: Hypothess 1 a): Funds wth good performance durng the fnancal crss should be assocated wth hgher flows after the crss. Hypothess 1 b): Funds wth low standard-devaton durng the fnancal crss should be assocated wth hgher flows after the crss. Hypothess 1 c): Funds that are more prone to use leverage should be assocated wth lower flows after the crss. Past academc research that nvestgates the mpact of hedge fund sze has come to two mportant conclusons. Frst, smaller-szed hedge funds dsplay more operatonal rsk than bg ones (see Chrstory et al. [2006]). Second, due to capacty constrants n some types of tradng strateges, bgger funds underperform smaller funds (see Agarwal et al. [2004] among others). Ths suggests that, on average, smaller funds outperform bgger ones, but also dsplay much fatter tals. Operatonal rsk has become at the centre stage of hedge fund nvestors concerns after the fnancal crss. The massve outflows experenced by some hedge funds have rased concerns about the ablty of small- to mddle-szed hedge funds to survve wthout sgnfcantly reducng ther costs and thereby lowerng the qualty of both ther nvestment and, more mportantly, operatons team. Ths s why we predct that, n the post-crss 4

5 envronment, operatonal rsk stemmng from sze wll outwegh the performance effect. The same type of argument s vald to predct the relatonshp between the flows and the age of the fund. On the operatonal sde, the partners of older funds can probably nvest more personal wealth n the fund management company than the partners of younger funds who have been collectng fees for fewer years. Ths wll unable partners of young funds to retan key employees after sgnfcant losses of assets. Fnally, gven the hgh level of rsk averson nduced by the 2008 events, nvestors may perceve older funds as more experenced and stable. Ths leads us to our second set of hypotheses: Hypothess 2 a): Funds wth hgher assets under management should be assocated wth hgher flows. Hypothess 2 b): Older funds should be assocated wth hgher flows. Untl the fnancal crss, the level of fees perceved by hedge funds was probably not a major allocaton crteron. Hedge fund managers were perceved as above average qualty managers that deserve to receve hgher fees than mutual fund managers. Emprcal research confrms ths predcton as the relatonshp between management fees and flows s not statstcally sgnfcant (see Baquero and Verbeek [2009]). However, the weak performance delvered by the ndustry n 2008 may have changed the behavour of nvestors and prompted them to become less complacent about the level of both management and ncentve fees. Wth respect to ncentve provsons, Dng et al. [2009] show that there s a postve relatonshp between flows and the exstence of a hgh-water mark provson, as ths better algns the ncentve between managers and nvestors. The same ratonal shall apply to hurdle rate provsons. Hypothess 3 a): Funds wth lower management fees should be assocated wth more nflows. 5

6 Hypothess 3 b): Funds wth lower ncentve fees should be assocated wth more nflows. Hypothess 3 c): Funds wth hgh-water mark provsons should be assocated wth more nflows. Hypothess 3 d): Funds wth hurdle rate provsons should be assocated wth more nflows. Prevous academc research (see Agarwal et al. [2004]) fnd that nvestors prefer more lqud hedge funds mplyng a negatve relatonshp between flows and lqudty restrctons mposed by hedge funds. Gven the extraordnary lqudty restrctons (e.g. sde-pockets) that have been mposed by some hedge funds durng the 2008 crss, we predct that the negatve mpact of llqudty on hedge fund flows should reman sgnfcant. Ths leads us to our fourth hypothess: Hypothess 4 a): Funds wth hgher total redempton perod should be assocated wth fewer nflows. Hypothess 4 b): Funds wth lockup provsons should be assocated wth fewer nflows. Hedge funds are, to a large extent, domcled n offshore centres such as Cayman Islands or Brtsh Vrgn Islands. Compared to onshore funds, the tax treatment as well as the operatonal expenses s generally cheaper for nvestors that nvest n offshore funds. However, the fnancal crss has rased several concerns regardng offshore funds. The most mportant one s probably the lack of transparency, oversght and nvestor protecton of some offshore vehcles. On top of that, developed countres have started to queston the tax treatment of funds domcled offshore. As a consequence, n early 2009 the EU publshed a draft project for a Drectve on Alternatve Investment Funds Managers ( AIFMD ). One aspect of the 6

7 drectve s the possble restrcton on the dstrbuton of offshore vehcles to EU based professonal nvestors. In ths context, we predct that the flows experenced by hedge funds after the crss may depend on ther domclaton. Ths leads us to our ffth and fnal hypothess: Hypothess 5: Funds domcled wthn the EU should be assocated wth more nflows. Methodology In order to test our hypotheses, we run a regresson smlar to the one used by Dng et al. [2009]: Flow = α+ β Perf + β SD+ β Leverage+ β StartSze+ β Age + β D_ OpenForInv estments+ β Total RedemptonPe rod + β D_ EURnonEU+ β D_ US + β D_ Carbbean+ β D_ Emergng+ ε + β D_ LowMgmtFee+ β D_ LowIncFee+ β D_ HghWaterMark + β D_ HurdleRate β D_ Lockup 12 9 (1) We measure Flow as the percentage change of assets under management (AUM) between end Aprl 2009 and May 2010, net of nvestment returns (r): 05/ 10 ( + r) AUM05 / 10 AUM04/ 09 1 Flow= (2) AUM We consder ths specfc perod n order to exclude sales that were manly drven by lqudty needs durng the frst months of As mentoned above, the hedge fund ndustry experenced postve net flows between May 2009 and May 2010 and we can suppose that these flows reled more on nvestors judgements about hedge fund s expected future performance than on pure lqudty needs. In lne wth the hypothess, we group the characterstcs of the funds nto 5 categores. Three varables consder the rsk and return features of the sngle hedge funds: Perf, SD and D_Leverage. Perf s the abnormal return of the fund computed usng the 8 factors model of 7

8 Fung and Hseh [2001] 1 from July 2007 to December Even f July 2007 was not the peak date for the performance of hedge fund ndces, t was the month durng whch the frst sgnfcant problems appeared n the hedge fund ndustry wth both the collapse of the Bear Sterns credt hedge funds and the begnnng of the quant meltdown. December 2008 was the through date of the drawdown for the ndustry as expressed by the HFRX Global Hedge Fund ndex. 2 SD s the standard devaton of returns over the same perod and D_Leverage s a dummy varable that takes the value of 1 f the fund uses leverage and 0 otherwse. As proxy for the senorty of the funds, we use StartSze, the natural logarthm of AUM of the fund as of Aprl 2009, and Age, the age of the fund (expressed n years). D_LowMgmtFee and D_LowIncFee are dummy varables that take the value of 1 f the management fee and ncentve fee are below the sample medan and 0 otherwse. Together wth D_HghWaterMark and D_HurdleRate, two dummes that equal 1 f the fund apples a hgh-water mark or hurdle rate provsons and 0 otherwse, they compose the bucket of varables related to fees. We measure the lqudty restrctons wth TotRedPerod, D_Lockup and D_OpenForInv. TotRedPerod s the sum of redempton frequency and redempton notce, expressed n months. D_Lockup s a dummy that takes the value of 1 f the fund has a lockup and 0 otherwse. To solate the fact that funds open to nvestors can potentally collect more money, we nclude the varable D_OpenForInv. Ths s a dummy varable that takes the value of 1 f the fund s open for new nvestments and 0 otherwse. Fnally, we consdered 5 groups of countres: European Unon (EU), European countres whch are not member of the EU (Channel Islands, Guernsey, Jersey and Swtzerland), North 1 Trend-followng rsk factors can be downloaded from FAC.xls. Other factors were obtaned from Bloomberg. 2 Note that we model the relatonshp between past performance and hedge fund flows lnearly as our man objectve s not to focus on the shape of the relatonshp between past performance and flows. Unreported results show that our conclusons are unaffected by the use of alternatve non-lnear measures such as the TRANK measure used by Dng et al. [2009]. These results avalable upon request by the authors.. 8

9 Amerca (US and Canada), Carbbean Regon (Bahamas, Barbados, Bermuda, BVI, Cayman Islands, US Vrgn Islands, Netherlands Antlles) and emergng countres (Gbraltar, Israel, Kngdom of Bahran, Maurtus, South Afrca and UAE). We consder the mpact of domclaton wth respect to a European domcled fund. We thus nclude dummes for the four latter categores: D_EURnonEU, D_US, D_Carbbean and D_Emergng, respectvely. Dataset Hedge funds returns and characterstcs are obtaned from the HFR database. Instead of relyng on tme seres of AUMs provded by HFR, we created our own seres by usng homemade backups of the statc felds contaned n the database. Ths procedure allows us to reduce the mpact of backfllng bas. Even f we do not formally control for survvorshp bas, we are only margnally concerned by ts mpact. As a matter of fact, our goal s to analyse the actve allocaton decson of nvestors, not the forced ones due to lqudatons. Among the seres contaned n our database, we retan the funds that reported ther AUM both n Aprl 2009 and May 2010 (2491 funds). We then dscard funds that do not state ther domcle (107 funds) and ther returns for the perod between July 2007 and December 2009 (258 funds). Other 60 funds are not consdered because we do not know ther fees (management fee, ncentve fee, hgh-water mark, or hurdle rate), nvestment terms (redempton frequency, redempton notce or lockup), whether they are open for nvestments and f they use leverage. We retan only the funds that report ther fgures (AUM and returns) n USD or EUR (1911 funds). We also dscard 178 funds whose AUMs followed and unrealstc evoluton. 3 Fnally, f a fund has several classes, 4 we retan the one wth the hghest AUM as of May By applyng these flters, we obtan a sample of 1485 funds. 3 We remove from our sample the funds whose AUM decreased by more than 90% ( AUM<-90%), whose AUM dd not change ( AUM=0%) or whose AUM ncreased by more than 10 tmes ( AUM>+1000%). It s very lkely that ths procedure dscards funds that msreported ther AUMs (and not funds that lqudated). In fact, almost all the funds reported returns also n 2010, and the patterns of NAVs do not suggest that these funds are shuttng down. 9

10 Descrptve statstcs Exhbt 1 contans the descrptve statstcs of the net flows observed for our sample from the end of Aprl 2009 to the end of May There s a sgnfcant dsperson between strateges and also wthn strateges. Event Drven s the style wth the lowest medan outflows (-0.6%), whereas Funds of Funds faced the most mportant medan outflows (-15.9%). In addton, Fund of Funds s also the only strategy wth negatve average flows. Standard devatons of flows are relatvely hgh for all the strateges (between 49% and 87 %) whch ndcate that nvestors dscrmnated between funds when they decded ther allocaton. EXHIBIT 1: Descrptve Statstcs of Flows (May 2009-May 2010) No Obs Mean StDev 1 st Q Medan 3 rd Q Skew Kurt All Global Macro Relatve Value Equty Hedge Event Drven Funds of Funds Exhbt 2 dsplays the descrptve statstcs of our contnuous explanatory varables. The dstrbuton of the sze varable s hghly postvely skewed wth some bg funds that ncrease the average sze of the funds contaned n our sample. The average fund s 8-year old, t generated a postve alpha of 0.4% per month over the perod under nvestgaton and t takes about 4 months to redeem from t. Regardng other lqudty terms, 88% of the funds ncluded n our sample have a hgh-water mark, 15% a hurdle rate and 26% a lockup. These fgures are very close to the ones observed for the whole HFR database. 87% of the funds that consttute 4 All the cases are treated wth a trple condton algorthm based on: 1) smlar names, 2) low dstance and 3) hgh correlaton between the returns. Specfcally, fund names are standardzed by removng attrbutes such as Ltd., onshore, offshore, etc., and then funds wth smlar standardzed names are compared two-by-two n terms of correlaton and Eucldan dstance. The dentfed duplcates are then removed accordng to ther AUM. 10

11 our sample report n USD. Fnally, one half of the funds we retaned are domcled n the Carbbean regon, 36% n the North Amerca and 14% n Europe. EXHIBIT 2: Descrptve statstcs of fund s characterstcs Mean StDev 1 st Q Medan 3 rd Q Skew Kurt Start Sze (mo USD) Age (years) Perf (%) SD (%) TotRedPerod (months) Results Exhbt 3 contans the estmated coeffcents and the t-statstcs for the regresson descrbed n Equaton (1). We run t on each strategy separately and on the whole sample. Gven the peculartes observed for Funds of Funds, we also estmate the regresson on the whole sample excludng Funds of Funds. In the latter two regressons, we add dummy varables to control for style effects (the base strateges are Funds of Funds and Relatve Value, respectvely). The second column of the table ndcates the expected sgn of the coeffcents accordng to our hypotheses. We compute the t-statstcs usng the Newey-West [1987] methodology n order to adjust for autocorrelaton and heteroskedastcty. The comments n the followng secton are based on the coeffcent estmated excludng Funds of Funds. Pooled regresson results As we can see from Exhbt 3, the regresson s outcome nvaldates our predctons regardng the mpact of StartSze and Age on hedge fund flows. Smaller funds attracted more money durng the perod than bgger ones. Ths fndng s not due to the ndrect mpact of performance as Perf and StartSze are postvely correlated (.e. bgger funds performed better durng the crss). Smlarly, Age has a negatve, albet not statstcally sgnfcant, coeffcent. These results are consstent wth prevous studes and show that, despte the fnancal crss, 11

12 nvestors allocaton decsons were not heavly mpacted by the addtonal operatonal rsk assocated to both small-szed and young hedge funds. EXHIBIT 3: OLS regressons of net flows (May 2009-May 2010) Expected Sgn All Strateges Wthout Funds of Funds Global Macro Relatve Value Equty Hedge Event Drven Funds of Funds Intercept 0.76 ** 1.27 *** ** 1.75 *** 2.18 ** 0.81 Perf *** 2.71 ** ** 13.3 ** 15.2 *** SD *** *** *** *** ** D_Leverage * ** ** StartSze ** ** * * * ** Age D_LowMgmtFee D_LowIncFee ** D_HghWaterMark D_HurdleRate *** ** 0.03 D_OpenForInv 0.13 ** *** ** 0.28 *** TotRedPerod ** ** ** D_Lockup ** *** D_EURnonEU ** ** 0.09 D_US ** 0.37 *** ** ** 0.11 D_Carbbean ** 0.31 ** ** *** 0.11 D_Emergng ** *** *** D_RV 0.21 ** - D_EH 0.28 *** 0.06 D_GM 0.22 ** D_ED 0.37 *** 0.17 ** Number Observatons Adjusted R squared 7.02% 3.96 % 1.60 % % 5.28% 14.32% 11.82% Note: Values sgnfcant at the 10% are denoted wth *, those sgnfcant at the 5% by ** and those sgnfcant at the 1% wth *** (2-taled tests). Wth respect to performance, both Perf and SD have sgnfcant coeffcents ndcatng that nvestors preferred funds that performed well wth low volatlty. By smultaneously controllng for all the varables, each addtonal percentage pont of rsk-adjusted return ncreased the average flow by 271%. In addton, the flows to levered funds last year were 6% lower than the one to unlevered funds. The relatonshp s not however statstcally sgnfcant and t s strongly nfluenced by the Funds of Funds and the Relatve Value funds. 12

13 Interestngly, ths fndng dffers from the results found by Dng et al. [2009] 5 who document a postve relatonshp between leverage and flows. Ths probably mrrors a combnaton of two effects: frst, a performance effect, snce levered funds were the poorest performers durng the crss, and second, a shft n the preference of nvestors who have become rskaverse to levered funds. Contrary to our predcton, we fnd no relatonshp between the level and the structure of fees and hedge fund flows. In fact, none of the varables related to fees and nvestment terms has a statstcally sgnfcant coeffcent and few of them dsplay the expected sgns. These results are smlar to the ones of Dng et al. [2009] and show that despte the crss, the level and the structure of fees has not become a relevant crteron for nvestors. We fnd mxed evdence for lqudty preference. The coeffcent of TotRedPerod s sgnfcantly negatve, whereas the one of D_Lockup s not sgnfcantly dfferent from zero. Ths means that nvestors consdered the permanent restrcton measured by TotRedPerod but gnored the one-off constrant represented by lockup. Ths result partally nvaldates our predctons and t s at odds wth prevous research (see Agarwal et al. [2004]). Interestngly, the coeffcents assocated to the varables related to the domcle of the fund are all statstcally sgnfcant and dsplay the predcted sgn. Funds domcled wthn the EU dd get the hghest subscrptons. Ths s probably a consequence of the draft of the AIFMD and the ncreasng nterest n UCITS funds. 6 All n all, the evdence of ths pooled regresson s mxed. On the one hand, smlarly to the pre-crss era, n 2009 nvestors mantaned a strong preference for small funds wth hgh past performance and low volatlty. On the other hand, despte the crss, they faled to 5 In ths study the authors run a regresson smlar to ours n order to gauge the mpact of share restrcton on flows. Even f the goal, the methodology (Fama-MacBeth vs. cross-secton) and the dataset (TASS vs. HFR) used are not the same, the relatonshps are generally close to the ones we fnd. 6 About 80% of our sample reported whether they are UCITS complant or not. Among them, 3.5% are UCITS complant. At a strategy level, Equty Hedge s the strategy wth the hghest percentage (~5.5%) of UCITS funds. 13

14 ncorporate fees crtera and only partally ncorporated lqudty crtera n ther nvestment decsons. Compared to our predctons, these results pont out that the crss has not yet fully altered the preferences of nvestors. One excepton s leverage: unlevered funds get hgher flows last year whle nvestors hstorcally preferred geared funds. However, ths result may also be related to performance. Strategy regresson results Gven the heterogenety across hedge fund strateges, we nvestgate whether the flowcharacterstcs relatonshps are strategy dependent. Besdes, heterogenety may also exst among hedge fund nvestors. Ths clentele effect s potentally strong for Funds of Funds, as these nvestors generally do not nvest drectly n sngle hedge funds. To address these ssues, we estmate Equaton (1) for each hedge fund strategy separately. The results are also reported n Exhbt 3. We fnd sgnfcant dfferences between the pooled regresson results and the strategy ones. In fact, only StartSze has a smlar mpact on every sngle strategy as well as on the pooled regresson, even f the coeffcents are not always statstcally sgnfcant. The mpact s always negatve, but ts strength vares across strateges. It s null and non sgnfcant for Global Macro funds, whereas t s stronger and sgnfcant for the other styles. Ths ndcates that nvestors dd not consder the sze of a fund as a proxy for ts safety. In that case, we would observe a postve coeffcent for the StartSze varable, and the magntude should be bgger for strateges supposed to be rsker from an operatonal pont of vew. Also, the strong negatve coeffcent assocated to StartSze for Event Drven funds s consstent wth the nvestors wllngness to avod potental lqudty ssues after the crss. As Event Drven funds generally take concentrated bets on less lqud assets, a hgher amount of assets under management could be vewed as a potental detractor for future performance by nvestors. 14

15 Another varable wth nterestng results s Perf: ts mpact s postve for all the strateges but Global Macro and t s statstcally sgnfcant for Equty Hedge, Event Drven and Funds of Funds. The magntude of the coeffcents vares sgnfcantly across strateges: t s nsgnfcantly dfferent from zero for Global Macro and Relatve Value funds (the strateges wth the hghest medan Perf) and t s hghly postve and sgnfcant for Funds of Funds (the style wth the lowest medan Perf). Hence, performance was a stronger crtera for the loosng strateges than for the wnnng ones. Note also that ths s at odds wth the results of Getmansky [2004] who fnd that the flow-performance relatonshp tends to be stronger for drectonal strateges than for relatve value and event orented ones. Ths may reflect a combnaton of two elements: frst, a wllngness of nvestors to put more emphass on lqudty than on performance of the strategy, and second, a favourable top-down vew for Global Macro funds for There are several other nterestng remarks that can be drawn by lookng at the sngle strategy results. Frst, Relatve Value s the strategy wth the strongest negatve mpact of leverage. Ths s nterestng because ths s the style that tradtonally uses most leverage. As stated prevously, ths specfc leverage effect for Relatve Value funds probably mrrors a performance effect. Second, Global Macro funds dstngush themselves for the coeffcents assocated to the domclaton of the fund. It s n fact the only strategy where funds domcled n the US and Carbbean had hgher flows. Ths s nterestng because n 2008 Global Macro funds had less lqudty problem, fewer sde-pockets and gates than other strateges. As a consequence, nvestors dd not feel the need of the addtonal protecton offered by local regulaton. Thrd, although lqudty had a negatve mpact on flows for every sngle strategy, we found that ths effect was statstcally sgnfcant only for Global Macro and Relatve Value. Ths hghlghts the fact that nvestor duly dscrmnated between lqud and llqud funds 15

16 regardless the nature of the underlyng assets (lqud assets for Global Macro funds, more llqud assets for Relatve Value funds). Fnally, Funds of Funds offer several specfctes as compared to sngle hedge fund strateges. Frst, the coeffcent of Perf s, as expected, sgnfcantly postve wth the hghest pont estmate of our sample, whereas SD has no statstcal mpact. Second, Funds of Funds nvestors preferred funds wth the hghest ncentve fees. In fact, t s the only strategy that loads sgnfcantly and negatvely on D_LowIncFee. Ths may be the consequence of an attempt by nvestors to better algn ther nterests wth the ones of the managers. As such, nvestors may have preferred managers whose compensaton s more dependent on performance. Thrd, the mpact of lqudty restrctons on net flows was also dfferent from sngle hedge fund strateges. Contrary to hedge fund strateges, TotRedPerod s not statstcally sgnfcant whle the one of D_Lockup s strongly and sgnfcantly negatve. Ths means that Funds of Funds nvestors consdered only the one-off restrcton of lockup and faled to ncorporate the permanent one of TotRedPerod. A closer look at the performances of the Funds of Funds by degree of lqudty reveals that ths s not related to a performance effect (.e. llqud Funds of Funds dd not outperform the most lqud ones n our sample). One alternatve explanaton probably les n the presence of lqudty restrctons: funds wth the longest TotRedPerod saw fewer outflows smply because nvestors were locked-n. Concluson Ths paper examnes the mpact of the fnancal crss on the allocaton decsons of hedge fund nvestors. More specfcally, we nvestgate the determnants of the flows to sngle hedge funds and funds of hedge funds observed from Aprl 2009 to May We fnd that past rsk-adjusted performance remaned the key crtera for allocaton decsons n Ths performance effect was however much stronger for the strateges that suffered 16

17 the most durng the crss (Event Drven) and t proved almost nconsequental for Global Macro funds. Gven the very strong negatve correlaton between the sngle strateges performances n 2008 and , ths means that post-crss money was not smart. We also fnd some evdence for lqudty preference, albet mxed. Our results show that nflows were stronger for funds wth low redempton perods n We fnd mxed evdence for a flght to safety. Frst, nvestors dd not favour bg and longestablshed funds. Sze duly remaned a key crteron for allocaton decsons, but nvestors mantaned ther tradtonal bas towards small funds, as they hstorcally tend to outperform bgger ones. Smlarly, age proved unmportant. Second, the use of leverage dd not weght strongly on allocaton decson. Relatve Value funds were the notceable excepton, as they are the most levered managers. Thrd, we fnd a sgnfcant mpact of fund domclaton as EU-based funds attracted sgnfcantly more subscrptons. We lnk ths to the new European regulaton project. Fnally, n lne wth prevous research, we document an nsgnfcant mpact of fee structure. Ths s at odds wth the efforts made by the fnancal ndustry to better algn the nterests of nvestors and managers after the crss. 7 For sngle hedge funds, the rank correlaton between the performances of 2008 and 2009 s -60%. 17

18 References Agarwal, V., N. Danel, and N. Nak. Flows, Performance, and Manageral ncentves n Hedge Funds. Workng Paper, George State Unversty, Baquero, G. and M. Verbeek. A Portrat of Hedge Fund Investors: Flows, Performance and Smart Money., Workng Paper, Erasmus Unversty Rotterdam, Chrstory, C., S. Daul, and J.-R. Graud. Quantfcaton of Hedge Fund Default Rsk. Journal of Alternatve Investments (2006), pp Dng, B., M. Getmansky, B. Lang, and R. Wermers. Share restrctons and Investor Flows n the Hedge Fund Industry. Workng Paper, Fung, W., D.A. Hseh. The rsk n hedge fund strateges: Theory and evdence from trend followers. Revew of Fnancal Studes, Vol. 14, No. 2 (2001), pp Getmansky, M. The Lfe Cycle of Hedge Funds: Fund Flows, Sze and Performance. Workng Paper, MIT, Goetzmann, W., J. Ingersoll, and S. Ross. Hgh Water Marks and Hedge Fund Management Contracts. Journal of Fnance, 58 (2003), pp Newey, W., and K. West. A Smple Postve Sem-Defnte, Heteroskedastcty and Autocorrelaton Consstent Covarance Matrx. Econometrca, 55 (1987), pp Xong, J., T. Idzorek, P. Chen, and R. Ibbotson. Dynamcs of Fund of Hedge Funds: Flow, Sze, and Performance. Workng paper,