CFR Working Paper No. 11-07 Performance inconsistency in mutual funds: An investigation of window- dressing behavior V. Agarwal • G. D. Gay • L. Ling Performance inconsistency in mutual funds: An investigation of window-dressing behavior VIKAS AGARWAL GERALD D. GAY and LENG LING* First Version: March 31, 2011 This version: February 7, 2012 JEL Classification: G11; G20 Keywords: Mutual funds; Window dressing; Portfolio disclosure; Fund flows _____________________________________________________________ *Vikas Agarwal is from Georgia State University, Robinson College of Business, 35 Broad Street, Suite 1207, Atlanta GA 30303, USA. E-mail: vagarwal@gsu.edu. Tel: +1- 404-413-7326. Fax: +1-404-413-7312. Vikas Agarwal is also a Research Fellow at the Centre for Financial Research (CFR), University of Cologne. Gerald D. Gay is from Georgia State University, Robinson College of Business, 35 Broad Street, Suite 1203, Atlanta GA 30303, USA. E-mail: ggay@gsu.edu. Tel: +1-404-413-7321. Fax: +1-404- 413-7312. Leng Ling is from Georgia College & State University (GCSU), Bunting College of Business, Suite 414, Milledgeville, GA 31061, USA. E-mail: leng.ling@gcsu.edu Tel: +1-478-445-2587 Fax: 478-445-1535. Ling acknowledges research grant support from GCSU. We thank Ranadeb Chaudhuri, Mark Chen, Conrad Ciccotello, K.J. Martijn Cremers, Elroy Dimson, Jesse Ellis, Wayne Ferson, Jason Greene, Zhishan Guo, Zoran Ivkovic, Marcin Kacperczyk, Jayant Kale, Aneel Keswani, Omesh Kini, Bing Liang, Reza Mahani, Ernst Maug, David Musto, Tiago Pinheiro, Chip Ryan, Thomas Schneeweis, Clemens Sialm, Vijay Singal, Tao Shu, Daniel Urban, Qinghai Wang, and Chong Xiao for their helpful comments and constructive suggestions. We are grateful to the seminar participants at the Bank of Canada, Cass Business School, University of Alabama, University of Cambridge, University of Georgia, University of Mannheim, University of Massachusetts Amherst, and Wuhan University for their comments. We acknowledge the research assistance of Sujuan Ma, Jinfei Sheng, and Haibei Zhao. We also thank Linlin Ma and Yuehua Tang for providing data. Performance inconsistency in mutual funds: An investigation of window-dressing behavior ABSTRACT This paper develops two measures of performance inconsistency based on information derived from funds’ actual performance and their disclosed portfolio holdings. Using these measures, we show that funds with unskilled managers and poor performance are associated with greater inconsistency. Further, inconsistency exhibits seasonality and relates negatively to future performance. Together, this evidence suggests that inconsistency is driven by window dressing rather than stock selection. Finally, we characterize and provide empirical support for an equilibrium of window dressing in the presence of rational investors by examining their capital allocation decisions. 1 Performance inconsistency in mutual funds: An investigation of window-dressing behavior In addition to information contained in realized fund returns, there is growing evidence in the academic literature that investors use information based on disclosed portfolio holdings to assess managerial ability. 1 However, there can sometimes be conflict between these two sources of information. For example, a fund performing poorly may disclose disproportionately higher (lower) holdings in stocks that have done well (poorly) over the same period. On one hand, such conflict can be associated with portfolio rebalancing as a part of a ‘stock selection’ strategy (e.g., momentum trading) intended to increase fund value. On the other hand, the conflict can result from a manager altering or ‘distorting’ (see Moskowitz (2000)) his portfolio in an attempt to mislead investors about his true ability, a practice referred to as window dressing that can adversely affect fund value through unnecessary portfolio churning. To distinguish between the two motivations for performance inconsistency, window dressing and stock selection, we first address two research questions: (1) which fund characteristics are associated with performance inconsistency?; and (2) how does the inconsistency affect future fund performance? If fund characteristics such as low manager skill and poor recent performance are associated with greater inconsistency, then the motivation is more likely to be window dressing. Similarly, if funds with greater performance inconsistency exhibit lower future performance, then inconsistency is again more likely to be driven by window dressing. If answers to these questions support the window-dressing motivation, then it 1 See, for example, Grinblatt and Titman (1989, 1993), Grinblatt, Titman, and Wermers (1995), Daniel, Grinblatt, Titman, and Wermers (1997), Wermers (1999, 2000), Chen, Jegadeesh, and Wermers (2000), Gompers and Metrick (2001), Cohen, Coval, and Pastor (2005), Kacperczyk, Sialm, and Zheng (2005, 2008), Sias, Starks, and Titman (2006), Alexander, Cici, and Gibson (2007), Jiang, Yao, and Yu (2007), Kacperczyk and Seru (2007), Cremers and Petajisto (2009), Huang and Kale (2009), and Baker, Litov, Wachter, and Wurgler (2010). 2 is important to understand how window dressing can exist in equilibrium given its potential adverse effects. This leads us to our third research question: (3) how do investors react to managers’ window-dressing behavior in terms of altering their capital flows and, importantly, what characterizes the equilibrium of this behavior? We develop two measures of performance inconsistency to address these research questions. Our first measure is ‘Rank Gap’ that captures the inconsistency between a performance-based ranking of a fund and a ranking based on the proportions of winner stocks and loser stocks disclosed by the fund at quarter end. The underlying intuition is that, on average, a poorly performing fund should have a higher percentage of its assets invested in loser stocks and a lower percentage invested in winner stocks than that of a better performing fund. Thus, observing a poorly performing fund with a high percentage of disclosed holdings in winners and a low percentage in losers suggests greater performance inconsistency that could potentially be driven by window-dressing behavior. Since the Rank Gap measure is based on ranking a fund’s performance as well as its winner and loser proportions relative to other funds, it can be viewed as a relative measure of performance inconsistency. Our second measure is motivated by the work of Kacperczyk, Sialm, and Zheng (2008) (henceforth, KSZ), who compare a fund’s actual performance (i.e., returns realized by investors based on net asset values) with the performance of the fund’s prior quarter-end portfolio, assuming it to be held throughout the current quarter. They refer to the difference between the two performance figures as ‘return gap’ and attribute it to manager skill. Since we are interested in studying potential window-dressing behavior, instead of using the prior quarter-end portfolio, we use the current quarter-end portfolio and assume that a manager held it from the beginning of the current quarter. The intuition is that a manager upon observing winner and loser stocks 3 towards the quarter end will tilt portfolio holdings towards winner stocks and away from loser stocks to give investors a false impression of stock selection ability. Specifically, we compute the difference between the return imputed from the quarter-end portfolio (assuming that the manager held this same portfolio at the beginning of the quarter) and the fund’s actual quarterly return. We refer to this measure as ‘Backward Holding Return Gap’ (BHRG). We provide in the Appendix an example that shows how BHRG differs from the KSZ return gap measure, and how these two measures together can help distinguish window dressers from skilled and unskilled managers. In contrast to the Rank Gap measure, which is relative, the BHRG measure is absolute as it compares the performance of each fund’s reported holdings with the fund’s actual return. Our first hypothesis posits that if fund performance during the quarter and/or manager skill is negatively associated with performance inconsistency, then the inconsistency is more likely to be driven by window-dressing behavior rather than stock selection. We find results that are consistent with window dressing. Using the four-factor alpha of Carhart (1997) that adjusts for momentum trading, i.e., buying winners and selling losers, we find that performance inconsistency is negatively related to fund’s past performance and manager skill. These findings are also economically significant. For example, a one standard deviation decline in alpha is associated with an increase of approximately 6.6% and 18.6% in the average Rank Gap and BHRG measures, respectively. For manager skill, the corresponding increases are 1.4% and 20.6%, respectively. Interestingly, we also find that funds with higher expense ratios and greater portfolio turnover show higher inconsistency. Higher expense ratios imply greater benefits to funds if investors respond to window-dressed portfolios with higher flows. Greater turnover can result from the unnecessary trading of buying winners and selling losers around quarter ends. 4 To further discern whether performance inconsistency is driven by window dressing, we test for seasonality in inconsistency following the intuition that while momentum trading should be uniformly distributed over the year, window dressing may be more pronounced in December (Moskowitz (2000)). The literature on tournaments and the flow-performance relation (e.g., Brown, Harlow, and Starks (1996), Chevalier and Ellison (1997), Sirri and Tufano (1998), and Huang, Wei, and Yan (2007)) suggests that many investors evaluate funds on a calendar year basis, which may provide greater incentives to window dress in December. Also, window dressers may be able to disguise their behavior by selling losing stocks in December and thus pool themselves with tax-loss sellers. The findings from these seasonality tests further corroborate that performance inconsistency is driven by window dressing rather than momentum. Our second hypothesis relates to the association of performance inconsistency with future fund performance. A negative association would be consistent with window dressing as it is a costly and value-destroying exercise involving unnecessary portfolio churning around quarter ends resulting in excessive transaction costs. We find that future fund performance is negatively related to both measures of inconsistency (Rank Gap and BHRG). In terms of economic significance, a one standard deviation increase in the Rank Gap and BHRG measures is associated with a decline of 32.1% and 39.3%, respectively, in the average values of next quarter’s alpha. To investigate this further, each quarter we sort the funds into deciles using either Rank Gap or BHRG, and compute the mean values of the alphas, raw returns, and momentum betas for each decile. For each inconsistency measure, we observe that both future alphas and raw returns exhibit a monotonically decreasing pattern as we go from the lowest to the highest decile of inconsistency. In contrast, the momentum betas show a monotonically increasing pattern, which would predict, on average, increasing raw returns and not decreasing. 5 These findings further corroborate that window dressing, and not the momentum effect, is driving inconsistency. Despite some evidence in the mutual fund literature consistent with window-dressing behavior (see, for example, Lakonishok et al. (1991), Sias and Starks (1997), He, Ng, and Wang (2004), Ng and Wang (2004), and Meier and Schaumburg (2004)), there is limited understanding of the incentives for managers to engage in window dressing. 2 Such incentives can be garnered from analyzing investors’ reaction to managers’ window-dressing behavior in terms of looking at their capital allocation decisions. Given our earlier findings showing the adverse effect of window dressing on future fund performance, one would expect rational investors to punish such managers with reduced fund flows. This in turn leads to an interesting question: why do some managers nevertheless do it and bear the risks involved? In other words, how can we explain the window dressing phenomenon in equilibrium in the presence of rational investors? A critical feature of this equilibrium is the delay period afforded by SEC rules that allow portfolio holdings to be disclosed with a delay of up to 60 days following quarter end. This delay period affects investors’ interpretation of the inconsistency between a fund’s actual performance and its performance imputed from the disclosed portfolio holdings. If a window- dressing manager performs well during the delay period, then investors are less likely to attribute the inconsistency to window dressing and more likely to an improvement in the manager’s security selection strategy. As a result, subsequent to the delay period, investors may reward the window-dressing manager with incrementally higher flows than that justified by the fund’s 2 In addition to performance-based window dressing (e.g., buying winners and selling losers) that we study, the literature notes other forms of window dressing. Prior to reporting, managers may (1) decrease their holdings in high-risk securities to make their portfolios appear less risky (Musto (1997) and (1999), and Morey and O’Neal (2006)); (2) purchase stocks already held to drive up stock prices and thereby fund values, a practice known as “portfolio pumping”, “leaning for the tape”, or “marking up” (Carhart et al. (2002), and Agarwal, Daniel, and Naik (2011)); (3) invest in securities that deviate from their stated fund objectives and later sell them (Meier and Schaumburg (2004)); and (4) invest in stocks covered in the media (Solomon, Soltes, and Sosyura (2011)). 6 performance. In contrast, if the performance during the delay period is bad, then investors are more likely to attribute the inconsistency to window dressing and punish the manager with incrementally lower flows. Figure 1 illustrates the timeline of events related to the observance of performance and flows by investors to help understand the equilibrium of window dressing. [Insert Figure 1 here.] In essence, such an equilibrium suggests that window-dressing managers are taking a bet that will pay off if their performance during the delay period turns out to be good. Investors are more likely to believe that these managers have stock selection ability if they attribute the good fund performance to the disclosed high (low) proportion of assets invested in winning (losing) stocks. In this scenario, as the signals of managerial ability from both good performance over the delay period and a composition of portfolio holdings tilted towards winners reinforce each other, investors will reward such funds with higher flows. In contrast, if the manager experiences continued poor performance during the delay period, then investors receive conflicting signals and will suspect managers of window-dressing behavior and shun such funds by withdrawing or not investing capital. Our results are consistent with such an equilibrium. We find that conditional on good performance during the delay period, window dressers benefit from higher flows as compared to non-window dressers. In contrast, conditional on bad performance, window dressers incur a cost in terms of lower flows. Furthermore, we find that window dressers exhibit greater dispersion in flows across the two states (good and bad performance) than do non-window dressers. This supports the notion that window dressers are taking a risky bet on performance during the delay period where the payoffs are in terms of investor flows. This finding together with our earlier results showing that window dressers are typically unskilled and poor performers is consistent 7 with the literature documenting a positive association between career concerns and risk taking (see Khorana (1996), Brown, Harlow, and Starks (1996), and Chevalier and Ellison (1997)). In addition to contributing to the window-dressing literature, our paper builds on a broader literature that studies the effects of portfolio disclosure on the investment decisions of money managers (Musto (1997) and (1999)), the consequences of portfolio disclosure such as free riding and front running (Wermers (2001), Frank et al. (2004), Verbeek and Wang (2010), and Brown and Schwarz (2011)), the determinants of portfolio disclosure and its effect on performance and flows (Ge and Zheng (2006)), and the motivation behind institutions seeking confidentiality for their 13F filings (Agarwal et al. (2011) and Aragon, Hertzel, and Shi (2011)). We proceed as follows. Section I reviews the literature and develops testable hypotheses. Section II describes the data and the construction of the main variables including the two performance inconsistency measures. Section III analyzes the determinants of performance inconsistency. Section IV investigates the effect of performance inconsistency on future fund performance. Section V analyzes the effect of window dressing on future fund flows to explain the equilibrium of window dressing. Section VI concludes. I. Related Literature and Testable Hypotheses One strand of related literature studies the relation between the turn-of-the-year effect and window dressing by institutional investors. Earlier papers in this literature include Haugen and Lakonishok (1988) and Ritter and Chopra (1989) who argue that window dressing can potentially explain the January effect. Sias and Starks (1997), Poterba and Weisbenner (2001), and Chen and Singal (2004) attempt to disentangle tax-loss selling and window-dressing explanations for the turn-of-the-year effect and provide evidence in support of tax-loss selling. [...]... pattern in panel B Together, these findings provide support for hypothesis 1 that performance inconsistency is negatively related to manager skill and first two months’ performance during the quarter, and is thus likely to be driven by window -dressing behavior We also repeat our sorting analysis where we reverse the sorting order and first sort the funds into performance quintiles and then into managerial... by window dressing rather than momentum trading IV Performance inconsistency and future performance We next investigate our second hypothesis that performance inconsistency, if driven by window dressing, should be associated with lower future performance as it involves unnecessary portfolio turnover We first conduct single sorts of funds into deciles each quarter according to 24 values of Rank Gap and... proportion, and a high rank based on loser proportion Similarly, a poorly performing fund should have low ranks based on all three However, if a fund has say a low performance rank, but relatively high rankings of winner and loser proportions, it would indicate performance inconsistency We thus first compute performance inconsistency as PerformanceRank  WinnerRank  LoserRank , 2 where PerformanceRank is... compared to sorting by Rank Gap, and the spread of 0.26% is statistically insignificant (p-value =0.17) Higher performance inconsistency being associated with lower future performance supports hypothesis 2 that window dressing, and not momentum, is driving the inconsistency 25 Next, we examine the relation between performance inconsistency and future performance after controlling for manager skill We double... PerformanceRank is the rank of fund performance, WinnerRank is the rank of winner proportion, and LoserRank is the rank of loser proportion The theoretical range of this measure is [99, 99] To help interpret this measure as a probability measure (which should lie between 0 and 1), we then scale it to obtain our first performance inconsistency measure, Rank Gap: [(PerformanceRank  WinnerRank  LoserRank )+100]/200... and skill are 36.1561 and 42.6324, respectively, and significant at the 1% level In terms of economic significance, a one standard deviation increase in (a) alpha reduces the probability of performance inconsistency by 3.54% (39.8% of the implied probability of 8.89%); and (b) manager skill reduces the probability of inconsistency by 1.12% (12.6% of the implied probability of 8.89%).10 Using an indicator... bound of the Rank Gap measure is thus (0.005, 0.995) The higher is the Rank Gap measure, the greater is the performance inconsistency In panel A of Table I, we report summary statistics for the Rank Gap measure and observe that the mean (median) of this measure in our sample is 0.5 (0.4975) [Insert Table I here.] A.2 BHRG: Absolute measure of performance inconsistency Our second measure of performance inconsistency. .. alternative trading patterns and find evidence consistent with window dressing We contribute to the literature by first developing two measures of performance inconsistency to distinguish between window dressing and stock selection We posit that fund managers having low skill and achieving poor performance earlier during a quarter (e.g., during the first two months) are more likely to exhibit higher inconsistency. .. several interesting findings First, performance inconsistency is associated with managers who are less skilled and/or who perform poorly Second, we observe that performance inconsistency is more pronounced in December versus other months Third, we find that funds with greater performance inconsistency exhibit lower future performance Taken together, these findings support that window dressing is the... finding to the unnecessary trading of winners and losers with the intention to window dress 10 We compute the implied probability of performance inconsistency by keeping all the continuous independent variables at their mean values and the indicator load variable at 0 21 In addition to the fund characteristics included as independent variables in equation (2), there can potentially be others that influence . • L. Ling Performance inconsistency in mutual funds: An investigation of window -dressing behavior VIKAS AGARWAL GERALD D. GAY and . of rational investors by examining their capital allocation decisions. 1 Performance inconsistency in mutual funds: An investigation of window-dressing