Working Paper The determinants of the flow of funds of managed portfolios: mutual funds versus pension funds

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1 econstor Der Open-Access-Publkatonsserver der ZBW Lebnz-Informatonszentrum Wrtschaft The Open Access Publcaton Server of the ZBW Lebnz Informaton Centre for Economcs Del Guerco, Dane; Tkac, Paula A. Workng Paper The determnants of the flow of funds of managed portfolos: mutual funds versus penson funds Workng Paper, Federal Reserve Bank of Atlanta, No Provded n Cooperaton wth: Federal Reserve Bank of Atlanta Suggested Ctaton: Del Guerco, Dane; Tkac, Paula A. (2000) : The determnants of the flow of funds of managed portfolos: mutual funds versus penson funds, Workng Paper, Federal Reserve Bank of Atlanta, No Ths Verson s avalable at: Nutzungsbedngungen: De ZBW räumt Ihnen als Nutzern/Nutzer das unentgeltlche, räumlch unbeschränkte und zetlch auf de Dauer des Schutzrechts beschränkte enfache Recht en, das ausgewählte Werk m Rahmen der unter nachzulesenden vollständgen Nutzungsbedngungen zu vervelfältgen, mt denen de Nutzern/der Nutzer sch durch de erste Nutzung enverstanden erklärt. Terms of use: The ZBW grants you, the user, the non-exclusve rght to use the selected work free of charge, terrtorally unrestrcted and wthn the tme lmt of the term of the property rghts accordng to the terms specfed at By the frst use of the selected work the user agrees and declares to comply wth these terms of use. zbw Lebnz-Informatonszentrum Wrtschaft Lebnz Informaton Centre for Economcs

2 The Determnants of the Flow of Funds of Managed Portfolos: Mutual Funds versus Penson Funds Dane Del Guerco and Paula A. Tkac Workng Paper November 2000 Workng Paper Seres

3 The Determnants of the Flow of Funds of Managed Portfolos: Mutual Funds versus Penson Funds Dane Del Guerco and Paula A. Tkac Federal Reserve Bank of Atlanta Workng Paper November 2000 Abstract: Due to dfferences n fnancal sophstcaton and agency relatonshps, we post that nvestors use dfferent crtera to select portfolo managers n the retal mutual fund and fducary penson fund ndustry segments. We provde evdence on nvestors manager selecton crtera by estmatng the relaton between manager asset flow and performance. We fnd that penson fund clents use quanttatvely sophstcated measures lke Jensen s alpha, trackng error, and outperformance of a market benchmark. Penson clents also punsh poorly performng managers by wthdrawng assets under management. In contrast, mutual fund nvestors use raw return performance and flock dsproportonately to recent wnners but do not wthdraw assets from recent losers. Mutual fund manager flow s sgnfcantly postvely related to Jensen s alpha, a seemngly anomalous result n lght of a relatvely unsophstcated mutual fund clent base. We provde prelmnary evdence, however, that ths relaton s drven by a hgh correlaton between Jensen s alpha and wdely avalable summary performance measures, such as Mornngstar s star ratng. By documentng dfferences n the flow-performance relaton, we contrbute to the growng lterature lnkng fund manager behavor to the mplct ncentves to ncrease assets under management. We show that several forces combne to weaken the ncentve for penson fund managers to engage n the type of rsk-shftng behavor dentfed n the mutual fund lterature. JEL classfcaton: G2, G1, L1 Key words: mutual funds, penson funds, fund flows, performance evaluaton The authors gratefully acknowledge research support from the Oregon Jont Professonal Schools of Busness Program. They also thank an anonymous referee, Carl Ackermann, John Chalmers, Larry Dann, Wayne Ferson, Laura Feld, Adtya Kaul, Mark LaPlante, Ka L, Tm Loughran, Wayne Mkkelson, Megan Partch, Jm Peterson, Roberta Romano, Paul Schultz, Katherne Spess, Laura Starks, Rene Stulz, and semnar partcpants at the Oregon Research Roundup, Oregon State Unversty, Pacfc Northwest Fnance Conference, Portland Socety of Chartered Fnancal Analysts, Securtes and Exchange Commsson, Tenth Annual Fnance and Accountng Conference (Austn, Texas, 1999), Unversty of Alberta, Unversty of Calforna Rversde, Unversty of Notre Dame, and the 1998 Western Fnance Assocaton meetngs (Monterey, Calforna) for helpful suggestons. The authors also benefted from conversatons wth Wes Wlson. The vews expressed here are the authors and not necessarly those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Any remanng errors are the authors responsblty. Please address questons regardng content to Dane Del Guerco, Lundqust College of Busness, Unversty of Oregon, Eugene, Oregon , , danedg@oregon.uoregon.edu, or Paula A. Tkac, Research Department, Federal Reserve Bank of Atlanta, 104 Maretta Street, N.W., Atlanta, GA , , paula.tkac@atl.frb.org. The full text of Federal Reserve Bank of Atlanta workng papers, ncludng revsed versons, s avalable on the Atlanta Fed s Web ste at To receve notfcaton about new papers, please use the on-lne publcatons order form, or contact the Publc Affars Department, Federal Reserve Bank of Atlanta, 104 Maretta Street, N.W., Atlanta, Georga ,

4 1. Introducton The mutual fund and penson fund segments of the money management ndustry are smlar n many basc ways. Both delver portfolo management servces to ts clents; choose nvestments from the same unverse of rsky assets; and employ both passve and actve fund managers. Due to the expanson of the mutual fund segment over the past decade, they are also comparable n terms of total assets under management and the total number of portfolo products. 1 One mportant dfference n these two ndustry segments, however, s ther dsparate clenteles. The typcal retal mutual fund nvestor dffers substantally from the typcal penson trustee n ther nvestment needs and fnancal background. As a result, these two clent types are lkely to use dfferent crtera when selectng a money manager. Because portfolo managers are typcally compensated as a percentage of assets under management, they have strong ncentves to focus ther efforts on attractng clents, delverng the dmenson of performance or servce that results n ncreased assets. To better understand these mplct ncentves dervng from clent behavor, we analyze whether dfferences n clent characterstcs between these two segments translate nto dfferences n the relaton between manager asset flow and performance. Our work bulds on earler papers by Srr and Tufano (1998), Ippolto (1992), and Patel, Zeckhauser and Hendrcks (1994) who present evdence that a flow-performance relaton exsts n the mutual fund segment. We focus on two man dfferences n clent characterstcs across the two ndustry segments: fnancal sophstcaton and the exstence of agency problems. Usng a complaton of survey evdence, practtoner sources, and academc studes, we argue that penson fund sponsors are more fnancally sophstcated than mutual fund nvestors. In addton, we show that several aspects of the typcal penson manager selecton process can be nterpreted as resultng from the layers of agency relatonshps nherent n the penson segment. Lakonshok, Shlefer, and Vshny (1992), n an overvew of the less studed penson fund segment, argue that penson sponsor offcals as fducares have agency problems that nduce them to value manager characterstcs that are easly justfed to superors or a trustee commttee. The mutual fund segment s qute dfferent n that mutual fund clents nvest only on ther own behalf. We document several dfferences n the relaton between flow and manager characterstcs consstent wth these fundamental clent dfferences. Frst, we fnd that penson fund sponsors appear to be more

5 2 quanttatvely sophstcated than mutual fund nvestors. For example, penson manager flow s sgnfcantly postvely related to rsk-adjusted performance measures, such as Jensen's alpha, and negatvely related to trackng error, a measure of dversfable rsk. Surprsngly, the relaton wth trackng error s most pronounced for penson managers that outperform ther benchmark, ndcatng that sponsors punsh managers who take on dversfable rsk, even f t results n outperformance. Mutual fund manager flow, on the other hand, s unrelated to trackng error and has a strong relaton wth unadjusted raw return performance. We do fnd, however, a sgnfcant postve relaton between mutual fund manager flow and Jensen s alpha. Ths result, whle consstent wth the emprcal fndngs n the prevous lterature, s anomalous n lght of the dfferences n clent sophstcaton between the two segments. We provde evdence suggestng that the strong statstcal relaton between mutual fund flow and Jensen s alpha s drven by a hgh correlaton between alpha and wdely-avalable summary performance measures, such as Mornngstar s star ratng. In partcular, when Mornngstar star ratngs are ncluded as an addtonal explanatory varable n mutual fund manager flow regressons, alpha s no longer sgnfcant. Second, we fnd that penson sponsors appear to prefer manager characterstcs that can be justfed expost to a trustee commttee. For example, we fnd that beatng a market benchmark attracts an addtonal $ mllon n flow to the average penson manager and boosts hs asset growth rate by 20 percentage ponts. Furthermore, we fnd that t s whether or not a manager beats a benchmark that s mportant; the magntude of the excess returns s not sgnfcantly related to flow. In contrast, we fnd that mutual fund manager flow s prmarly postvely related to the magntude of the excess returns, and especally pronounced at the top of the performance dstrbuton. Ths suggests that beatng a benchmark s a dscrete event n the penson segment, possbly because t serves to valdate the manager s competence. Alternatvely, sponsors may smply use the beatng of a benchmark as a low-cost screenng mechansm to narrow the feld of managers under consderaton for hre. We also fnd that the relaton between manager flow and performance s much noser n the penson fund segment. Ths supports the characterzaton of that segment as relatvely more ndvdualzed and nfluenced by non-performance manager characterstcs. Consstent wth prevous research, the mutual fund flow-performance relaton s hghly convex, mplyng that mutual fund nvestors dsproportonately flock to good performers, but do not punsh poor performers by 1 The 1995 Pensons and Investments magazne Top 1000 money managers ssue covered 7953 penson fund products collectvely controllng $3.1 trllon. In the same year, ICI s Mutual Fund Factbook lsts 5357 mutual funds controllng $2.1

6 3 wthdrawng assets. In contrast, the flow-performance relaton s approxmately lnear n the penson fund segment. Penson sponsors wthdraw assets from managers wth poor alpha performance, as well as allocate flow toward good performers. By documentng dfferences n the flow-performance relaton, we contrbute to the growng lterature lnkng fund manager behavor to ther mplct ncentves to ncrease assets under management. The shape of the flow-performance relaton n the mutual fund ndustry mples that wnners take all n ths segment. As a result of the convexty n rewards, mutual fund managers have an mplct ncentve to alter the rsk of ther portfolos to ncrease the chances that they are among the wnners. Brown, Harlow, and Starks (1996) and Chevaler and Ellson (1997) fnd emprcal support for ths predcton. In contrast, we show that several forces combne to weaken the ncentve for penson fund managers to engage n ths same type of rskshftng behavor. In addton to the lack of convexty n the flow-performance relaton and the wthdrawal of assets for poor performance, penson fund sponsors appear to explctly punsh ths type of behavor through ther punshment of hgh trackng error and tendency to fre managers who substantally devate from ther stated nvestment polces. Our comparson of penson fund and mutual fund managers provdes new nsghts nto prevous studes that focus only on mutual funds. In stark contrast to the hgh degree of autocorrelaton n mutual fund flows, we fnd that penson fund flows exhbt very lttle autocorrelaton. We explore reasons why the autocorrelaton of flows appears to be a result unque to mutual funds, and not a unversal characterstc of managed funds. In addton, we fnd large and robust dfferences n the role of asset sze n attractng flow. Large mutual funds attract flow approxmately n proporton to ther sze. In contrast, large penson fund managers attract much less dollar flow than smaller funds, wth the top 10% of managers ranked by asset sze actually losng assets on average. We conjecture that these results are also related to dfferences n agency relatonshps and sophstcaton across the two segments. For example, the hgh degree of autocorrelaton n mutual fund flows may be drven by the allocaton behavor of partcpants n defned contrbuton (401k) retrement plans. The mportance of personal relatonshps and face-to-face contact between penson managers and clents may nduce decreasng returns to scale n ths segment, resultng n a negatve relaton between flow and asset sze. We provde some supportng arguments and prelmnary evdence for these conjectures, as well as dscuss mplcatons for manageral ncentves. trllon n aggregate.

7 4 In a broader sense, ths paper also contrbutes conceptually to the large lterature on fund performance evaluaton. The focus n ths lterature has tradtonally been, do mutual funds exhbt superor rsk-adjusted performance? The puzzle of actve portfolo management whereby mutual fund managers underperform passve benchmarks, yet contnue to attract assets to manage, may be reconcled by shftng the focus to do mutual funds exhbt superor performance n the eyes of ther nvestors? Our results suggest that the answers to these questons mght be qute dfferent. 2. Comparson of the penson fund and mutual fund management ndustry segments In a gven year there s a far amount of hrng and frng actvty n both the mutual fund and penson fund ndustry segments, resultng n a large volume of nflows and outflows. Twenty-nne percent of mutual fund owners surveyed n 1995 ndcated that they had conducted an exchange (transferred out of one fund and nto another wthn the same mutual fund company) and 14% closed an account. Durng that same year, 22% of penson plan sponsors termnated a manager, 28% hred a manager and 15% termnated and hred a manager wthn the year. 2 Prevous evdence suggests that past performance nfluences the manager selecton and termnaton decson, and s thereby an mportant determnant of flow. Despte dfferent sample perods, methodologes, and performance measures, Chevaler and Ellson (1997), Gruber (1996), Patel, Zeckhauser, and Hendrcks (1994), Ippolto (1992), and Srr and Tufano (1998) all fnd that past performance s an mportant determnant of flow n the mutual fund segment. Lakonshok et al (1992) provde some evdence that performance s related to the growth n the number of clents n the penson fund segment as well. Although these studes establsh the mportance of a manager s track record n determnng the amount of assets he controls, there has been relatvely lttle dscusson of whch performance measures and manager characterstcs matter most. A careful comparson of a typcal clent n the two segments wll shed lght on how and why the flow-performance relaton s lkely to dffer across these groups. 2 Unless otherwse noted, the sources for the survey nformaton on mutual fund nvestors comes from varous publcatons from the Investment Company Insttute ncludng: the 1996 natonal survey of mutual fund nvestors The People Behnd the Growth, the 1993 survey Understandng Shareholder s Redempton Decsons, the 1997 survey Understandng Shareholder s Use of Informaton and Advsors, and the 1996 survey Shareholder Assessment of Rsk Dsclosure Methods. (All avalable at Unless otherwse noted, the survey nformaton on penson fund sponsors comes from varous surveys by Greenwch Assocates (compled n Investment Management Report 1996 and 1997).

8 5 As of 1995, the mutual fund segment served more than 30 mllon households whle the penson fund segment served around 45,000 corporate and publc plan sponsors and endowments. The medan mutual fund assets per household s $18,000 whle the average penson fund assets s n the range of $67 mllon. 3 Indvduals typcally have a much smaller portfolo of managers to montor: the medan household owns three mutual funds wth two dfferent fund famles. The average number of portfolo managers per plan sponsor s 8.9, wth plans over $1 bllon n assets employng as many as 20 managers. These basc dfferences mply that a penson fund manager s flows wll be much more dscrete, as the loss or gan of one or two clents may change assets under management by mllons of dollars. In addton, by controllng a large amount of assets penson fund sponsors have more market power n contractng for portfolo management servces than mutual fund nvestors. Indeed, Halpern and Fowler (1991) report that fees vary consderably by penson fund clent for the same manager. The queston of nterest s how these two very dfferent clent pools allocate money to the managers competng for ther assets. In ths secton we focus on two clent dfferences that wll gude our emprcal analyss of the relaton between flow and performance n these two ndustry segments Clent dfferences: fnancal sophstcaton The typcal penson fund clent s arguably more fnancally sophstcated than the typcal mutual fund nvestor. Penson fund sponsors are often fnance professonals wth expertse n the area of nvestment management. In addton, most penson sponsors rely heavly on the recommendatons of consultants when decdng whch managers to hre or retan. As a result, the performance evaluaton measures favored by consultants lkely nfluence the relaton between flow and performance n ths segment. A consultant s screenng servce generally ncludes a hgh degree of quanttatve analyss ncludng rsk-adjusted measures such as Jensen s alpha, the Sharpe measure, and trackng error. These measures are commonly found n many of the avalable penson manager databases and evaluaton software packages. In addton, frms such as BARRA, Mobus, and Wlshre Assocates market software that performs sophstcated return attrbuton analyss that decomposes portfolo returns nto exposure to varous passve ndces. 3 McGraw-Hll s 1995 Money Market Drectory and the 1995 Drectory of Penson Funds and ther Investment Managers (McGraw Hll).

9 6 Trackng error, n partcular, s a commonly used measure n ths ndustry segment. Besdes beng a standard measure ncluded n popular clent software packages, at least nne artcles on trackng error have appeared snce 1992 n the practtoner-orented Journal of Portfolo Management and Fnancal Analysts Journal. Trackng error, a measure of dversfable rsk, measures the volatlty of a portfolo s devaton from benchmark returns. One performance measure advocated by penson consultants and academc researchers, the apprasal rato, uses trackng error as a component. 4 The apprasal rato s defned as Jensen s alpha dvded by dversfable rsk (trackng error), and can be nterpreted as a beneft-to-cost rato of an actvely managed portfolo. The proper applcaton of an apprasal rato mples that after controllng for alpha, a sponsor should optmally allocate captal to managers wth lower trackng error. Managers n the penson segment are often selected and evaluated accordng to ther nvestment style or specalty. For example, a sponsor may conduct a search for a manager that nvests only n large-captalzaton value stocks. As a result, the sponsor would compare a potental manager s track record to an ndex of value stocks or other large-cap value managers. Vrtually all penson managers state ther nvestment style and benchmark when marketng themselves to potental clents. The more sophstcated (quanttatve) methods of rsk adjustment and benchmarkng that are commonplace n the penson fund ndustry do not appear to be common among mutual fund owners. 5 Capon et al (1996) report that 75% of recent mutual fund purchasers surveyed dd not know the nvestment style of ther funds, and 39.3% dd not know whether ther fund was a load or no-load fund. When choosng a fund or montorng a current nvestment, mutual fund nvestors typcally rely on sources of nvestment advce or nformaton less lkely to endorse sophstcated rsk-adjusted measures of fund performance. Most use the meda for nformaton: 53% use newspapers, magaznes or nvestment newsletters (most frequently mentoned are the Wall Street Journal and Money magazne) and only 19% consult a ratngs servce lke Mornngstar or Lpper. Accordng to a 1995 Money magazne poll of mutual fund nvestors, only 26.7% sad they compared ther fund s return to a benchmark. 6 4 For example, see Treynor and Black (1973) and Bode, Kane, and Marcus (1999), p Admat and Pflederer (1997) present a model n whch tyng manager compensaton drectly, or ndrectly through flow, to observed benchmark-adjusted performance does not lead to optmal portfolos, or algned ncentves between the manager and clent. Nevertheless, we refer to the use of benchmarks as sophstcated n the sense that they are quanttatve measures endorsed by penson consultants and portfolo theory. 6 Why Funds Don t Beat the Market, Money (August 1995, pp )

10 7 A confoundng factor n a characterzaton of mutual fund nvestors as unsophstcated s that 59% of mutual fund owners consult wth a fnancal advsor such as a broker or fnancal planner before purchasng mutual funds. In addton, fund recommendatons n newspapers and magaznes are typcally based on performance measures that ncorporate some form of rsk adjustment. Many fund advertsements feature Mornngstar star ratngs based on fund rankngs on both rsk and return. Together, these factors may mplctly ntroduce an element of more sophstcated decson makng nto the fund selecton process. However, the magntude of ths effect s an emprcal queston. These dfferences n the level of clent fnancal sophstcaton suggest that dfferent performance measures may be mportant n each ndustry segment. We expect flow n the penson fund segment to be related to rsk-adjusted measures of performance such as Jensen s alpha, trackng error, and style-adjusted returns. Flow n the mutual fund segment s lkely to be more closely related to raw returns and summary performance measures, such as popular rankngs lke Mornngstar stars Clent dfferences: the manager selecton process and agency ssues Relatve to the mutual fund segment, manager selecton s often a lengthy and costly process for penson sponsors. Many retan consultants such as Wlshre Assocates, Frank Russell, or RogersCasey to montor the performance of current managers and make hrng and frng recommendatons. Greenwch Assocates reports that for every manager actually selected by the average fund, 22 are screened by penson fund consultants, 16 complete a wrtten questonnare, 5 are ntervewed personally, and 4 reach the fnal set. Thus, a strong track record s only a startng pont n attractng clents as presumably only those wth good records make t to the ntervew stage of the process. Survey and anecdotal evdence suggest that non-performance manager characterstcs such as personalty, credblty, reputaton, and attentveness are very mportant n the ultmate hrng and retenton decson. For example, 25% of plan sponsors lsted a lack of credblty wth nvestment commttee or trustees as the reason for termnaton of ther manager. Accordng to scorng sheets from CalPERS recent manager search, only ten ponts out of 550 were allocated to performance for those managers makng t past the ntal screenng, whle 150 ponts were allocated to the nvestment commttee ntervew. 7 Most sponsors frequently meet one-on-one wth ther managers to ask questons, examne holdngs, and assess performance. For

11 8 example, 78% of sponsors meet at least once a year wth the most mportant managers and apparently value personal contact hghly. 8 Overall, the pcture emergng from ths ndustry segment s that manager characterstcs unobservable to a researcher play an mportant role n attractng penson assets. In contrast, mutual fund nvestors have lttle opportunty for personal contact wth portfolo managers, and are more lkely to rely on a track record or a fund analyst s report to gude ther decson. Even Mornngstar nputs only quanttatve varables nto ts star ratngs even though they are clearly nfluental enough to gan access to fund management. It s not clear why penson sponsors rely so heavly on hred consultants and qualtatve characterstcs when choosng a portfolo manager. One vew s that hrng an expert to screen the unverse of managers based on quanttatve performance measures, and then evaluatng fnalsts on qualtatve varables, s a cost-effectve method of judcously montorng large sums of penson labltes. Perhaps sponsors are better able to dscern aspects of manager skll and predct future performance from face-to-face meetngs than through past performance alone. Alternatvely, Lakonshok, Shlefer, and Vshny (1992) argue that these practces can be nterpreted as evdence of an agency problem. The majorty of penson fund assets are n defned beneft plans, where typcally a corporate treasurer, as a fducary, s responsble for nvestng the penson assets. 9 Lakonshok, Shlefer and Vshny (1992) argue that an agency problem between senor corporate management, the corporate treasurer, and the outsde portfolo managers can account for many facts about the penson fund segment. Specfcally, snce the corporate treasurer must answer to senor management n the event of nferor plan performance, he may choose managers and strateges that reduce hs own job rsk. As a result, he may tend to choose strateges where blame can be easly transferred to others and hs decsons can be defended ex-post. For example, Lakonshok, et al argue that the common practces of externally managng penson assets and hrng professonal penson consultants are popular because they provde convenent scapegoats n the event of an unpleasant outcome. 10 Under ths agency nterpretaton, we expect that sponsors value manager characterstcs that reduce a corporate treasurer s job rsk. For example, outperformng a market benchmark may be convncng evdence Accordng to a Nelson/Wlshre poll, a recent trend toward the ntroducton of clent servce personnel to nteract wth sponsors n place of the portfolo management team s vewed negatvely by 65% of the plan sponsors surveyed. 9 Accordng to Greenwch Assocates, 86% of corporate pensons managed 63.2% of ther penson assets va defned beneft plans n Eghty-sx percent of penson plans surveyed by Greenwch Assocates managed less than 5% nternally n Sxty percent of penson plans surveyed by Greenwch Assocates used the servces of a penson fund consultant n 1994 and 84% of those used ther consultant to montor current managers n addton to provdng other servces.

12 9 of competency to trustees, even f the manager was not a top performer among peer managers. Indeed, a recent survey of sponsors ranked performance relatve to market ndces as more mportant than the nvestment performance of other managers. 11 In ths envronment, managers who take concentrated bets on stocks and consequently devate substantally from market benchmarks take a rsk of beng wrong and alone. 12 Trackng error captures ths dea because t dynamcally measures the volatlty of a portfolo s devaton from benchmark returns. Bernsten (1998) dscusses ths ssue, statng that clents love affar wth benchmarks has made large trackng errors extremely perlous for [penson] managers. Thus, clent attenton to trackng error can be nterpreted as the result of agency problems because t focuses on the cost of manager bets that devate from the benchmark, whle gnorng the potental beneft n terms of ncreased return. Dfferences n the manager selecton and evaluaton processes n the penson fund and mutual fund segments suggest three dfferences n the relaton between flow and performance. Frst, trackng error and performance relatve to a market ndex are lkely to be related to penson fund flows and not mutual fund flows, both because of agency reasons and because of ther relance on sophstcated concepts lke benchmarkng. In addton to beng less quanttatve, mutual fund nvestors do not need to justfy hrng decsons to superors or benefcares. Second, we should observe lower explanatory power of quanttatve performance measures n explanng flow n the penson fund segment, because qualtatve manager characterstcs are generally more mportant to penson fund sponsors than to mutual fund nvestors. 13 Note that ths does not necessarly contradct the noton that penson sponsors are more quanttatvely sophstcated than mutual fund nvestors. A weak statstcal relaton may suggest that sponsors use quanttatve measures prmarly as a frst screen, or as a supplement to qualtatve manager characterstcs. If penson sponsors are more sophstcated, however, then those performance measures that are related to flow should be the rsk-adjusted and quanttatve varety, and not raw returns. Fnally, dfferences n the attenton pad to montorng managers suggest that penson fund 11 Tme Horzons of Penson Fund Managers, by Fnancal Executves Research Foundaton, Mark Krtzman, Wrong and Alone, Economcs & Portfolo Strategy (New York: Peter L. Bernsten, Inc. :1998) 13 We recognze that non-performance factors such as fund reputaton or servces may be mportant to mutual fund nvestors as well. However, they are unlkely to greatly weaken the cross-sectonal relaton between flow and performance because reputaton n the mutual fund ndustry s largely based on marketng, whch also tends to focus on performance. In addton, there s a great deal of homogenety n servces offered across fund complexes, mplyng lttle cross-sectonal dsperson along ths dmenson.

13 10 sponsors are more lkely to punsh poorly performng managers by wthdrawng assets than mutual fund nvestors. 3. Descrpton of the sample 3.1. Penson fund sample Data on penson fund money managers are from the June 1995 M-Search Database compled and dstrbuted by Mobus, Inc. Ths database contans numerous frm and manager characterstcs for 1320 management frms offerng approxmately 4500 portfolo products over the perod 1985 to Each management frm typcally offers more than one nvestment product, each wth a gven style or objectve. As n studes of the mutual fund ndustry, the unt of analyss s the ndvdual fund product (e.g., the analog of Fdelty Magellan). Although other terms such as fund or product are often used, we wll refer to ths unt of analyss as the fund manager. For each manager we have an annual tme-seres of assets under management and the number of dstnct clents, and quarterly returns. Assets and clent numbers are broken down by tax treatment of the clent account (tax-exempt, taxable) so that we are able to solate the flows from tax-exempt, fducary clents. Tax-exempt clents, who control approxmately 88% of total sample assets, nclude unversty endowments and non-proft foundatons n addton to publc and corporate penson sponsors. We collectvely refer to ths clent group as penson fund sponsors. The Mobus database s sold prmarly to sponsors to ad n selectng and montorng portfolo managers. Managers do not pay to be ncluded n M-Search, and Mobus does not provde any consultng servces for manager selecton or evaluaton. A typcal use of the Mobus database s to do an ntal screenng of managers wth a certan nvestment style. The data are provded to Mobus va self-reported manager surveys. Whle ths may cause some concern regardng the qualty of the data, management frms do have an ncentve to provde Mobus wth complete, accurate, and tmely nformaton. Managers have an ncentve to be complete snce M- Search screens wll exclude a manager from a search f data are mssng. They arguably have an ncentve to be accurate, snce clents may check the data of the managers who make ther fnal screen aganst alternatve sources (e.g., Nelson s Drectory of Investment Managers, Pensons and Investments, prvate consultants,

14 11 etc). 14 Fnally, they have an ncentve to be tmely snce Mobus wll drop a frm after falng to report returns for three consecutve quarters. To focus on a set of relatvely homogeneous managers, we analyze only actve domestc equty managers who nvest accordng to a growth, value, or general equty nvestment style. As a result, we exclude all non-equty, nternatonal, and passve ndex managers. Investment style s determned as of December 1994, and appled to the hstorcal data for each manager. We use product names and supplementary managersuppled style nformaton on M-Search to assgn each penson fund manager to a style category. Usng a smlar style classfcaton on ths same data set, Horan (1998) reports that the Mobus growth and value style categores are consstent wth a classfcaton usng loadngs on the Fama-French book-to-market factor (HML). Due to data requrements and qualty reasons, we mpose four addtonal screens. Frst, because we use three-year performance measures n our emprcal tests we requre portfolo returns to be avalable for three consecutve years. Most penson sponsors and consultants requre the exstence of a three-year performance track record to be consdered n the ntal phases of a manager search. Second, we requre returns to be total returns, ncludng cash holdngs, gross of management fees. We analyze gross returns because they are reported more frequently than net returns, resultng n a larger sample, and because, unlke the mutual fund ndustry, fees vary consderably by clent. 15 Thrd, we requre each set of returns to be the composte of all fully dscretonary portfolos managed by the frm n a gven style, ncludng the performance of any portfolos termnated durng the measurement perod. Ths ensures that the analyzed returns measure the manager s actual performance, as opposed to the performance of a self-selected representatve composte of hs portfolo. 16 Fnally, to ncrease 14 Nelson s Drectory s a comprehensve prnt drectory based on the survey responses of approxmately 2500 money management frms wth U.S. nsttutonal clents, ncludng those frms based outsde of the U.S. To check the accuracy of our data, we compared a subsample to numbers presented n Nelson s drectory. Nnety percent of ths subsample ether matched exactly or were wthn 10% of the values reported n Nelson s. In addton, Coggn and Trzcnka (1995) report that checks of the Mobus data aganst the March 1993 PIPER database confrmed the accuracy of the Mobus data. 15 Other studes of penson fund manager performance such as Lakonshok, Shlefer and Vshny (1992) and Coggn, Fabozz, and Rahman (1993) also use returns gross of fees. Chrstopherson, Ferson, and Glassman (1998) conduct ther tests usng returns gross of fees, and wth an estmate of fees subtracted out. As we descrbe later, our soluton to the ssue of comparablty of mutual fund and penson fund managers s to add back fees and expenses to mutual fund returns to check the robustness of the results. 16 In most cases, the composte s the market-value weghted average of portfolos managed n a gven style. In a few nstances, an equally weghted composte was used when market-value weghted composte returns were unavalable.

15 12 the precson of our tests we exclude managers that control less than $20 mllon n tax-exempt assets. 17 These restrctons leave a fnal sample of 562 penson fund managers from 388 management frms, for a total of 2,461 manager-year observatons over the 1987 to 1994 perod. These 562 managers control assets that aggregate to $634 bllon at the end of 1994, whch represents 47% of the 1994 actvely managed domestc equty ndustry assets accordng to fgures from the 1996 Nelson s Drectory. Data avalablty lmts us to analyzng only annual measures of flow, whch mples that we effectvely gnore the short-term dynamcs of nvestment and redempton behavor. However, whle managers are clearly affected by daly and weekly flows that requre effcent cash management, t s not clear that the overall ndustry pcture that we are studyng here would beneft from hgher frequency flow measurement. For example, monthly flows are largely due to sponsor-specfc cash needs and the desre to rebalance the overall sponsor portfolo, and less lkely to be due to the hrng and frng of managers for performance reasons. In addton, most other cross-sectonal studes of the flow-performance relaton use annual data, so ths allows us to better compare our results Mutual fund sample All data on mutual fund managers are from Mornngstar, Inc. s July 1995 Mutual Funds OnDsc. By usng the same data avalablty crtera and screens descrbed above, we arrve at a sample of 483 mutual fund managers n 352 dfferent fund famles for a total of 2,676 manager-years. Specfcally, we requre the funds to be all-equty mutual funds n the growth, value, or domestc equty styles wth three years of consecutve returns data. We also exclude funds that are closed to new nvestors and nsttutonal funds that have nvestment mnmums greater than $25,000. In addton, we exclude the manager-years where the fund merged wth another fund, snce the flow measures may be dstorted. 18 We restrct our sample to annual observatons n the perod from 1987 to 1994 to be drectly comparable to the penson fund sample. Our fnal sample of 483 managers aggregate to $389 bllon at the end of 1994, whch represents approxmately 55% of the 1994 domestc equty mutual fund ndustry assets accordng to fgures from the 1996 Mutual Fund Factbook. We use 17 For example, the standard devaton of percentage flow s 40 tmes greater n the sample funds wth less than $20 mllon n assets than n the rest of the sample. 18 We thank Judy Chevaler for provdng a lst of merged mutual funds and merger dates. We supplemented ths lst wth the lst of fund mergers n Wesenberger to completely cover the perod.

16 13 the Mornngstar-assgned style code (nne categores broken down by market captalzaton and by growth, value, or blend) to classfy mutual funds nto style categores smlar to those n the penson fund sample. As n the penson manager sample, nvestment style s determned as of December 1994 and appled to the hstorcal data for each manager. Chan, Chen, and Lakonshok (1998) report that the mutual funds n ther sample generally had consstent styles over tme Potental bases Our sample of fund managers contans only the frms exstng or ncluded n the Mobus or Mornngstar databases as of June If poorly performng frms and/or managers have dropped out of the database durng the sample perod, ths may nduce survvorshp bas. Several recent studes, ncludng Grnblatt and Ttman (1989), Brown and Goetzmann (1995), Malkel (1995), Carhart (1995), and Elton, Gruber, and Blake (1996), have confrmed the economc sgnfcance of survvorshp bas n equty mutual fund performance studes. We are not aware of any evdence on survvorshp bas n the penson fund segment, but we have reason to beleve that t s less prevalent n the data than for the mutual fund segment. 19 More mportantly, three studes have confrmed that survvorshp bas does not affect nferences on the flow-performance relaton. Srr and Tufano (1998), Chevaler and Ellson (1997), and Goetzmann and Peles (1997) repeat ther analyses on samples free of survvorshp bas and report no changes n nferences. Fnally, because managers jon the databases at dfferent tmes n ther hstory (.e., not just when the fund starts up ntally), our results may also suffer from back-fll bas. For example, managers may have a greater ncentve to volunteer nformaton to Mobus after a perod of good performance. Snce Mobus began sellng ts database n 1989, the number of covered manager products has grown by 500%. Agan, however, any survvorshp or back-fll bas s lkely to be less severe n our study of the relaton between flow and performance than n a study that attempts to characterze the average performance of fund managers Measures of flow and performance 19 Not all managers deleted from Mobus are poor performers. Accordng to sources at Mobus, managers are also deleted from the Mobus database when they are successful and closng to new clents, or when they do not fnd Mobus to be a productve source of clent contacts. Also, due to the mportance of clent contact and servcng dscussed n Secton 2, poor performance s not the sole reason for a frm to go out of busness n the penson fund segment. To assess the potental severty of the survvorshp bas n our sample we obtaned from Mobus a lst of frms deleted n Of 89 deleted frms we were able to fnd 71 (80%) lsted n Nelson s 1995 Drectory ndcatng that they had not gone out of busness, but were dropped from the database for other reasons. Of these, 31 (35%) were also lsted n Nelson s 1996 Drectory. Of those wth return data for 1993, the 1993 return dstrbuton for the sample and deleted groups are not statstcally dfferent.

17 14 We analyze three measures of net manager flows. The frst s the annual net dollar flow n or out of a fund, defned as the annual change n total net assets mnus apprecaton. Flow t = TNA t TNA t-1 (1 + R t ) The second measure, net percentage flow, scales net dollar flow by the total net assets n year t-1 and can be nterpreted as an asset growth rate net of apprecaton. In robustness checks, we also analyze the percentage change n the number of penson clents as an alternatve measure of flow. Clent data are useful for studyng the more dscrete penson fund flows, where ganng or losng one clent results n mllons of dollars n flow. Whle most prevous papers n the mutual fund flow-performance lterature have analyzed only percentage flows, we focus on the dollar measure. Conceptually, the dollar flow measure more precsely addresses our queston of nterest, what drves nvestment dollars across the two ndustry segments? As noted n prevous studes, however, percentage flow may be preferable when dollar flow s postvely related to fund sze, whereby larger funds attract hgher flows regardless of performance. Whle there s ndeed a strong postve emprcal relaton between dollar flows and fund sze n the mutual fund segment, the penson fund segment dsplays the opposte relaton. The unvarate correlaton between fund sze and dollar flow s a statstcally sgnfcant Controllng for a potental sze effect n a multple regresson format, rather than by scalng the flows, preserves ths nformaton for analyss. We address possble reasons behnd the dfferent flow-sze relaton across the ndustry segments n Secton 4.5, and we note n the text any nstances where results dffer across the two flow measures. There are many ssues that surface when decdng on a set of performance measures to study. The performance evaluaton lterature s large, and there s consderable debate as to whch measures are most approprate. Snce a goal of ths paper s to nfer whch measures are mportant to clents n each ndustry segment, we focus on the measures suggested by our study of clent characterstcs outlned n Secton 2. Specfcally, measures expected to be mportant to penson sponsors as a result of ther fnancal sophstcaton, use of consultants, and potental agency problems nclude: performance relatve to the S&P 500 market benchmark, style-adjusted performance, trackng error, and rsk-adjusted measures such as a one-factor Jensen s alpha. Measures expected to be mportant to mutual fund nvestors nclude hstorcal raw returns and summary rankngs wthn ther style objectve (a proxy for meda rankngs). All of these performance measures

18 15 are annualzed, and lagged so as to be observable to the clent before a hrng decson s made. The appendx defnes these varables Comparatve summary statstcs Table 1 contans manager-year statstcs that hghlght some of the basc smlartes and dfferences across the two segments. The dstrbuton n assets under management ndcates skewness n both segments, but there are clearly larger asset pools n the penson manager sample. As mentoned earler, penson manager flows are expected to be relatvely lumpy, as the medan number of clent accounts s only 14 versus 12,609 for mutual fund managers. Combnng these clent statstcs wth the medan assets under management n each ndustry mples that the typcal penson clent has a $21 mllon nvestment wth the medan manager, whle the typcal mutual fund clent has $13,000. Comparng the flow dstrbutons provde the frst ndcaton that there are nterestng dfferences between the two ndustres. Although both dstrbutons are centered approxmately at zero, the tals appear to be qute dfferent. Consstent wth prevous studes, the dstrbuton of mutual fund flows appears to be asymmetrc. The top 5% experence net nflows nearly three tmes larger than the outflows at the bottom 5% ($302 mllon n nflows versus $109 mllon n outflows). In contrast, the dstrbuton of penson manager flows s more symmetrc; the bottom 5% of penson managers actually suffer larger dollar outflows than the top 5% gans, $524 mllon n outflows versus $400 mllon n nflows. These statstcs, along wth the results of Srr and Tufano (1998) and Chevaler and Ellson (1997), suggest that the shape of the flow-performance relaton may dffer n the two ndustres. We explore ths possblty n secton 5. Unlke the flow dstrbutons, the dstrbutons of performance measures are smlar, especally f returns are measured gross of management fees for both segments (not reported). We also fnd that the dstrbuton of manager-years n the broad domestc equty, growth and value style categores s roughly smlar n both samples. Panels B and C of Table 1 contan parwse correlaton coeffcents of our flow and performance varables, estmated separately for each ndustry segment. The parwse correlatons between performance varables are not hgh enough to cause concern over multcollnearty problems n our regressons. 4. Relatng flow and performance n the two ndustry segments

19 16 In secton 2 we argue that dfferences n the typcal clent n the mutual fund and penson fund segments mply dfferences n the relaton between flow and performance. In ths secton, we test for these dfferences usng a lnear regresson framework relatng both dollar and percentage cross-sectonal flows, pooled over eght years, to lagged performance measures. In addton to control varables for asset sze, fund age, and lagged flow, we nclude a set of sxteen tme-style nteracton dummes, one for each year and style combnaton. For example, V88 = 1 f ths observaton s a value manager n the year 1988, and 0 otherwse. Ths specfcaton fts a separate ntercept for each year-style category of the data. The tme component of the nteracton term pcks up any cross-sectonal correlatons n the observatons due to dfferng average flows across sample years. The style component adjusts for the fact that n any gven year, growth funds may experence average flow that s sgnfcantly dfferent from that of value funds, or of general equty `funds. Combnng the tme and style components adjusts for both of these potental effects. Includng ths set of nteracton terms reduces ths source of correlaton n the resduals, mtgates bas, and ncreases the precson of our estmated coeffcents. Several of the nteracton term dummes are sgnfcant n all specfcatons, suggestng that the correcton s necessary. In addton, all t-statstcs reported n the tables are based on a correcton for heteroskedastcty usng the method of Whte (1980). Our hypotheses regardng the expected dfferences between the flow-performance relaton n the two ndustry segments mply that some varables should be sgnfcant determnants of flow n only one segment (e.g., trackng error n the penson segment). We therefore estmate the flow-performance regressons separately for each segment, and compare the relatons across the two segments. For completeness, we also report n the tables the results of t-tests comparng the magntudes of the estmated coeffcents across the segments. In general the t-test results confrm the sgnfcance analyss, and as a result, we dscuss them only when the results requre explanaton. We also conduct numerous robustness checks of the data. 20 For smplcty we report only the results of the robustness checks that affect our nferences. Thus, all other results can be assumed to be robust to alternatve specfcatons. 20 We repeated our tests usng mutual fund returns gross of management fees and expenses (addng annual fees and expenses back n to annual returns and annual alphas.) For the penson fund sample, we repeated all tests usng the percentage change n number of clents as the dependent varable flow measure. We also repeated our tests after frst elmnatng the largest 10% of both samples n asset sze; we also analyzed the sample after removng the smallest managers n asset sze (<$250 mllon n assets). Fnally, we repeated our tests usng style-specfc (growth, value, and generc domestc equty) benchmarks nstead of only the generc S&P500 benchmark.

20 17 We begn wth an analyss of the relatve fnancal sophstcaton of the two clent groups. Next, we consder the role of performance benchmarks n each ndustry. Fnally, we explore whether the lack of punshment for poor performance documented for mutual funds extends to the penson fund segment. Ths has partcular mportance for determnng the mpact of flow on manageral ncentves Whch type of performance matters? Gven the relatve fnancal sophstcaton of penson sponsors, we expect to fnd that rsk-adjusted performance measures are sgnfcantly related to penson manager flow. Smlarly, consstent wth prevous research, we expect to observe that unadjusted raw returns explan mutual fund manager flow. We begn our analyss wth a parsmonous test of ths hypothess that wll also allow for comparson wth the results n prevous flow-performance studes of mutual funds. Specfcally, for each ndustry segment we regress flows on lagged returns, one-factor Jensen s alpha, and trackng error, poolng eght years of cross-sectonal data from These regressons also nclude control varables for asset sze, lagged flow, fund age, and tme-style nteracton dummes (not reported). Table 2 contans the results of regressons for both dollar and percentage flows for each ndustry segment. Overall, the results n Table 2 provde mxed support for our hypothess. In the penson fund segment, both alpha and trackng error have the predcted relaton wth flows. Specfcally, the sgnfcant coeffcents on Jensen s alpha ndcate that penson sponsors reward 1% hgher alpha performance wth an addtonal $12.7 mllon n net dollar flow, or 2.3% addtonal net asset growth. In addton, the coeffcents on trackng error are negatve and sgnfcant n both the dollar and percentage flow regressons. The sgns and sgnfcance of these coeffcents are consstent wth a sophstcated penson fund clentele. We would not expect trackng error to be mportant to mutual fund nvestors, whch s consstent wth what we fnd. Contrary to our predctons, lagged raw return s sgnfcantly related to penson fund manager flow, and Jensen s alpha s sgnfcantly related to mutual fund manager flow. These results ndcate that both unadjusted and rsk-adjusted returns are related to manager flow n both segments. Whle ths appears nconsstent wth our hypothess, ths test may be too smplstc to draw conclusons. For example, the sgnfcance of raw returns for penson managers may be due to the hgh correlaton between lagged return and lagged return n excess of a market benchmark. Smlarly, the mportance of Jensen s alpha to mutual fund nvestors may be due to a