The Behavior of Investor Flows in Corporate Bond Mutual Funds

Transcription

1 The Behavior of Invesor Flows in Corporae Bond Muual Funds Yong Chen Texas A&M Universiy Nan Qin Virginia Tech This draf: March 15, 2014 Absrac This paper comprehensively examines invesor flows in corporae bond muual funds. Despie exensive sudies in equiy funds, lile is known abou invesor flows in bond funds which, wih several disinc feaures, can offer new insighs. Using a large sample of corporae bond funds, we firs documen ha flows are sensiive o boh fund performance and macro condiions. Then, we show ha flows predic fund performance, bu his predicabiliy need no be relaed o momenum or price pressure as argued in prior research. Finally, we examine he predicabiliy of idiosyncraic flows, and find no evidence ha fund invesors use finer-han-public informaion. * We are graeful o Charles Cao, Sephen Dimmock, Wayne Ferson, Fangjian Fu, Pengjie Gao, Shane Johnson, Gergana Josova, Jing-Zhi Huang, Greg Kadlec, Hwagyun Kim, Min Kim, Raman Kumar, Bing Liang, Roger Loh, Arvind Mahajan, Marin Rohleder, Marco Rossi, Zheng Sun, Kelsey Wei, Russ Wermers, Tong Yao, Lu Zheng, and seminar/session paricipans a Nanyang Technological Universiy, Shanghai Universiy of Finance and Economics, Singapore Managemen Universiy, Virginia Tech, and he Midwes Finance Associaion meeings for heir helpful commens. We hank Gergana Josova for providing some of he daa used in he paper. Yong Chen acknowledges financial suppor from he Republic Bank Research Fellowship a Texas A&M Universiy. A pilo version of his paper was previously circulaed under he ile How Smar is he Smar Money? Evidence from Corporae Bond Muual Funds. We are solely responsible for any remaining errors. Mays Business School, Texas A&M Universiy, College Saion, TX 77843; ychen@mays.amu.edu. Pamplin College of Business, Virginia Tech, Blacksburg, VA 24061; nanqin@v.edu. Elecronic copy available a: hp://ssrn.com/absrac=

2 The Behavior of Invesor Flows in Corporae Bond Muual Funds This draf: March 15, 2014 Absrac This paper comprehensively examines invesor flows in corporae bond muual funds. Despie exensive sudies in equiy funds, lile is known abou invesor flows in bond funds which, wih several disinc feaures, can offer new insighs. Using a large sample of corporae bond funds, we firs documen ha flows are sensiive o boh fund performance and macro condiions. Then, we show ha flows predic fund performance, bu his predicabiliy need no be relaed o momenum or price pressure as argued in prior research. Finally, we examine he predicabiliy of idiosyncraic flows, and find no evidence ha fund invesors use finer-han-public informaion. JEL Classificaion: G10, G23 Keywords: Invesor flows, corporae bond funds, flow-performance relaion, predicabiliy of flows, idiosyncraic flows Elecronic copy available a: hp://ssrn.com/absrac=

3 1. Inroducion Over he pas wo decades, insiuional invesors have gradually become he predominan figure in financial markes in place of individual invesors. As a main ype of insiuional invesors, professional fund managers paricipae in financial markes on behalf of heir invesors, and fund performance ineviably impacs he welfare and choices of fund invesors. Moreover, decisions made by fund invesors in selecing and exiing funds also have profound implicaions for no only invesors bu also funds. Given hese issues, i is imporan o undersand he behavior of invesors in ineracing wih funds. There has been a large lieraure examining he deerminans and effecs of invesor flows o professionally managed funds. The exising sudies have focused on equiy muual funds (e.g., Ippolio, 1992; Gruber, 1996; Chevalier and Ellison, 1997; Sirri and Tufano, 1998; Zheng, 1999, among many ohers), 1 hedge funds (e.g., Brown, Goezmann, and Park, 2001; Agarwal, Daniel, and Naik, 2004; Gemansky, Liang, Schwarz, and Wermers, 2011), and pension funds and reiremen plans (e.g., Del Guercio and Tkac, 2002; Sialm, Sarks, and Zhang, 2013; Pool, Sialm, and Sefanescu, 2013). However, lile is known abou he behavior of invesor flows in bond funds. Bond funds, as an imporan secor of muual funds, experienced fas growh over he pas 20 years. Recenly, he oal ne asses of US bond funds exceeds $3.4 rillion, which is more han half of he size of equiy funds and larger han he size of hedge funds. 2 During he A parial lis of he relaed sudies in equiy muual funds includes Ippolio (1992), Chevalier and Ellison (1997), Sirri and Tufano (1998), Huang, Wei, and Yan (2007, 2012), and Kim (2011) on he flow-performance relaion; Gruber (1996), Zheng (1999), Wermers (2003), Sapp and Tiwari (2004), Keswani and Solin (2008), and Lou (2012) on he predicabiliy of invesor flows; Brown, Harlow, and Sarks (1996), Chevalier and Ellison (1997), Koski and Poniff (1999), Huang, Sialm, and Zhang (2011), and Schwarz (2012) on fund managers' risk-shifing pracice; and Warher (1995), Edelen and Warner (2001), Coval and Safford (2007), Zhang (2011), and Lou (2012) on he impac of flows on securiy prices. 2 The daa source is he 2013 Invesmen Company Insiue (ICI) fac book. Among bond funds, he oal ne asses of US corporae bond (including high-yield bond) funds have grown from abou $45 billion in 1990 o over $783 billion as of 2012, suggesing an average growh rae of abou 13.9% per year. Over he same period, he whole US muual fund indusry experienced an average growh rae of 12.1% per year. 1

4 2009 financial crisis, many invesors shifed heir invesmens from equiy funds o bond funds, which refleced invesors percepion abou marke condiions. Despie he apparen imporance of bond funds, here is only sparse academic research abou he ineracion beween invesor flows and bond fund performance. 3 Specifically, he following quesions have largely been unaddressed: wha facors affec invesors decisions o move capial ino and ou of bond funds? Can invesor flows predic fuure fund performance, i.e., he smar money effec (Gruber, 1996; Zheng, 1999)? If here exiss predicabiliy of flows, does i reflec invesors use of public informaion or superior informaion? This paper provides he firs aemp o address all hese issues o beer undersand he invesor behavior hrough bond funds. In his paper, we focus our invesigaion on corporae bond funds. Corporae bond funds, wih several disinc feaures, offer an advanageous seing o sudy invesor flows. Firs, hough he facors explaining sock reurns are sill unclear, corporae bond reurns are beer explained by macroeconomic facors such as ineres rae and defaul spread. 4 This makes i easier o idenify facors affecing invesor flows. Second, prior research in equiy muual funds has found mixed resuls abou how price momenum affecs he inference abou he predicabiliy of invesor flows. 5 Sapp and Tiwari (2004) find ha price momenum can explain he predicabiliy of fund flows, while Keswani and Solin (2008) documens he smar money effec even afer conrolling for momenum. Alhough momenum is a robus feaure of socks and oher asse classes, i is much weaker in corporae bonds (e.g., Gebhard, Hvidkjaer, and Swaminahan, 2005; 3 Zhao (2005) sudies he deerminans of fund flows for reail bond funds. Comer and Rodriguez (2008) find ha bond fund flows are sensiive o pas fund performance. 4 For example, i remains conroversial abou how o inerpre sock-characerisics-based facors (fundamenal risk or mispricing) such as hose in he Fama-French (1993) hree-facor model. Alhough facors like defaul spread are also measured by reurn difference beween differen ypes of bonds, he underlying reasons are less ambiguous. 5 Price momenum refers o he phenomenon ha socks performing well recenly coninue o perform well in he nex hree o welve monhs (Jegadeesh and Timan, 1993). Momenum has also been documened in inernaional equiy markes and for non-equiy asse classes including governmen bonds, currencies, commodiy fuures (e.g., Rouwenhors, 1998; Asness, Moskowiz, and Pedersen, 2013). 2

5 Guierrez, Maxwell, and Xu, 2009; Josova, Nikolova, Philipov, and Sahel, 2013). 6 Therefore, one can es he predicabiliy of flows in corporae bond funds wihou much inervenion of momenum. Finally, similar o equiy funds, he vas majoriy of corporae bond funds are acively managed. Hence, fund invesors should value superior fund performance and make invesmen decisions based on heir percepion abou fund performance. All hese feaures sugges ha corporae bond funds offer a new and useful seing o sudy he behavior of muual fund invesors. Using a sample of 1,446 US corporae bond funds over , we provide new insighs abou he deerminans and predicabiliy of invesor flows. Firs, we show ha invesor flows in corporae bond funds chase recen fund performance, which is similar o prior resuls for equiy funds (e.g., Chevalier and Ellison, 1997; Sirri and Tufano, 1998). However, differen from he finding of a convex flow-performance relaion in equiy funds, he flow-performance relaion is no significanly convex for corporae bond funds; ha is, bond fund invesors reac as sensiively o poor performance as o good performance. Furher, here exiss heerogeneiy in he flow-performance relaionship across differen ypes of bond funds. For example, flows o high-qualiy bond funds are more sensiive o poor performance han flows o high-yield bond funds. In addiion, we find ha fund flows are also affeced by recen macro condiions such as T-bill rae and defaul spread. Nex, we find significan predicabiliy of invesor flows for fuure fund performance in corporae bond funds. Funds experiencing ne money inflows ouperform hose wih ne ouflows 6 Using monh-end corporae bond price daa, Gebhard, Hvidkjaer, and Swaminahan (2005) find ha invesmengrade corporae bonds do no exhibi reurn momenum. Guierrez, Maxwell, and Xu (2009) confirm he absence of reurn momenum in boh invesmen-grade and high-yield corporae bonds. Recenly, Josova e al. (2013), using ransacion and dealer-quoe daa, show evidence of momenum ha only exiss in high-yield bonds, bu no in invesmen-grade bonds. Kim, Mahajan, and Pekevich (2012) find ha momenum profis in corporae bonds exis only when credi shocks are negaive. 3

6 subsequenly. For example, he flow-weighed porfolio of funds wih ne inflows ouperforms he porfolio of funds wih ne ouflows by abou 0.16% per monh (or 1.92% per year, -saisic = 3.40) afer adjusing for risk exposures. The difference in performance is mainly driven by underperformance of funds experiencing ne ouflows. The predicabiliy of flows is presen in boh high-qualiy bond funds and high-yield bond funds even in he absence of reurn momenum. However, i appears mosly in reail funds insead of insiuional funds. We furher show ha he predicabiliy is neiher shor-lived nor relaed o fund size, which does no suppor a emporary price-pressure explanaion. More imporanly, he predicabiliy is largely reduced once we conrol for recen fund performance. One innovaion of our empirical analysis is ha we examine he idiosyncraic componen of fund flows ha is unrelaed o recen fund performance or macro condiions. If invesors use superior informaion abou muual funds above and beyond public informaion, we would expec idiosyncraic flows o be posiively associaed wih fuure fund performance. On he oher hand, if invesors mainly use public informaion, idiosyncraic flows should be unrelaed o fuure fund performance. We show ha idiosyncraic flows canno predicae fuure fund performance. Therefore, his resul suggess ha fund invesors make invesmen decisions primarily using public informaion raher han privae informaion. This paper conribues o he growing lieraure of invesor behavior in delegaed porfolio managemen in several ways. Firs, our paper provides he firs comprehensive examinaion of invesor flows for bond muual funds ha, wih unique feaures, offer a useful seing o sudy invesor behavior. Second, differen from prior sudies, we examine how invesor flows respond o no only fund performance bu also macro condiions. Finally, we show ha he predicabiliy of flows need no be relaed o momenum or price pressure as argued in previous 4

7 research. Insead, our evidence from several new ess suggess ha he predicabiliy is caused by flows chasing performance combined wih fund performance persisence. The res of he paper proceeds as follows. Secion 2 describes he daa. In Secion 3, we examine he relaionship beween invesor flows and recen fund performance and macro condiions. In Secion 4, we presen he evidence of he predicabiliy of invesor flows and evaluae poenial explanaions. Finally, Secion 5 offers some concluding remarks. 2. The Daa In his secion, we firs describe and summarize our sample of corporae bond funds. Then, we discuss how invesor flows are compued based on fund reurns and oal ne asses. Finally, we describe he facor models used o measure risk-adjused performance for corporae bond funds. 2.1 Corporae Bond Funds Our daa of corporae bond muual funds are from he Cener for Research in Securiy Prices (CRSP) survivor-bias free US muual fund daabase. The daabase conains informaion abou muual funds ne-of-expense reurns, oal ne asses (TNA) and various fund characerisics. Our sample covers all US corporae bond funds ha exis anyime beween 1991 and Differen from prior research on invesor flows ha mainly uses quarerly or annual daa, our analyses employ monhly daa of fund reurns and TNAs o obain more powerful es resuls. Keswani and Solin (2008) emphasize he advanages, such as high es power, of using monhly daa as opposed o lower-frequency daa in sudying fund flows. Our sample sars in 5

8 1991 when monhly informaion firs became available in he CRSP muual fund daabase. 7 Our daa covers boh live and defunc funds over he sample period. We idenify corporae bond funds by heir objecive codes. 8 We exclude index funds from our sample. We remove fund records wih TNA less han $10 million and age less han hree years o miigae daa biases, such as incubaion bias (Evens, 2010), associaed wih very small or young funds. 9 Finally, we exclude funds holding more han 30% governmen bonds and equiies combined because of heir differen risk exposures. Afer hese screenings, our sample includes a oal of 1,446 corporae bond funds a he share-class level and 93,676 fund-monh observaions. The sample covers 904 high-qualiy bond funds ha mainly hold invesmen-grade corporae bonds and 542 high-yield bond funds ha hold bonds wih a credi-raing lower han invesmen grade. Our daa is a he share class level raher han a he fund level. Ofen a fund can offer several differen share classes held by differen groups of invesors, even hough he underlying porfolio is he same for hese share classes. Nanda, Wang and Zheng (2009) examine he effecs of he inroducion of muliple share classes in he muual fund indusry. While i is appropriae o sudy performance a he fund level, i is reasonable o examine he flow-performance relaion a he share-class level because some share classes are designed for reail invesors while ohers for insiuional invesors. Hence, an invesigaion a he share-class level can beer explore he heerogeneiy in he flow-performance relaion beween reail invesors and insiuional 7 In heir sudy of equiy funds, Keswani and Solin (2008) aribue he fac ha Sapp and Tiwari (2004) do no find he smar money effec afer conrolling for momenum o he use of pre-1991 quarerly daa. 8 For he sample of corporae bond funds, we selec muual funds wih he Wiesenberger fund ype code (wbrger_obj) CHY or CBD in 1991, he sraegic insigh objecive code (si_obj_cd) CHY, CHQ, CGN, CIM, CMQ or CSM during , or he Lipper objecive code (lipper_obj) HY, A, BBB, IID, SID or SII during Furher, we caegorize funds wih wbrger_obj=chy, si_obj_cd=chy or lipper_obj=hy as high-yield bond funds, and hus he oher funds are labeled as high-qualiy bond funds. 9 Our resuls are robus o using oher cuoff crieria such as requiring fund size o exceed $5 million and fund age o be a leas one year. 6

9 invesors. Our sample includes 733 reail funds whose shares are mainly held by individual invesors and 491 insiuional funds whose cliens are primarily insiuional invesors. 10 In Panels A and B of Table 1, we repor summary saisics for our sample of corporae bond funds. In he sample, fund size is skewed by large funds, as he average TNA is $384 million while he median TNA is only $105 million. Fund urnover is measured by he minimum of aggregaed sales or aggregaed purchases of securiies during a year divided by he fund s average TNA in he previous 12 monhs. The average urnover raio is 139% per year for he whole sample. High-yield bond funds, on average, have lower urnover han high-qualiy bond funds, which is consisen wih he noion ha high-yield bonds are ofen less liquid han invesmen-grade bonds. Expense raio is he raio of he fund s operaing expenses (including 12b-1 fees) over oal invesmen, and he average expense raio is abou 1.4% per year in our sample. The average fund age is abou 10 years wih he median age of abou eigh years. The mean reurn on an equal-weighed porfolio of all sample funds is 0.60% per monh (or, 7.2% annually) over he sample period. Meanwhile, he average reurn for high-qualiy bond funds is 0.52% per monh, while he average reurn for high-yield bond funds is 0.65% per monh. In addiion, reurns of high-yield bond funds exhibi a larger serial correlaion han reurns of highqualiy bond funds. 2.2 Invesor Flows In muual funds, flows reflec he invesmen decisions of fund invesors. Following he lieraure (e.g., Chevalier and Ellison, 1997; Sirri and Tufano, 1998), we compue invesor flows 10 Based on informaion from he CRSP daabase, 222 funds in our sample canno be idenified as eiher reail or insiuional funds. 7

10 for a fund in a given period as he percenage change in fund TNA during he period minus he change in TNA caused by fund reurn realized in he same period. As discussed above, we examine invesor flows a a monhly frequency. For each fund in each monh, is ne flow raio is calculaed as follows. TNAi, TNAi, 1(1 Ri, ) Flow i,, (1) TNA i, 1 where TNAi, is he oal ne asse value of fund i a he end of monh, and Ri, is he reurn on fund i in monh. One issue o be considered is fund mergers. A merger adds new money o he acquiring fund, bu such money inflows do no reflec invesors invesmen decision. To miigae he poenial effec, we delee merger funds observaions for he following monh afer a merger happens. This reamen does no maerially change our sample, because only a iny fracion of fund-monh observaions (355 ou of 93,676 observaions, or 0.4% of he observaions) are removed. Similar o Huang, Wei, and Yan (2007), we remove exreme flow raios (i.e., greaer han 50% or smaller han -50%) ha could be problemaic due o misrepored fund mergers and splis. As shown in Panel A of Table 1, he average (median) flow raio is 3.26% (1.76%) per monh over he sample period, wih high-qualiy and high-yield bond funds experiencing a similar level of average flow. The average flow is greaer han he median, suggesing ha some funds experienced unusually higher money inflows han mos oher funds. 8

11 2.3 Risk-Adjused Fund Performance In his paper, we measure he risk-adjused performance for corporae bond funds based on wo mulifacor models proposed in he lieraure (e.g., Blake, Elon, and Gruber, 1993; Elon, Gruber, and Blake, 1995). 11 The firs measure is he inercep from a ime-series regression of he following wo-facor model: R R G ( HY HQ ) e, (2) i, f G HYHQ where Ri, is he reurn on fund i in monh, Rf is he risk-free rae proxied by he one-monh T- bill rae in monh, G is he reurn on a governmen bond index in excess of he risk-free rae, (HY HQ) is he spread beween he reurns on an invesmen-grade corporae bond index (HQ) and a high-yield corporae bond index (HY). The inercep, or alpha, reflecs invesmen reurns in excess of a fair compensaion for risk exposures. model: The second performance measure is obained from he following four-facor regression R R STK BOND DEF OPTION e, (3) i, f STK BOND DEF OPTION where STK is he excess reurn on he CRSP value-weighed sock index, BOND is he excess reurn on he Barclays aggregae bond index, DEF is a defaul spread beween a high-yield bond index and an inermediae governmen bond index, and OPTION reflecs he value of opion in bonds proxied by reurn spread beween he GNMA morgage-backed securiy index and he inermediae governmen bond index. All he bond index daa in hese facor models are obained from Barclays Capial. 11 Blake, Elon, and Gruber (1993, 1995) provide early evidence abou risk-adjused performance for bond funds. Recenly, here is a growing ineres in examining bond fund performance and iming abiliy using new empirical mehods and daa. See, e.g., Ferson, Henry, and Kisgen (2006), Chen, Ferson, and Peers (2010), Cici and Gibson (2012), Monea (2012), and Huang and Wang (2013). 9

12 Panel C of Table 1 repors summary saisics for hese facors. Over he sample period, governmen bonds realized an average excess reurn of 0.29% per monh, while high-yield bonds provided a higher average reurn han high-qualiy bonds by abou 0.20% per monh. For he same period, he overall sock marke shows an average excess reurn of 0.57% per monh. The defaul spread averages of 0.29% per monh, while he mean spread beween he GNMA and governmen bond indices is 0.04% per monh. Table 2 repors he resuls of fund performance a he aggregae level based on equalweighed porfolios of all he sample funds as well as he wo subsamples of high-qualiy and high-yield bond funds. Consisen wih prior research (e.g., Blake, Elon, and Gruber, 1993; Chen, Ferson, and Peers, 2010; Cici and Gibson, 2012), we find ha afer fees and expenses, corporae bond funds on average underperform he benchmarks. 12 For example, using he fourfacor model, we find an alpha of -0.04% per monh (or, abou -0.5% per year) for he overall porfolio of funds. In general, he regression coefficiens from he facors are inuiive. For example, he high-yield bond fund porfolio shows higher exposures o boh he sock facor and he defaul spread facor han he high-qualiy bond fund porfolio. Overall, he facors explain bond fund reurns well, and he R-squared from he four-facor model is paricularly high exceeding 90% in all he regressions. For breviy, we mainly repor resuls obained from he four-facor model in laer secions, hough he wo-facor model yields consisen inference. For robusness, we also consider addiional facor models. We employ a condiional facor model in he spiri of Ferson and Schad (1996) by including ineracion erms beween he facors and lagged values of public informaion ha includes he hree-monh T-bill rae, he 12 A he individual fund level, however, several sudies have shown posiive risk-adjused performance and iming abiliy in bond funds, such as Chen, Ferson, and Peers (2010), Cici and Gibson (2012), Monea (2012), and Huang and Wang (2013). 10

13 yield spread beween he 10-year governmen bonds and he hree-monh T-bill, he yield spread beween Moody s BAA- and AAA-raed corporae bonds, and he dividend yield of he S&P 500 index. As anoher alernaive model, we add a liquidiy facor o he facor model in which we follow Gaev and Srahan (2006) o use he spread beween 3-monh nonfinancial corporae commercial paper rae and 3-monh T-bill rae as a measure of liquidiy in corporae bond markes. Overall, our inference is robus o hese addiional facor models. The es deails are no repored o conserve space bu are available upon reques. 3. The Deerminans of Invesor Flows In his secion, we invesigae he deerminans of invesor flows o corporae bond funds. Prior sudies on equiy funds (e.g., Chevalier and Ellison, 1997; Sirri and Tufano, 1998) documen a convex flow-performance relaion ha suggess ha fund invesors are more sensiive o good performance bu less sensiive o bad performance. As shown by Brown, Harlow, and Sarks (1996), Chevalier and Ellison (1997), Koski and Poniff (1999), and Huang, Sialm, and Zhang (2011), his convex flow-performance relaion has imporan implicaions for fund managers risk-shifing behavior. 13 However, lile is known abou he flow-performance relaion in bond funds. Here, we firs examine how invesors reac o fund performance for corporae bond funds and hen discuss is similariies and differences compared wih he previously documened paern for equiy funds. In addiion, given he finding ha macro 13 In he muual fund lieraure, risk-shifing refers o he pracice ha a manager increases (decreases) his porfolio risk in he laer par of a year afer his performance is behind (ahead of) peer funds in he firs par of he year. Tess of risk-shifing are usually moivaed by he convex flow-performance relaion ha induces fund managers o game porfolio risk. Using asse holdings informaion of equiy funds, Huang, Sialm, and Zhang (2011) show ha riskshifing reflecs ill-moivaed rades and is cosly for fund invesors. 11

14 variables explain bond fund reurns well, we es wheher and how invesor flows are sensiive o recen macro condiions. 3.1 The Flow-Performance Relaion We examine he relaion beween invesor flows and recen fund performance by performing Fama-MacBeh regressions. Specifically, each monh we run a cross-secional regression of fund flows on lagged values of fund reurn, reurn volailiy, and several fund characerisics. Then, for each independen variable, we repor he average coefficien across all he monhs in he sample period. The -saisics are based on Newey-Wes robus sandard errors. Table 3 repors he findings. The regression coefficien on lagged fund reurns suggess ha invesor flows chase pas fund performance, which is similar o prior findings for equiy funds. 14 For example, for he overall sample, a one-percen increase in fund reurn in he pas year is associaed wih a 0.41% (-saisic = 10.10) increase in fund flows in he curren monh. In addiion, here is some evidence ha fund flows are negaively associaed wih fund volailiy, especially wih he case of high-yield bond funds. Older funds have lower flow raio, suggesing ha he growh in fund size slows down as a fund maures. Meanwhile, ne inflows are posiively associaed wih fund size for high-qualiy bond funds, bu negaively associaed wih fund size for high-yield bond funds. This is perhaps because high-qualiy bond funds on average have smaller size han high-yield bond funds as shown in Secion 2, so i is easier for hem o have a higher flow raio as percenage change in size. In addiion, invesor flows are negaively associaed wih expense raio, indicaing ha invesors prefer funds wih low oal expenses. 14 For robusness, we replace lagged fund reurns in he es wih lagged alphas esimaed from he four-facor model, and all he inference is unchanged. 12

15 We evaluae possible non-lineariy in he flow-performance relaion using a piecewise Fama-MacBeh regression. 15 Following Sirri and Tufano (1998), lagged fund reurns are broken down ino quiniles in each monh. This way, we can examine he flow sensiiviy o fund reurns in differen quiniles. Again, we perform he es for all funds, high-qualiy bond funds, and highyield bond funds, separaely. Ineresingly, differen from prior findings for equiy funds, here is no significan convexiy beween invesor flows and pas fund performance for he overall sample of corporae bond funds. For he overall sample, he average regression coefficien on he bes quinile is 0.19 (-saisic = 8.66), he coefficien on he wors quinile is 0.16 (-saisic = 5.34), and he coefficien on he medium quinile is 0.22 (-saisic = 6.69). A es for saisical significance of he difference beween he coefficiens for he bes and wors quiniles yields a - saisic of The lack of significan nonlineariy in he flow-performance relaion can also be seen in Figure 1. Thus, invesor flows reac o poor fund performance in a similar way o good performance in corporae bond funds. We also explore possible heerogeneiy in he flow-performance relaion across differen ypes of funds. 16 For high-qualiy bond funds, he flow-performance relaion appears o be slighly concave, bu he concaviy is no saisically significan. For high-yield bond funds, fund flows are somewha more sensiive o bes performance han o wors performance. Given ha he convex flow-performance relaion is used as a heoreical moivaion o invesigae he risk-shifing behavior in equiy funds (e.g., Brown, Harlow, and Sarks, 1996, Chevalier and 15 In a sudy of hedge funds, Gemansky, Liang, Schwarz, and Wermers (2011) find a convex flow-performance relaion for funds wihou share resricions, bu a concave relaion for funds wih share resricions. For pension funds, Del Guercio and Tkac (2002) show ha pension fund sponsors punish poorly performing managers by wihdrawing capial, bu do no flock disproporionaely o pas winner managers. Kim (2011) finds ha he flowperformance relaion in equiy funds has become less convex during he 2000s. Recenly, Sialm, Sarks, and Zhang (2013) find ha flows reac mos srongly o exreme performance quiniles for defined conribuion (DC) pension funds, and he flow-performance relaion is only slighly convex for non-dc pension funds. 16 Spiegel and Zhang (2013) sudy he implicaion of heerogeneiy for he shape of flow-performance relaionship in muual funds. 13

16 Ellison, 1997; Huang, Sialm, and Zhang, 2011), i would be ineresing o examine if bond funds also engage in risk-shifing in absence of a convex flow-performance relaion. We leave his opic for fuure research. 3.2 Macro Condiions and Invesor Flows As shown in Secion 2, bond fund reurns can be well explained by a facor model conaining bond-marke relaed macro variables. Moivaed by his observaion, we nex examine wheher invesor flows are also sensiive o recen macroeconomic condiions. To his end, we conduc a pooled ime-series and cross-secional regression. The dependen variable is monhly fund flows, and he independen variables are one-monh lagged values of boh macro-level and fund-level variables. The sandard errors are clusered a he fund level, and year dummies are also included in he regressions. Table 4 presens he evidence. For he overall sample, corporae bond fund flows are sensiive o recen bond marke reurns as capured by he aggregae bond index. Overall, a onepercen reurn on he bond index in he precious monh is associaed wih abou a 15% (-saisic = 6.88) ne money inflow ino an average bond fund. Meanwhile, invesor flows show a posiive reacion o he hree-monh T-bill rae and a negaive reacion o he reurn spread beween morgage-backed securiies and governmen bond index. A he aggregae level, here is no significan relaion beween defaul spread and fund flows. The able also repors he evidence for high-qualiy and high-yield bond funds, separaely. Flows o high-qualiy bond funds reac negaively o sock marke reurns, reflecing a fligh o 14

17 safey effec. Also, invesor flows are posiively relaed o defaul spread, suggesing ha more money flows ino relaively safe high-qualiy bond funds when defaul risk is higher. The picure is somewha differen for high-yield bond funds. Flows o such funds show a posiive sensiiviy o sock markes, reflecing a similariy beween high-yield bonds and socks. Also, invesor flows are negaively associaed wih defaul spread for high-yield funds, which suggess ha when defaul risk increases, high-yield funds experience less inflow and more ouflow. The differen direcions in which high-qualiy and high-yield bond funds reac o defaul spread explains why he regression coefficien on defaul spread is insignifican a he aggregae level. Ineresingly, flows o high-yield bond funds have a posiive reacion o he recen VIX index, indicaing ha high-yield bond funds experience more inflows when sock markes are volaile. This able also includes fund-specific variables such as find size, age, expense raio, reurn volailiy, and performance. Since fund performance is sensiive o marke condiions (e.g., up versus down markes) and hus i is no appropriae o compare i across differen periods, we use fund performance rank in he monh in he regressions, insead. In general, he coefficiens on hese fund-specific variables are consisen wih hose repored in Table 3. Taken ogeher, he resuls in his secion show ha invesor flows in corporae bond funds are sensiive o no only recen fund performance bu also macro condiions. 17 Meanwhile, differen from previous findings for equiy funds, here is no significan convexiy in he flowperformance relaion for he overall sample of corporae bond funds. We also find heerogeneiy in he behavior of invesor flows beween high-qualiy and high-yield bond funds. 17 Ferson and Warher (1996) find ha flows o equiy funds can be parially prediced by macro variables such as T- bill rae and dividend yield. 15

18 4. Can Invesor Flows Predic Fund Performance? This secion examines wheher invesor flows can predic fuure fund performance. Gruber (1996) and Zheng (1999) provide he firs evidence of such predicabiliy (also dubbed he smar money effec) among equiy funds, in ha funds experiencing ne money inflows subsequenly ouperform hose experiencing ne ouflows. The evidence of his predicabiliy is robus in equiy funds, bu he inerpreaion has been debaed. On he one hand, he predicabiliy could reflec fund invesors using superior informaion o selec funds. On he oher hand, he predicabiliy may be a manifesaion of some aribues of eiher he funds or heir underlying asses. For example, Zheng (1999, p.921) conjecures ha reurn momenum may explain he predicabiliy, and Sapp and Tiwari (2004) formally show ha he predicabiliy is largely reduced once conrolling for reurn momenum in measuring fund performance. 18 However, using higher-frequency fund daa, Keswani and Solin (2008) find evidence of he predicabiliy even when momenum is conrolled for. All hese exising papers examine equiy funds. As discussed above, here is lile evidence of price momenum in corporae bonds (especially high-qualiy bonds), and hus corporae bond funds provide a unique seing o examine he predicabiliy of fund flows. In his secion, we firs presen evidence of he predicabiliy of invesor flows in corporae bond funds. Then, we check he robusness of he resuls. Finally and more imporanly, we invesigae alernaive explanaions for he predicabiliy of flows. 18 Wermers (2003) shows ha equiy fund invesors end o inves heavily in pas winner funds, and hen winner funds end o inves he new money heavily in momenum socks and push up he prices of hese socks. 16

19 4.1 Predicabiliy of Invesor Flows As a firs es for he predicabiliy of invesor flows, we follow Zheng (1999) o examine he payoffs of rading sraegies involving muual funds ha experience differen paerns of invesor flows. Specifically, we consruc he following four porfolios of muual funds based on he signs of heir ne flows in he previous monh. Porfolio 1: Equal-weighed porfolio of all funds wih posiive ne flows. Porfolio 2: Equal-weighed porfolio of all funds wih negaive ne flows. Porfolio 3: Flow-weighed porfolio of all funds wih posiive ne flows. Porfolio 4: Flow-weighed porfolio of all funds wih negaive ne flows. A fund has posiive ne flow when is aggregae inflow exceeds is aggregae ouflow. For ease of illusraion, we refer o Porfolios 1 and 3 as posiive-flow porfolios, while Porfolios 2 and 4 as negaive-flow porfolios. These porfolios are rebalanced each monh, and his process generaes ime series of porfolio reurns. We infer he predicabiliy of invesor flows by examining he risk-adjused reurns of hese porfolios as well as he reurn spreads beween he porfolios. The risk-adjused performance is esimaed by ime-series regressions based on he wo-facor and four-facor models. Table 5 presens evidence ha srongly suggess he predicabiliy of invesor flows in corporae bond funds. Tha is, he posiive-flow porfolios significanly ouperform he negaiveflow porfolios on a risk-adjused basis. For example, he reurn spread beween Porfolios 3 and 4 shows an alpha of 0.16% per monh (abou 1.92% per year, -saisic = 3.40) based on he four-facor model. Noe ha alpha of he posiive-flow porfolios is no significanly posiive, while he negaive-flow porfolios significanly underperform. Hence, he spread of alpha 17

20 beween he posiive-flow and negaive-flow porfolios is mainly from he under-performance of negaive-flow funds, and such alpha canno be fully realized in pracice because muual fund shares are no shorable. Noneheless, invesing in funds wih posiive inflows would sill yield boh saisically and economically higher reurns han invesing in an average fund (he alpha spread beween posiive-flow funds and an average fund is 0.07% per monh wih a -saisic of 2.52). In unabulaed ess, we examine wheher he difference in fund expenses could explain he difference in afer-expense performance beween he posiive-flow and negaive-flow porfolios. The raionale is ha if invesor direc money flows ino low-expense funds and ou of high-expense funds, we may observe predicabiliy of invesor flows (i.e., posiive associaion beween money inflows and afer-expense fund performance) even if all funds have he same preexpense performance. To examine his possibiliy, we add fund expenses back o fund reurns and repea he ess using pre-expense reurns. In hese ess, we sill find significan evidence of he predicabiliy of invesor flows. Thus, he dispersion in fund expenses does no explain he documened predicabiliy. In sum, for he firs ime in he lieraure, we find significan evidence ha invesor flows can predic fuure performance in bond funds, which is similar o prior findings for equiy funds (e.g., Gruber 1996; Zheng, 1999), bu differen from ha for pension funds (e.g., Sialm, Sarks, and Zhang, 2013). In he remainder of his secion, we check robusness of he predicabiliy of flows in bond funds and, more imporanly, we evaluae alernaive explanaions for such predicabiliy. 18

21 4.2 Predicabiliy of Invesor Flows in Differen Types of Funds Here, we explore he effec of heerogeneiy in fund ypes on he predicabiliy of invesor flows. Firs, we separae high-qualiy bond funds and high-yield bond funds ino wo subsamples o examine wheher invesor flows show differen paerns in predicing fuure fund performance. As shown in Panels A and B of Table 6, he predicabiliy of invesor flows exis in boh highqualiy and high-yield bond funds in ha he posiive-flow porfolios significanly ouperform he negaive-flow porfolios. For example, he posiive-flow porfolio of high-qualiy bond funds ouperforms he negaive-flow porfolio of high-qualiy funds by 0.15% per monh (abou 1.8% per year, -saisic = 2.30) based on he four-facor model. The difference in risk-adjused reurns for he wo porfolios among high-yield bond funds is 0.09% per monh (-saisic = 2.60). Thus, while he predicabiliy of flows appears in boh ypes of funds, i is sronger among high-qualiy bond funds han among high-yield bond funds. As discussed above, several sudies (e.g., Gebhard, Hvidkjaer, and Swaminahan, 2005; Guierrez, Maxwell, and Xu, 2009; Josova e al., 2013) have found no evidence of reurn momenum in high-qualiy bonds. Hence, he predicabiliy of flows in high-qualiy bond funds clearly suggess ha he predicabiliy need no be relaed o momenum. However, Josova e al. (2013) find momenum exising in high-yield bonds. Similar o Sapp and Tiwari (2004), we include he reurns o a bond momenum sraegy consruced in Josova e al. (2013) when measuring fund performance, and we sill find economically and saisically significan predicabiliy of flows in corporae bond funds including high-yield bond funds. 19 This confirms ha momenum canno be he main source of he predicabiliy of flows. Deails of he es resuls are available upon reques. 19 We hank Gergana Josova for providing us wih he daa of reurns o he bond momenum sraegy. 19

22 Nex, we examine he predicabiliy of flows among reail funds and insiuional funds, separaely. Panels C and D of Table 6 shows ha he predicabiliy of invesor flows is significan in reail funds, bu no in insiuional funds. For example, among reail funds, he posiive-flow porfolio ouperform he negaive-flow porfolio by 0.21% per monh (-saisic = 3.62) on a ne-of-expense risk-adjused basis. However, he performance difference in he wo porfolios of insiuional funds is only 0.06% per monh and saisically insignifican. In addiion, we find ha on aggregae reail funds underperform insiuional funds. For example, he four-facor alpha is -0.09% for he value-weighed porfolio of reail funds, while he alpha is -0.03% for he porfolio of insiuional funds. This finding indicaes ha insiuional funds have low expenses and urnovers and hus relaively high ne reurns, and i is also consisen wih he noion ha reailed invesors are generally less sophisicaed han insiuional invesors (e.g. Barber and Odean, 2000). However, he resuls cas some doub abou wheher he predicabiliy of flows really reflecs superior informaion used by invesors, as he predicabiliy exiss mainly among less sophisicaed reail invesors. 4.3 Fund Size and he Predicabiliy of Invesor Flows We now es for possible relaion beween fund size and he predicabiliy of flows. If he predicabiliy exiss primarily among large funds, i could suppor a price-pressure based explanaion because rades of large funds have greaer poenial o impac asse prices han small funds and such price impac will be refleced in fuure (especially shor-erm) fund reurns. 20 Zheng (1999) finds ha for US equiy funds, he predicabiliy of flows is more pronounced wih 20 Lou (2012) argues ha flow-induced rading pressure explains he smar money effec. His argumen is ha fund rades induced by invesor flows generae a price pressure ha in urn causes reurn momenum, performance persisence, and he smar money effec. The effec of fund flows on sock prices have also been sudied by Warher (1995), Edelen and Warner (2001), and Coval and Safford (2007). 20

23 small funds han wih large funds. We invesigae he poenial paern for bond funds. In each monh, we divide bond funds ino 10 deciles by fund size. Then, across he deciles we compare alphas as he inercep from a regression of reurn spreads beween he posiive-flow and negaive-flow porfolios. Table 7 shows ha overall he predicabiliy of invesor flows appears somewha sronger among small funds, when we look a he full sample and he subsample of high-yield bond funds. For he full sample, he alpha spread beween he posiive-flow and negaive-flow porfolios is 0.23% per monh (-saisic = 4.48) for he funds of below-median size (i.e., size deciles 1 hrough 5), while he alpha spread is 0.17% per monh (-saisic = 3.54) for he funds of abovemedian size (i.e., size deciles 6 hrough 10). There is a similar paern for high-yield bond funds. However, he predicabiliy of flows is slighly more prominen among large funds for highqualiy bond funds. In addiion, a closer look a he 10 deciles reveals no monoonic relaion beween fund size and he predicabiliy. To furher invesigae he relaionship, we examine he predicabiliy of flows for a subsample of small-rade funds whose rades are less likely o cause a price pressure. The small-rade funds are defined as hose having lower-han-median R 2 in a regression of fund reurns on he porfolio comprising of he larges 10% of sample funds. Tha is, small-rade funds do no jus have small size, bu have differen rade paerns from large funds. These small-rade funds are unlikely o maerially move asse prices. If he predicabiliy of flows is enirely caused by price pressure, we would expec o find lile evidence of he predicabiliy of flows in his subsample. However, we find significan predicabiliy of flows among small-rade funds. The deails of es resuls are unabulaed o save space, bu are available upon reques. 21

24 To summarize, we find ha he relaion beween fund size and he predicabiliy of flows is mixed in corporae bond funds. Furher, here is predicabiliy of flows among funds whose rades are less likely o move asse prices. These resuls do no suppor a price-pressure based explanaion for he predicabiliy of flows. 4.4 Predicabiliy of Invesor Flows over Differen Holding Periods How long does he predicabiliy of flows las? The lengh is imporan for undersanding he naure of he predicabiliy. If i is shor-lived, he source of he predicabiliy is more likely o be emporary price changes. Oherwise, a long-lasing predicabiliy would reflec informaion use by fund invesors. We examine he duraion of he predicabiliy by looking a he performance of he flow-sored porfolios over various holding periods. Specifically, in each monh we form porfolios based on fund flows in he previous monh, and hese porfolios are held subsequenly for differen periods ranging from one o 36 monhs. This process yields ime series of porfolio reurns for differen holding periods, based on which we esimae alpha using he four-facor model. Whenever a fund sops operaing during a holding period, is reurns are included in calculaing he porfolio reurns unil is disappearance. Table 8 shows ha he predicabiliy of flows is no a shor-lived phenomenon. As explained above, we infer he predicabiliy by alpha spread of he flow-sored porfolios. For he overall sample, while he alpha spread decays in magniude over ime, i remains saisically significan for he holding periods ranging from one monh o 36 monhs. For example, he alpha spread is 0.16% per monh (-saisic = 3.40) for he one-monh holding period, while he spread becomes 0.08% per monh (-saisic = 3.29) for he 18-monh holding period, abou half of he size of ha for he one-monh period. 22

25 For high-qualiy bond funds, he predicabiliy exiss from a holding period of one monh up o a nine-monh holding period. Tha is, afer porfolio formaion, alpha spread beween he wo porfolios is boh economically and saisically significan unil nine monhs laer. Meanwhile, holding he posiive-flow porfolio yields posiive alpha, while holding he negaiveflow porfolio leads o negaive alpha. Take he nine-monh holding period as an example: is alpha spread is 0.1% per monh (-saisic = 3.29) ha would ranslae o abou 1.2% per year. We find a similar paern for high-yield bond funds. The spread of alpha beween he wo porfolios is saisically significan unil 18 monhs afer porfolio formaion. Thus, he duraion of he predicabiliy is longer in high-yield bond funds compared wih high-qualiy bond funds, while alpha spread is smaller in high-yield bond funds. For example, alpha spread for he 18- monh holding period is 0.04% per monh (-saisic = 2.38). In sum, we find ha he predicabiliy of invesor flows is no very shor-lived; insead, i lass as long as 36 monhs. There is a similar paern for boh high-qualiy bond funds and highyield bond funds. This finding suggess ha he predicabiliy of flows is more likely o be informaion driven raher han caused by emporary changes in asse prices. 4.5 Regression Analysis of he Predicabiliy of Invesor Flows To gain furher insigh abou he predicabiliy of flows, we perform Fama-MacBeh regressions of fund alpha on one-monh lagged ne inflow, wih conrols for fund characerisics. In each monh for each fund, we esimae is alpha as he difference beween he fund excess reurn and he producs of he fund s loadings on he four facors and he realizaions of hose facors in he monh. The fund s facor loadings are esimaed using fund reurns in he previous 23

26 36 monhs based on he four-facor model. Funds wih less han 36 monhs of observaions are excluded. We hen regress fund alpha cross-secionally on lagged flow, an ineracion erm beween fund flow and an ouflow dummy ha equals one if he fund experiences ne ouflows in he previous monh or zero oherwise. In some regression specificaions, we also conrol for he fund s average alpha in he previous year as well as lagged values of fund characerisics. Table 9 presens resuls from he Fama-MacBeh regressions. In he firs specificaion, we regress fund alpha on lagged ne flow wihou oher conrols. Consisen wih he resuls from flow-sored porfolios, lagged flow is significanly posiively associaed wih fuure fund alpha, which suggess he predicive power of flows for fund performance. In he second specificaion, we include he ineracion erm of invesor flow and he ouflow dummy. Ineresingly, he coefficien on he ineracion erm is significanly posiive (coefficien = 1.02; -saisic = 2.14), suggesing ha money ouflows have greaer impac on fund performance. This is consisen wih a fire sale inerpreaion when many invesors redeem share a he same ime, he fund is forced o liquidae asses and he liquidaions will push down asse prices and fund reurns. 21 However, he ineracion erm does no subdue he coefficien on lagged flow, and ha coefficien only drops slighly when he ineracion erm is included. Thus, he fire sale sory canno fully explain he predicabiliy of flows. In he hird and fourh specificaions, we add fund alpha in he prior year o he regression. The prominen finding is ha afer lagged alpha is added, he predicabiliy of flows is largely reduced. In he meanime, we find ha fund performance is persisen since lagged alpha significanly predics fund performance. Huij and Derwall (2008) and Guierrez, Maxwell, and 21 See Shleifer and Vishny (1992) for a general discussion on fire sales. For equiy muual funds, Coval and Safford (2007) and Zhang (2011) examine he effecs of fire sales on sock prices and fund performance riggered by excessive capial wihdrawal. Ellul, Joikashira, and Lundbad (2012) examine fire sales of downgraded corporae bonds held by insurance companies. 24

27 Xu (2009) find significan evidence of performance persisence in bond funds as well. Berk and Green (2004) build a model in which muual fund performance does no persis in equilibrium when fund invesors direc capial ino skilled funds and skilled funds face diseconomies of scale. As discussed above, he evidence of invesors chasing pas performance is pervasive. Moreover, Edelen, Evans, and Kadlec (2007) argue ha rading coss are a major reason for diseconomies of scale in equiy funds. In he seing of corporae bond funds, however, Guierrez, Maxwell, and Xu (2009) find no evidence of diseconomies of scale, which hey argue is because rading coss in bond markes ypically decrease wih rade size. Thus, corporae bond funds are subjec o diseconomies of scale o a less exen han equiy funds. Consisen wih his raionale, we do no find a significan relaion beween lagged fund size and fund performance, bu significan performance persisence in corporae bond funds. Given he resuls, an explanaion for he predicabiliy of flows emerges ha i is mainly driven by invesor flows chasing pas performance combined wih fund performance persisence. Tha is, money flows ino (ou of) pas winner (loser) funds, and hus he posiive (negaive)-flow porfolio conains pas winner (loser) funds. Because of performance persisence, he posiiveflow porfolio coninues o ouperform he negaive-flow porfolio. Consequenly, we observe he predicabiliy of flows. We nex conduc formal ess o evaluae his explanaion Predicabiliy of Invesor Flows Condiional on Recen Fund Performance We invesigae how recen fund performance affecs he inference abou he predicabiliy of flows. We divide he sample funds ino 10 deciles based on heir average reurns in he prior 22 Gruber (1996) and Zheng (1999) sugges a similar explanaion for equiy funds, bu hey do no es his explanaion as inensively as our sudy does. 25