The Behavior of Investor Flows in Corporate Bond Mutual Funds

Transcription

1 The Behavior of Invesor Flows in Corporae Bond Muual Funds Yong Chen Mays Business School, Texas A&M Universiy, College Saion, TX 77843, Nan Qin Luer School of Business, Chrisopher Newpor Universiy, Newpor News, VA 23606, Firs draf: Augus 1, 2011 This version: Sepember 28, 2015 Managemen Science, forhcoming * We are graeful o Lauren Cohen (he deparmen edior), an associae edior, and wo anonymous referees for consrucive commens and suggesions ha grealy improved he qualiy of he paper. We also hank Charles Cao, Zhi Da, Sephen Dimmock, Wayne Ferson, Fangjian Fu, Paul Gao, Shane Johnson, Gergana Josova, Jing-Zhi Huang, Greg Kadlec, Hwagyun Kim, Min Kim, Raman Kumar, Bing Liang, Roger Loh, Dong Lou, Arvind Mahajan, Marin Rohleder, Marco Rossi, Zheng Sun, Jay Wang, Kelsey Wei, Russ Wermers, Tong Yao, Lu Zheng, and seminar/conference paricipans a Nanyang Technological Universiy, Shanghai Universiy of Finance and Economics, Singapore Managemen Universiy, Virginia Tech, and he 2012 MFA meeing in New Orleans for heir helpful commens. We hank Gergana Josova for providing some of he daa used in he paper. An earlier version of he paper was circulaed under he ile How Smar is he Smar Money? Evidence from Corporae Bond Muual Funds. Yong Chen acknowledges financial suppor from he Republic Bank Research Fellowship a Texas A&M Universiy.

2 The Behavior of Invesor Flows in Corporae Bond Muual Funds This paper provides a comprehensive examinaion of money flows in corporae bond funds which, hough less researched, represen an imporan seing o sudy invesor behavior. Based on a large sample of corporae bond funds over , we firs show ha flows are sensiive o boh fund performance and macro condiion, bu unlike equiy funds, he flow-performance relaionship is no convex. Then, we find ha invesor flows can predic fund performance. More imporanly, he predicabiliy canno be explained by reurn momenum or price pressure bu is subsumed by performance persisence. Finally, an examinaion of idiosyncraic flows reveals lile evidence ha fund invesors use finer-han-public informaion. Key words: corporae bond funds, invesor flows, flow-performance relaion, predicabiliy of flows, idiosyncraic flows 1. Inroducion A prominen phenomenon in US financial markes is ha insiuional invesors gradually became he predominan figure in place of individual invesors over he pas wo decades. Professional fund managers, as a main ype of insiuional invesors, inves on behalf of heir invesors and hus fund performance impacs invesors welfare. Meanwhile, invesor decisions o selec and exi funds in urn affec fund operaion. Therefore, o beer undersand financial markes, i is imporan o undersand he ineracion beween invesors and funds. Indeed, here is a large and growing lieraure sudying fund flows. However, as previous research focuses on equiy muual funds, hedge funds, and pension funds, 1 invesor flows in corporae bond funds have received lile aenion. 1 A parial lis of he lieraure on fund flows includes Ippolio (1992), Warher (1995), Brown, Harlow, and Sarks (1996), Gruber (1996), Chevalier and Ellison (1997), Sirri and Tufano (1998), Zheng (1999), Edelen and Warner (2001), Wermers (2003), Sapp and Tiwari (2004), Coval and Safford (2007), Huang, Wei, and Yan (2007, 2012), Keswani and Solin (2008), Huang, Sialm, and Zhang (2011), Kim (2011), Zhang (2011), Lou (2012), Schwarz (2012), and Spiegel and Zhang (2013) on equiy muual funds; Brown, Goezmann, and Park (2001), Agarwal, Daniel, and Naik (2004), and Gemansky, Liang, Schwarz, and Wermers (2011) on hedge funds; Del Guercio and Tkac (2002), Sialm, Sarks, and Zhang (2015), and Pool, Sialm, and Sefanescu (2015) on pension funds and plans. 1

3 Corporae bond funds recenly experienced fas growh. According o he ICI fac book (2014), corporae bond funds (including invesmen-grade and high-yield bond funds) grew from managing abou $50 billion in 1990 o abou $1.9 rillion as of 2013, suggesing an average growh rae of over 16% per year. 2 Despie he apparen imporance, here is surprisingly lile research abou corporae bond fund flows and he following quesions are largely unaddressed: wha deermines invesor flows in corporae bond funds? Can invesor flows predic fuure fund performance (i.e., he smar money effec firs documened by Gruber (1996) and Zheng (1999))? If so, wha is he mechanism behind he predicabiliy of flows? In his paper, we provide a comprehensive examinaion of invesor flows in corporae bond funds. For a beer undersanding of invesor behavior, corporae bond funds provide a new and imporan seing. Corporae bond fund invesors are likely o be a differen clienele from equiy fund invesors, since corporae bonds have differen reurn and risk characerisics han socks. In addiion, prior sudies show ha reurn momenum and price pressure are relaed o he smar money effec in equiy funds (Sapp and Tiwari, 2004; Lou, 2012). However, Josova e al. (2013) find momenum in corporae bonds o arise from differen mechanism han ha for sock reurns. Furher, price pressure in corporae bonds is weak (e.g., Ellul e al., 2012). A he same ime, mos corporae bond funds are acively managed, and hus similar o acively managed equiy funds, invesors in corporae bond funds should value fund performance in heir decision-making. Therefore, he quesion of wha deermines invesor flows in corporae bond funds, as well as heir effecs, are imporan and sill open. Based on a sample of 418 corporae bond funds over he period , we conduc a rich se of ess on he deerminans and predicabiliy of invesor flows. Firs, we show ha invesor flows in corporae bond funds chase recen fund reurns. However, unlike he convex 2 Over he same period, he whole US muual fund indusry experienced an average growh rae of 12% per year. 2

4 flow-performance relaion found in equiy funds (e.g., Chevalier and Ellison, 1997; Sirri and Tufano, 1998), he flow-performance relaion in corporae bond funds is no convex. Tha is, corporae bond fund invesors reac o poor performance as sensiively as o good performance. In addiion, fund flows are sensiive o macro condiion such as ineres rae and defaul spread. Nex, we find srong evidence ha invesor flows predic fund performance in corporae bond funds. Funds experiencing ne inflows subsequenly ouperform hose wih ne ouflows. For example, he flow-weighed porfolio of funds wih ne inflows ouperforms he porfolio of funds wih ne ouflows by abou 0.19% in he nex monh (-saisic = 3.23) afer adjusing for risk exposures. The evidence of he predicabiliy of flows is robus o several sensiiviy ess, such as conrolling for sale pricing in corporae bonds (e.g., Warga, 1991; Cici, Gibson, and Merrick, 2011) and reurn momenum (Josova e al., 2013). Furher, he predicabiliy exiss in boh invesmen-grade and high-yield bond funds, and in boh reail and insiuional share classes. In addiion, he predicabiliy of flows lass for up o hree years. However, he predicabiliy of invesor flows is subsumed by fund performance persisence. Tha is, once pas fund performance is conrolled for, invesor flows do no predic fuure fund performance. The resul suggess ha he predicabiliy of flows arises from he facs ha invesors chase fund performance and fund performance persiss. Due o he performancechasing behavior, new money is flowed ino (ou of) pas winner (loser) funds. Because of performance persisence, winner funds wih money inflows coninue o ouperform loser funds wih money ouflows in he fuure, which explains he smar money effec. Finally, we explore he naure of informaion used by fund invesors. In paricular, we examine he predicabiliy of idiosyncraic flow ha is defined as he componen of flow unexpeced by recen fund performance or macro condiion. If invesors use finer-han-public 3

5 informaion, we would expec idiosyncraic flows o predic fund performance. In fac, we find lile evidence ha idiosyncraic flows can predic fund performance, which suggess ha fund invesors make invesmen decisions mainly using public informaion raher han privae informaion. Our paper makes imporan conribuions o he lieraure on fund flows and invesor behavior. Firs, we provide a comprehensive examinaion of he deerminans of invesor flows in corporae bond funds based on monhly flows from a large sample. Though Zhao (2005) and Comer and Rodriguez (2008) documen sensiiviy of bond fund flows o pas performance, hey examine quarerly or annual flows over a shor period. To our knowledge, we are he firs o examine how macro condiion affecs bond fund flows. Furher, our paper adds o he lieraure by providing an in-deph invesigaion of he predicabiliy of invesor flows. Afer evaluaing alernaive explanaions, we show ha fund performance persisence combined wih he reurnchasing behavior is responsible for he predicabiliy of fund flows. Though Fulkerson, Jordan, and Riley (2013) find evidence of he smar money effec in bond funds, hey do no invesigae he mechanism behind he effec. We also relae our findings o prior research abou invesor flows in equiy funds, which offers an inegraed view of invesor behavior in he muual fund indusry. Finally, we invesigae he naure of informaion used by fund invesors by decomposing fund flow ino sysemaic and idiosyncraic flow. The res of he paper proceeds as follows. Secion 2 describes he daa. In Secion 3, we examine how invesor flows are relaed o fund performance and macro condiion. In Secion 4, we show evidence of he predicabiliy of invesor flows and evaluae alernaive explanaions. Finally, Secion 5 offers some concluding remarks. 4

6 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 he risk-adjused performance in he ess for he predicabiliy of fund flows. 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 funds ne-of-expense reurns, oal ne asses (TNA) and various fund characerisics. Our sample covers US corporae bond funds over he period We mainly employ monhly daa of he funds, hough we check he robusness of our inference using quarerly daa as well. Our sample sars in 1991 when monhly informaion on fund size firs became available in he daabase. Our daa covers boh live and defunc funds. We idenify corporae bond funds by heir objecive codes. 3 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 (Evans, 2010), associaed wih small or young funds. 4 We also exclude funds holding more han 30% governmen bonds and equiies combined because of heir differen risk exposures. Finally, we aggregae all share classes (e.g., reail and insiuional share classes) o he fund level. Our sample includes a oal of 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 funds wih all oher objecive codes are caegorized as invesmen-grade bond funds. 4 Our resuls are robus o oher screening crieria such as requiring fund size o exceed $5 million and fund age o be a leas one year. 5

7 corporae bond funds, among which 189 are invesmen-grade bond funds ha mainly hold invesmen-grade corporae bonds and 229 high-yield bond funds ha hold bonds wih a crediraing lower han invesmen grade. Panel A of Table 1 summarizes fund characerisics. In he sample, he average (median) TNA is $893 ($262) million, suggesing ha fund size is skewed by large funds. The average (median) fund age is abou 14 (12) years. Expense raio, as he raio of a fund s operaing expenses over oal invesmen, averages around 1.1% per year. 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 103% per year for he overall sample. High-yield bond funds, on average, have lower urnover han invesmengrade bond funds, which is consisen wih he noion ha high-yield bonds are ofen less liquid han invesmen-grade bonds. Panel B of he able repors ime-series average of he cross-secional disribuion of monhly fund reurns. Over he sample period, he mean reurn of all sample funds is 0.60% per monh (or, 7.2% annually). In addiion, he mean reurn for invesmen-grade bond funds is 0.47% per monh, while he mean reurn for high-yield bond funds is 0.66% per monh. Meanwhile, high-yield bond funds exhibi an average reurn serial-correlaion of 23.23%, which is higher han hose for invesmen-grade bond funds and he sock marke index. 2.2 Invesor Flows Muual fund flows reflec invesmen decisions of fund invesors. Following he lieraure, we compue invesor flows for a fund in a given period as he percenage change in fund TNA 6

8 during he period minus he change in TNA caused by fund reurn realized in he same period. For each fund in each monh, is ne flow raio is calculaed as follows. TNAi, TNAi, 1(1 Ri, ) Flow i,, (1) TNA where TNAi, is he oal ne asse of fund i a he end of monh, and Ri, is he reurn of fund i in monh. One issue o be considered is fund mergers. A merger adds new money o he acquiring fund, hough such money inflow does no reflec invesors decision. To miigae he poenial effec, we delee merger funds observaions for he following monh afer a merger happens. Following Huang, Wei, and Yan (2007), we remove exreme flow raios (i.e., greaer han 50% or smaller han 50% in a monh) ha could be due o misrepored fund mergers and splis. Panel C of Table 1 summarizes he cross-secional disribuion of flow raio. The average (median) flow raio is 0.24% ( 0.14%) in a monh, wih a sandard deviaion of 6.27% per monh. The average flow raio here appears o be smaller han ha documened for equiy funds, bu he dispersion in flow raio is comparable o ha for equiy funds (e.g., Huang, Wei, and Yan, 2012). This suggess ha capial flows acively in corporae bond funds as well. In he meanime, here is a high level of serial-correlaion in he flow raio. For he overall sample, he firs-order serialcorrelaion is abou 30% on average. i, Facor Models and Fund Performance In Secion 4 when we invesigae he predicabiliy of fund flows, we use wo mulifacor models following Blake, Elon, and Gruber (1993) and Elon, Gruber, and Blake (1995) o measure he risk-adjused performance for funds experiencing differen money flow paerns. The firs is a wo-facor regression model: 7

9 R R G ( HY IG ) e, (2) i, f G HYHQ where Ri, is he reurn on fund i in monh, Rf is he risk-free rae proxied by one-monh T-bill rae, G is he excess reurn on he governmen bond index, (HY IG) is he spread beween he high-yield bond index and he invesmen-grade bond index. The inercep, or alpha, reflecs invesmen reurns in excess of a fair compensaion for risk exposures. The second model is he following four-facor regression model: 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 aggregae bond index, DEF is he reurn spread beween he high-yield bond index and he inermediae governmen bond index, and OPTION is he reurn spread beween he GNMA morgage-backed securiy index and he inermediae governmen bond index. Following Elon, Gruber, and Blake (1995), he OPTION facor is included o capure he possibiliy ha some funds hold morgage-backed securiies ha have an opion feaure. 5 All he bond index daa are obained from Barclays Capial. Panel D of Table 1 summarizes he facors. Over he sample period, governmen bonds realize an average excess reurn of 0.26% per monh, while high-yield bonds have an average reurn higher han invesmen-grade bonds by 0.14% per monh. The aggregae sock index shows an average excess reurn of 0.61% per monh, and he aggregae bond index has an average excess reurn of 0.28% per monh. The defaul spread averages of 0.25% per monh, while he mean spread beween he GNMA and governmen bond indices is 0.04% per monh. 5 In general, corporae bond muual funds do no hold a large fracion of morgage-backed securiies. No surprisingly, he average fund has a negaive loading on he OPTION facor as shown in Table 2, suggesing ha funds have higher exposure o governmen bonds han o morgage-backed securiies. Our inference is robus o omiing he OPTION facor in he analysis. 8

10 Table 2 repors fund performance a he aggregae level based on equal-weighed porfolios. Overall, corporae bond funds underperform he benchmarks afer fees and expenses, consisen wih prior research (e.g., Blake, Elon, and Gruber, 1993; Chen, Ferson, and Peers, 2010; Cici and Gibson, 2012). 6 Based on he four-facor model, he porfolio of all funds has an alpha of 0.05% per monh, or abou 0.60% per year. The facors explain bond fund reurns well, wih he R-squared above 90% in he four-facor model across he regressions The Deerminans of Invesor Flows In his secion, we invesigae he deerminans of invesor flows o corporae bond funds. Prior sudies on equiy funds find ha flows chase pas fund performance, and he flowperformance relaion is convex suggesing ha invesors are more sensiive o good performance bu less sensiive o bad performance (e.g., Chevalier and Ellison, 1997; Sirri and Tufano, 1998). Here, we examine how corporae bond fund invesors reac o recen fund performance. Since macro variables explain bond reurns well, we also es how invesor flows change wih macro condiion. 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 ne flow on lagged values of fund performance rank, volailiy, and fund characerisics. Performance rank is he fracional rank (ranging from 0 o 1) of fund raw reurn 6 A he individual fund level, several sudies find posiive risk-adjused performance and iming abiliy in a small fracion of bond funds, such as Chen, Ferson, and Peers (2010), Cici and Gibson (2012), Huang and Wang (2014), and Monea (2015). 7 We also consider a condiional model similar o Ferson and Schad (1996) and augmen he four-facor model wih a liquidiy facor. Our inference is robus o he alernaive facor models. 9

11 relaive o oher funds wihin he same fund syle (invesmen-grade or high-yield bond funds) in he previous 12 monhs. 8 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 sandard errors. Table 3 repors he findings. For he overall sample, he regression coefficien on lagged fund performance rank suggess ha invesor flows chase pas fund performance. For he overall sample, moving from he wors o he bes percenile would, on average, be associaed wih a 1.4% (-saisic = 13.24) increase in fund ne flow. In addiion, money flows are posiively associaed wih fund size, especially for invesmen-grade bond funds. There is some evidence ha fund flows are negaively associaed wih fund volailiy. Invesor flows appear o be negaively relaed o expense raio, bu he relaion is no saisically significan. Older funds have lower flow raio, suggesing ha he growh in fund size slows down as a fund maures. Meanwhile, flows exhibi persisence, as presen flows are posiively relaed o pas flows. We also examine a family spillover effec. We use a family spillover dummy variable ha equals one if reurn o one of he funds in he family is ranked among op 10% among all funds in he same fund syle in he previous 12 monhs, and zero oherwise. Oher hings equal, he exisence of a op-performing fund in a fund family is associaed wih an addiional flow of 0.2% (-saisic = 3.43) in he curren monh o all funds in he family. 9 Thus, money flow o a fund is affeced by he performance of oher funds in he same family. We nex evaluae possible non-lineariy in he flow-performance relaion using piecewise linear regressions. Following Sirri and Tufano (1998), we break down fund performance rank ino quiniles in each monh so ha he flow-performance sensiiviy can be 8 We use performance rank o accoun for he fac ha invesmen-grade and high-yield bond funds have differen average reurns. 9 Sirri and Tufano (1998) and Nanda, Wang, and Zheng (2004) sudy he spillover effec in equiy muual funds. 10

12 examined for each quinile separaely. Here, we find no significan convexiy beween invesor flows and pas fund performance. For he overall sample, he average regression coefficien in he boom quinile is similar o ha in he op quinile, and a es for saisical significance of he difference beween he coefficiens shows a -saisic of The lack of convexiy in he flow-performance relaion can also be seen in Figure 1. In oher words, corporae bond fund invesors reac o poor fund performance in a similar way o good performance. 10 We also examine he flow-performance relaion for invesmen-grade and high-yield bond funds separaely. Similar o he overall sample, here is no convexiy for eiher fund syle. Prior research (e.g., Brown, Harlow, and Sarks, 1996; Chevalier and Ellison, 1997) argues ha he convex flow-performance relaionship in equiy funds moivaes fund managers risk-shifing behavior (i.e., fund managers increase porfolio risk afer heir performance is behind peer funds), and Huang, Sialm, and Zhang (2011) show ha risk-shifing is cosly for fund invesors. I would be ineresing o examine if bond funds also engage in risk-shifing wihou a convex flowperformance relaion, and we leave his opic for fuure research. 3.2 Macro Condiion and Invesor Flows As shown in Secion 2, bond fund reurns can be well explained by facors including bond-relaed macro variables. Moivaed by his observaion, we nex examine wheher invesor flows are also sensiive o recen macroeconomic condiion. To his end, we conduc a pooled ime-series and cross-secional regression. The dependen variable is monhly fund flows, and he 10 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. 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 flow-performance relaion in equiy funds has become less convex afer Recenly, Sialm, Sarks, and Zhang (2013) find ha flows reac mos srongly o exreme performance quiniles for defined conribuion (DC) pension plans, and he flow-performance relaion is slighly convex for non-dc pension plans. 11

13 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 fund fixed effec is 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 previous monh is associaed wih abou a 0.22% (saisic = 9.64) ne money inflow ino an average bond fund. Meanwhile, invesor flows show a significanly negaive reacion o he hree-monh T-bill rae, which is inuiive since an increase in ineres rae is associaed wih a drop in bond reurns. We also find a posiive associaion beween he defaul spread and money flows ino invesmen-grade bond funds, suggesing ha more capial flows ino relaively safe funds when defaul risk is higher. Furher, flows o high-yield bond funds are posiively relaed o he opion facor, implying ha such funds receive larger money flow when morgage-backed bonds realize higher reurns. In addiion, flows o high-yield bond funds show a posiive sensiiviy o sock marke reurn, reflecing a similariy beween high-yield bonds and socks. Ineresingly, flows o corporae bond funds have a posiive reacion o he recen VIX index, indicaing ha more money flows ino corporae bond funds when he sock marke becomes volaile. In sum, for he firs ime in he lieraure, we presen evidence on he relaion beween macro condiion and corporae bond fund flows. In addiion, he coefficiens on he fund-specific variables in Table 4 are generally consisen wih hose repored in Table 3. Taken ogeher, we show ha invesor flows o corporae bond funds are sensiive o no only recen fund performance bu also macro condiion. A he same ime, unlike previous findings for equiy funds, he flow-performance relaion is no convex for corporae bond funds. 12

14 4. Can Invesor Flows Predic Fund Performance? This secion examines he predicabiliy of invesor flows for fund performance. Gruber (1996) and Zheng (1999) provide he firs evidence of he smar money effec in equiy funds, bu he underlying mechanism has been debaed. I could reflec invesors using fine informaion o selec funds, and i could also sem from some aribues of he funds or underlying asses. 11 While he previous sudies examine equiy funds, we look ino corporae bond funds. 4.1 Predicabiliy of Invesor Flows We firs follow Zheng (1999) o examine he payoffs o rading sraegies involving funds ha experience differen paerns of invesor flows. Specifically, we consruc he following four porfolios of 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 11 Zheng (1999) conjecures ha reurn momenum can cause such a predicabiliy, and Sapp and Tiwari (2004) show ha he predicabiliy is largely reduced once momenum is conrolled for. In sudying UK muual funds, Keswani and Solin (2008) find he predicabiliy even afer conrolling for momenum. Wermers (2003) shows ha equiy fund invesors end o inves in pas winner funds, and winner funds inves new money heavily in momenum socks and push up heir prices. Recenly, Lou (2012) shows ha flow-induced price pressure explains he predicabiliy in equiy funds. 13

15 beween he porfolios. The risk-adjused performance is esimaed by ime-series regressions based on he mulifacor models described in Secion 2. Table 5 presens evidence ha srongly suggess he predicabiliy of invesor flows in corporae bond funds. The posiive-flow porfolios significanly ouperform he negaive-flow porfolios on a risk-adjused basis. For example, he reurn spread beween Porfolios 3 and 4 shows a four-facor alpha of 0.19% per monh, or abou 2.28% per year (-saisic = 3.23). Noe ha alpha of he posiive-flow porfolio is no significanly posiive, bu alpha of he negaiveflow porfolio is significanly negaive. Hence, he spread of alpha beween he flow-sored porfolios is mainly from under-performance of he negaive-flow funds, and such alpha canno be fully realized in pracice because muual fund shares are no shorable. Noneheless, invesing in posiive-flow funds would be beer off han invesing in an average fund. I is well known ha corporae bond prices can be sale due o hin-rading (e.g., Warga, 1991; Cici, Gibson, and Merrick, 2011). The high auocorrelaion in fund reurns (especially for high-yield bond funds) repored in Table 1 is likely o be driven by sale prices. If money flows ino funds wih highly sicky reurns, we migh observe a spurious smar money effec. To rule ou he possible effec of sale pricing, we repea our inference using invesor flows calculaed based on quarerly fund reurns and TNA values. Table 6 repors he resuls. Based on quarerly daa, here is sill significan evidence of he predicabiliy of fund flows. For example, Porfolio 3 ouperforms Porfolio 4 by abou 0.38% per quarer (-saisic = 2.41) according o he fourfacor model. To furher conrol for he effec of sale pricing, we conduc anoher robusness es. When measuring he performance for he flow-sored porfolios, we include lagged facor reurns in he facor models. As shown in Dimson (1979) and Asness, Krail, and Liew (2001), his 14

16 procedure can reduce regression biases associaed wih illiquid holdings of he funds. From his es, we sill observe significan evidence of he predicabiliy of flows. To conserve space, he deails of he es resuls are no repored bu are available upon reques. Nex, we invesigae wheher momenum can explain he predicabiliy of fund flows. 12 Earlier sudies (Gebhard, Hvidkjaer, and Swaminahan, 2005; Guierrez, Maxwell, and Xu, 2009) find no evidence of reurn momenum in invesmen-grade bonds. However, Josova e al. (2013) documen significan evidence of reurn momenum for high-yield bonds. 13 Here, we repea our es by including he bond momenum facor consruced in Josova e al. (2013) in he facor models. The resuls are presened in Table 7. Ineresingly, wih he momenum facor included, he risk-adjused reurns end o be higher han hose wihou he momenum facor (as repored in Table 5) accordingly o he wo-facor model, bu slighly lower according o he four facor model. More imporanly, wih conrol for bond momenum, he funds wih ne inflows coninue o ouperform hose wih ne ouflows by abou 0.26% per monh (-saisic = 2.61) based on he momenum-augmened four-facor model. Thus, momenum does no explain he smar money effec in corporae bond funds. In addiion, we examine wheher he difference in fund expenses could explain he difference in afer-expense performance beween he flow-sored porfolios. Suppose ha all funds have he same pre-expense performance and invesor direc money ino low-expense funds and ou of high-expense funds, hen we may observe a predicabiliy of invesor flows due o he posiive associaion beween money flow and afer-expense fund performance. To examine his possibiliy, we add fund expenses back o fund reurns and repea he ess using pre-expense reurns, and we sill find significan predicabiliy of invesor flows. Thus, he dispersion in fund 12 Momenum refers o he coninuaion in asse reurns beween winners and losers (Jegadeesh and Timan, 1993). 13 Kim, Mahajan, and Pekevich (2012) find ha momenum profis in corporae bonds exis only during weakening aggregae credi condiions. 15

17 expenses does no explain he predicabiliy. The deails of he es are no repored o conserve space bu are available upon reques. In sum, we presen robus evidence ha invesor flows can predic fuure performance in bond funds. The predicabiliy canno be explained by sale pricing of bonds, bond reurn momenum, or fund expenses. 4.2 Predicabiliy of Invesor Flows in Differen Types of Funds Here, we explore he effec of heerogeneiy in funds on he predicabiliy of flows. Firs, we examine wo subsamples for invesmen-grade bond funds and high-yield bond funds, separaely. As shown in Panels A C of Table 8, he predicabiliy of flows exiss in boh fund syles since he posiive-flow porfolio significanly ouperforms he negaive-flow porfolio. Based on he four-facor model, he alpha spread beween he posiive- and he negaive-flow porfolios is 0.20% per monh (-saisic = 2.20) among invesmen-grade bond funds, while he alpha spread is 0.12% per monh (-saisic = 3.66) among high-yield bond funds. Alhough he predicabiliy of flows in invesmen-grade bond funds appears o be somewha sronger han ha in high-yield bond funds, he difference in he alpha spread beween he wo fund syles is no saisically significan. Nex, we examine he predicabiliy of fund flows from reail invesors and insiuional invesors, separaely. Since a fund can offer a share class o reail invesors and anoher share class o insiuional invesors, we employ he share-class level (no he fund-level) daa in his es. 14 Flows from reail and insiuional invesors migh have differen predicabiliy for fuure fund reurns. For example, if insiuional invesors possess finer informaion abou fund prospec, 14 Nanda, Wang and Zheng (2009) examine he effecs of he inroducion of muliple share classes in he muual fund indusry. 16

18 hen we would expec heir flows o beer predic fund reurns. On he oher hand, reail invesors may pay more aenion o recen fund performance when allocaing heir capial, and if here is fund performance persisence, heir flows could show sronger predicabiliy. As shown in Panels D F of Table 8, he predicabiliy of flows is presen in boh reail and insiuional share classes. The predicabiliy seems somewha sronger among reail invesors han among insiuional invesors, bu he difference is saisically insignifican. 4.3 Fund Size and he Predicabiliy of Invesor Flows We now es for possible relaion beween fund size and he predicabiliy of flows. In he conex of equiy funds, Zheng (1999) finds ha he predicabiliy is more pronounced in small funds. We es for a poenial paern for corporae bond funds. In each monh, we divide funds ino 5 quiniles by heir sizes a he end of he previous monh, and hen we compare he alpha spread beween he posiive-flow and negaive-flow porfolios across he quiniles. Table 9 shows ha he predicabiliy of flows exiss among all he quiniles in he overall sample and has similar magniude for small funds (quanile 1) and large funds (quinile 5). In he quinile of smalles funds, he posiive-flow porfolio ouperforms he negaive-flow porfolio by an alpha of 0.15% per monh, while in he quinile of larges funds, he posiive-flow porfolio ouperforms he negaive-flow porfolio by an alpha of 0.16% per monh. Looking a invesmengrade and high-yield bond funds separaely, we find ha across all he size quaniles, he posiive-flow porfolio significanly ouperforms he negaive-flow porfolio in 6 ou of he 10 cases. However, here is no evidence ha he predicabiliy is sronges among small funds. 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 subsanial price impac. 17

19 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. For his subsample of funds, we sill find significan evidence of predicabiliy of flows. The deails of he es are no repored o conserve space bu are available upon reques. 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. A shor-lived predicabiliy is more likely o be a resul from emporary price movemen, while a long-lasing one could reflec informaion used by invesors. We examine he duraion of he predicabiliy by looking a he performance of he flow-sored porfolios over differen holding periods. Specifically, in each monh we form flow-sored porfolios of he funds, and hese porfolios are held subsequenly for differen periods ranging from 1 o 36 monhs. The procedure is similar o ha used in Jegadeesh and Timan (1993) and provides ou-of-sample reurns on he porfolios, 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 10 shows ha he predicabiliy of flows is no shor-lived. As before, we infer he predicabiliy by alpha spread of he flow-sored porfolios. For he overall sample, he alpha spread remains significan for up o 36 monhs afer porfolio formaion. For insance, he alpha spread is 0.10% per monh (-saisic = 2.30) for he 6-monh holding period. For invesmen-grade bond funds, he predicabiliy is presen for up o 6 monhs. Take he 6-monh holding period as an example: is alpha spread is 0.12% per monh (-saisic = 1.75) 18

20 ha ranslaes o abou 1.44% per year. For high-yield bond funds, he spread in pos-formaion alpha beween he wo porfolios is significan for up o 36 monhs, and for he 6-monh holding period, he alpha spread is 0.09% per monh (-saisic = 3.53). In sum, we find he predicabiliy of flows o las for a period as long as 36 monhs. This suggess ha he predicabiliy is likely o be informaion-driven. Such informaion can be public informaion like pas fund performance, or privae informaion abou fund prospec. We invesigae he naure of informaion used by fund invesors laer in Secion Regression Analysis of he Predicabiliy of Invesor Flows Thus far, we have presened robus evidence of he predicabiliy of flows. To explore he underlying mechanism, we perform Fama-MacBeh regressions of fund alpha on one-monh lagged ne flow as well as various conrols. 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 facor loadings and realizaions of he facors, wih he facor loadings esimaed from he four-facor model using fund reurns in he previous 36 monhs. Table 11 repors he resuls from six differen regression specificaions. The firs specificaion is o regress fund alpha on lagged flow alone. We find ha lagged flow is significanly posiively associaed wih fund alpha. This resul suggess he exisence of he predicabiliy of fund flows, consisen wih he findings from he flow-sored porfolios. The second specificaion adds an ineracion erm of lagged flow and an ouflow dummy ha equals one if he fund has ne money ouflow in he previous monh or zero oherwise, o es for possible asymmery in he effec of inflow and ouflow. The coefficien on he ineracion erm is significanly posiive, indicaing ha ouflow has a greaer effec on fund performance 19

21 han inflow does. The finding is consisen wih a fire sale sory: When experiencing subsanial money wihdrawal from invesors, a fund is forced o liquidae asses and such liquidaion pushes down asse prices and fund reurns. 15 However, afer conrolling for he asymmeric relaion, lagged flow is sill posiively relaed o fund alpha. In he hird and fourh specificaions, we use a proxy for fund illiquidiy o es he effec of price pressure on he predicabiliy of flows. We use serial correlaion in fund reurns o proxy for illiquid holdings. For each fund in monh, we run an AR(3) regression of fund reurns over he previous 12 monhs up o monh -1, and use he sum of absolue value of he hree AR coefficiens o capure fund illiquidiy. We look a absolue value because illiquid holdings can cause sale rading (and hus posiive auocorrelaion in reurns), and can also be associaed wih reurn reversal (negaive auocorrelaion). In general, less liquid holdings are expeced o impose greaer price pressure. In our seing, here is no evidence ha fund illiquidiy conribues o he predicabiliy of flows. 16 This resul makes sense, given ha prior research finds relaively weak price pressure in corporae bond markes (e.g., Ellul, Joikashira, and Lundbad, 2012). In he meanime, lagged flow remains predicive of fund performance. In he las wo regression specificaions, we add lagged fund reurn in he prior year o he regression. Wih he conrols for fund characerisics, he regression coefficien on lagged flow 15 See Shleifer and Vishny (1992) for a general discussion on fire sales. Coval and Safford (2007) and Zhang (2011) sudy he effec of fire sales on sock price and equiy fund performance. Ellul, Joikashira, and Lundbad (2012) examine fire sales by regulaory-consrained insurance companies ha hold downgraded corporae bonds. 16 In he hird and fourh specificaions, he dependen variable alpha is calculaed based on facor loadings esimaed using fund reurns in he pas 36 monhs. Since he righ-hand-side AR variable is also esimaed based on pas fund reurns, his could generae a mechanical relaionship in he regressions. However, as he coefficiens on he AR variables are insignifican, a spurious relaionship seems no a major concern. To furher alleviae such a concern, we replace he dependence variable wih fund raw reurn and raw reurn in excess of a bond index in monh in robusness ess, and our resuls are robus o he wo alernaive specificaions. Anoher poenial issue is ha he absolue value of AR coefficiens capures he ne effec of sale pricing and reurn reversal. If boh effecs exis wihin he same monh, he proxy based on AR coefficiens is likely o underesimae he level of illiquidiy. Bu given ha price pressure is relaively weak in corporae bonds, his underesimaion seems unlikely o severely bias our inference. We leave his issue for fuure research. 20

22 shrinks o 0.20 (-saisic = 1.32). Hence, once lagged fund reurn is conrolled for, he predicabiliy of flows largely disappears. Meanwhile, fund performance appears o persis as pas fund reurn significanly predics fund alpha, similar o he findings of Huij and Derwall (2008) and Guierrez, Maxwell, and Xu (2009). Prior research (e.g., Carhar, 1997) finds lile evidence of performance persisence for equiy funds. Berk and Green (2004) build a model in which fund performance does no persis when invesors chase fund performance and funds face decreasing reurns o scale. Empirically, Chen e al. (2004) show ha equiy fund performance declines wih fund size, supporing he noion of diseconomies of scales. Relaedly, Edelen, Evans, and Kadlec (2007) find rading coss o accoun for he diseconomies of scale as rading coss increase wih fund rade size in equiy funds. Ineresingly, hough corporae bond fund invesors chase fund performance (as repored in Secion 3), Table 11 shows no evidence ha fund size erodes fund performance, suggesing ha corporae bond funds do no face severe diseconomies of scale. This makes sense as rading coss of corporae bonds ypically decrease wih rade size and insiuion size (e.g., Schulz, 2001). Therefore, he differences in rading coss and reurns o scale help explain why performance persisence exiss in corporae bond funds, bu no in equiy muual funds. 4.6 Predicabiliy of Invesor Flows Condiional on Recen Fund Performance We now furher invesigae how pas fund performance affecs he inference abou he predicabiliy of flows. We sor he sample funds ino 5 quiniles based on heir reurns in he previous year. By examining he predicabiliy of flows wihin each quinile, we conrol for pas fund reurn. If he predicabiliy of flows is accouned for by pas performance, we would expec insignifican alpha spread in he quiniles. 21

23 Table 12 repors alpha spreads beween he flow-sored porfolios for he quinile groups. The cenral message is ha he predicabiliy of flows is largely subsumed by performance persisence. For he overall sample, he smar money effec is insignifican in 4 ou of he 5 quinile groups, wih he group of poores-performing funds as he only excepion. A similar impression is obained for boh invesmen-grade and high-yield bond funds; he predicabiliy of flows is insignifican for 9 ou of he 10 cases. Therefore, once we conrol for pas fund reurn, he predicabiliy of flows ends o disappear. Taken ogeher, our resuls sugges ha he predicabiliy of flows in corporae bond funds arises from he facs ha invesors chase fund performance and fund performance persiss. Tha is, capial flows ino (ou of) pas winner (loser) funds so ha he posiive (negaive)-flow porfolio conains more of pas winner (loser) funds. Because of performance persisence, he posiive-flow porfolio coninues o ouperform he negaive-flow porfolio. To have an inegraed undersanding of he predicabiliy of flows, we relae our resuls in o hose documened for equiy funds. In he conex of equiy funds, Gruber (1996) and Zheng (1999) also sugges ha he smar money effec is relaed o performance persisence, hough hey do no es he explanaion inensively. Sapp and Tiwari (2004) find ha reurn momenum explains he predicabiliy of flows in equiy funds. Lou (2012) shows ha flow-induced price pressure on sock prices accouns for he predicabiliy of flows. Ineresingly, reurn momenum and price pressure are found o explain performance persisence in equiy funds (Carhar, 1997; Lou, 2012), and hus performance persisence is likely o conribue o he smar money effec in equiy funds as well. 22

24 4.7 Idiosyncraic Flows We have shown ha he predicabiliy of flows is likely o be informaion-driven. Now, we invesigae he naure of informaion public or privae informaion used by invesors o direc capial ino differen funds. We perform a es o examine he predicabiliy of idiosyncraic flow ha is defined as he componen of flow unexpeced by recen fund performance or macro condiion. 17 This componen of flow is idiosyncraic for wo reasons. Firs, since i is unrelaed o recen fundspecific or macro-level variables, i is more likely o reflec invesors idiosyncraic decisions (e.g., idiosyncraic liquidiy needs). Second, i is compued for each individual fund separaely. Each monh, idiosyncraic flow for each individual fund is he inercep plus residual from a ime-series regression of he fund s invesor flow on lagged values of fund-specific and macrolevel variables. Flow a b' Fund - specific Variable i,-1 c' MacroVariables -1 ui,, (4) i, where fund-specific variables (including fund reurns and characerisics) and macro variables are hose described in Secion 3. If invesors possess superior informaion abou he funds, idiosyncraic flows should predic fund performance. However, if invesors mainly rely on public informaion in decision-making, idiosyncraic flows reflec heir idiosyncraic need and should no relae o fuure fund performance. Similar o he porfolios consruced based on sors of fund flows in he previous monh, we form four porfolios of funds based on idiosyncraic flows Ferson and Kim (2012) examine sysemaic versus idiosyncraic flow based on facor analysis using eigenvecors exraced from aggregae fund flows. 18 For each fund in each monh, idiosyncraic flow is esimaed based on he fund s whole record and hus has lookahead bias. However, our purpose is no o develop a rading sraegy, bu o examine wheher fund flow conains informaion above and beyond public informaion. In a robusness es, we eliminae he look-ahead bias by esimaing idiosyncraic flow using only he fund s record up o ha monh, and our inference is unchanged. 23

25 Porfolio 5: Equal-weighed porfolio of all funds wih posiive idiosyncraic flows. Porfolio 6: Equal-weighed porfolio of all funds wih negaive idiosyncraic flows. Porfolio 7: Flow-weighed porfolio of all funds wih posiive idiosyncraic flows. Porfolio 8: Flow-weighed porfolio of all funds wih negaive idiosyncraic flows. We refer o Porfolios 5 and 7 as posiive-idiosyncraic-flow porfolios, while Porfolios 6 and 8 as negaive-idiosyncraic-flow porfolios. As before, we examine he spread of risk-adjused performance beween hese porfolios based on he wo-facor and he four-facor models. Table 13 shows ha idiosyncraic flows do no significanly predic fund performance. The four-facor alpha spread beween Porfolios 7 and 8, hough sill posiive a 0.06% per monh (-saisic = 1.19), is no longer of economic or saisical significance. In oher words, he funds wih posiive idiosyncraic flows do no subsequenly ouperform he funds wih negaive idiosyncraic flows. Figure 2 illusraes he difference in predicaive power of raw flows versus idiosyncraic flows. Wih recen fund-specific and macro variables conrolled for, he unexpeced flows exhibi lile predicabiliy for fund performance. Therefore, he resul suggess ha fund invesors make invesmen decisions based on public informaion raher han privae informaion. However, from he perspecive of invesors, he use of public informaion seems raional since i is associaed wih beer invesmen payoffs in he fuure. 5. Conclusion This paper provides a comprehensive examinaion of invesor flows in corporae bond funds. Corporae bond funds offer a new and imporan seing o sudy invesor flows. Using a 24

26 sample of 418 US corporae bond funds over he period , we presen new insighs abou he behavior of muual fund invesors. Firs, we show ha invesor flows in corporae bond funds chase recen fund performance, bu unlike he case for equiy funds, he flow-performance relaion is no convex in corporae bond funds. We also find ha invesor flows are sensiive o recen macro condiion. Nex, we presen robus evidence of he predicabiliy of flows, i.e., funds experiencing ne inflows subsequenly ouperform hose wih ne ouflows. This is similar o he prior finding for equiy funds (e.g., Gruber, 1996; Zheng, 1999). More imporanly, we show ha his predicabiliy canno be explained by momenum or price pressure bu is subsumed by fund performance persisence. Finally, we invesigae he naure of informaion used by fund invesors by looking ino idiosyncraic flows ha are unrelaed o pas fund performance and macro condiion. Our resul reveals lile evidence ha idiosyncraic flows predic fuure fund performance. Hence, we conclude ha fund invesors do no use finer-han-public informaion in heir decision-making. I would be ineresing for fuure research o examine he risk-shifing behavior in corporae bond funds, given a lack of convex flow-performance relaionship. Anoher poenial area is o sudy fund managers purchasing and selling aciviies in response o capial flows, when deailed informaion on fund holdings becomes available. Finally, our measure of idiosyncraic flow can be used in oher seings such as equiy funds and pension funds. We leave hese opics for fuure research. 25

27 References Agarwal, Vikas, Naveen Daniel, and Narayan Naik, 2004, Flows, performance, and managerial incenives in hedge funds, Working paper, available on SSRN. Asness, Clifford, Rober Krail, and John Liew, 2001, Do hedge funds hedge? Journal of Porfolio Managemen 28, Berk, Jonahan, and Richard Green, 2004, Muual fund flows in raional markes, Journal of Poliical Economy 112, Blake, Chrisopher, Edwin Elon, and Marin Gruber, 1993, The performance of bond muual funds, Journal of Business 66, Brown, Keih, W. Van Harlow, and Laura Sarks, 1996, Of ournamens and empaions: An analysis of managerial incenives in he muual fund indusry, Journal of Finance 51, Brown, Sephen, William Goezmann, and James Park, 2001, Careers and survival: Compeiion and risk in he hedge fund and CTA indusry, Journal of Finance 56, Carhar, Mark, 1997, On persisence in muual fund performance, Journal of Finance 52, Chen, Joseph, Harrison Hong, Ming Huang, and Jeffrey D. Kubik, 2004, Does fund size erode muual fund performance? The role of liquidiy and organizaion, American Economics Review 94, Chen, Yong, Wayne Ferson, and Helen Peers, 2010, Measuring he iming abiliy and performance of bond muual funds, Journal of Financial Economics 98, Chevalier, Judih, and Glenn Ellison, 1997, Risk aking by muual funds as a response o incenives, Journal of Poliical Economy 105, Cici, Gjergji, and Sco Gibson, 2012, The performance of corporae-bond muual funds: Evidence based on securiy-level holdings, Journal of Financial and Quaniaive Analysis 47, Cici, Gjergji, Sco Gibson, and John Merrick, 2011, Missing he marks: Dispersion in corporae bond valuaions across muual funds, Journal of Financial Economics 101, Comer, George, and Javier Rodriguez, 2008, An analysis of invesmen syle, performance, and cash flows of fixed income funds, Working paper, Georgeown Universiy. Coval, Joshua, and Erik Safford, 2007, Asse fire sales (and purchases) in equiy markes, Journal of Financial Economics 86,