The Performance of Emerging Hedge Fund Managers Rajesh K. Aggarwal and Philippe Jorion* This version: January 8, 2008 Draft * Aggarwal is with the Carlson School of Management, University of Minnesota. Jorion is with the Paul Merage School of Business, University of California at Irvine and Pacific Alternative Asset Management. The paper has benefited from the comments and suggestions of Jim Berens, Jane Buchan, Judy Posnikoff, Patricia Watters, and seminar participants at UC-Irvine. Correspondence can be addressed to: Philippe Jorion Rajesh K. Aggarwal Paul Merage School of Business Carlson School of Management University of California at Irvine University of Minnesota Irvine, CA 92697-3125 Minneapolis, MN 55455 (949) 824-5245, E-mail: [email protected] (612) 625-5679, Email: [email protected] © 2007 Aggarwal and Jorion The Performance of Emerging Hedge Fund Managers ABSTRACT This paper provides the first systematic analysis of performance patterns for emerging managers in the hedge fund industry. Emerging managers have particularly strong financial incentives to create investment performance and, because of their size, may be more nimble than established ones. Performance measurement, however, needs to control for the usual biases afflicting hedge fund databases. Backfill bias, in particular, is severe for this type of study. After adjusting for such biases and using a novel event time approach, we find strong evidence of outperformance during the first two to three years of existence. Controlling for size, each additional year of age decreases performance by 48 basis points, on average. Cross-sectionally, early performance by individual managers is quite persistent, with early strong performance lasting for up to five years. JEL Classifications: G11 (portfolio choice), G23 (private financial institutions), G32 (financial risk management) Keywords: hedge funds, emerging managers, incentives, performance evaluation 2 I. Introduction The hedge fund industry has grown very rapidly. Assets under management have increased from an estimated $39 billion in 1990 to more than $1,400 billion in 2006.1 Correspondingly, the number of managers has increased from 530 to more than 7,200. One immediate question with the large growth in the number of managers is whether all of these new managers are capable of generating superior performance. This paper provides the first systematic evidence on whether emerging hedge fund managers tend to outperform more established ones. We find that emerging managers tend to add value in their early years. This effect is slightly stronger for larger funds. Thereafter, performance tends to deteriorate. This is consistent with the implications of stronger incentive effects for emerging managers, but mainly for those that start up with a larger pool of capital. Controlling for size, each additional year of fund age decreases fund performance by 48 basis points, on average, which suggests that emerging funds, especially in the first two years of life, represent attractive investment opportunities. The growth of the hedge fund industry can be rationalized by the value added generated by hedge fund managers that we document. For example, over the period 1994 to 2006, the CSFB hedge fund index delivered an additional 6.8% annual return over cash.2 Put differently, this is the same performance as the S&P stock market index, but with half the volatility and very little systematic risk. These performance results are puzzling in view of the mutual fund literature, which finds that mutual funds generally fail to outperform their benchmarks even after adjusting for risk. Hedge funds, however, differ in a number of essential ways from mutual funds. They provide more flexible 1 According to the HFR (2007) survey, excluding funds of funds to avoid double-counting. 2 The CSFB hedge fund index, which in absolute terms returned 10.9% per annum over this period, is representative of all hedge funds and does not represent the returns on emerging hedge funds alone. For emerging hedge funds, see Table 1. 3 investment opportunities and are less regulated.3 Hedge fund managers also have a stronger financial motivation to perform because of the compensation structure typical of hedge funds: this includes not only a fixed annual management fee that is proportional to assets under management but also an incentive fee that is a fraction of the dollar profits. In addition, hedge fund managers often invest a large portion of their own wealth in the funds they manage. At the same time, there is a fair amount of interest in “emerging” managers, defined as newly-established managers. In this paper, we define emerging hedge fund managers as recently- established funds, using fund age or years of existence since inception, as the primary sorting criterion.4 We focus on emerging managers for several reasons. Incentive effects should be stronger for this class of hedge fund managers. The marginal utility of a given annual profit should be higher for managers with lower initial wealth; given that emerging managers should be on average younger than more established managers, profits can be expected to accrue over a longer lifetime. In addition, because of their size, they may be more nimble than established managers. Finally, emerging managers are much more likely to be open to investors than are established hedge funds, especially established funds with strong historical performance. So far, no academic paper has directly investigated the effect of fund age on hedge fund performance. Age sometimes appears as another factor explaining performance in mutual funds, with generally insignificant effects. Crucially, the age factor in hedge funds is subject to a very significant backfill bias or instant-history bias. This bias occurs because managers report their performance to the databases only voluntarily—there is no requirement that managers disclose performance. Typically, after inception, the fund’s performance is not made public during some 3 More flexible investment opportunities include the ability to short securities, to leverage the portfolio, to invest in derivatives, and generally to invest across a broader pool of assets. The lighter regulatory environment creates an ability to set performance fees, lockup periods, or other forms of managerial discretion. 4 incubation period. Upon good performance, the manager is more likely to make the performance public. If so, the manager starts reporting to the database current performance and backfills the past performance, and not even necessarily over the entire incubation period. Funds that collapse due to poor performance may never appear in the database. Our paper eliminates backfill bias by selecting a sample of funds with inception dates very close to the start dates in the database. We find that that the backfill bias would otherwise completely distort measures of early performance, imparting an upward bias of around 5% in the first three years. We also find that the common practice of arbitrarily dropping the first 12 or 24 months of the sample is insufficient to control for backfill bias. In addition, it may bias tests of persistence toward non-rejection because performance during the backfill period generally appears very high. Our paper provides evidence on whether emerging hedge fund managers tend to outperform more established ones. After eliminating backfill bias, we examine fund performance in “event time” where the event is the start of fund performance. Examining funds in event time is a more powerful and direct method to assess the relationship between age and performance. To see this, suppose that every year a large number of new funds start up, and that new or emerging funds outperform existing funds. Running pooled cross-sectional regressions of fund returns on indices or factors (even with time fixed effects) in calendar time would imply that hedge funds outperform on average. However, the outperformance is actually generated by the new funds, an effect which will be captured in event time but missed in calendar time. Our use of event time is novel in hedge fund research, and the event time approach is ideally suited for examining the performance of emerging hedge funds. Conventional event studies 4 Recently established funds are taken as a proxy for emerging managers. It is possible, however, that a recently established fund is run by a manager who has run other hedge funds. With this caveat, we use the terms emerging 5 typically examine short horizon reactions to news or events. More recently (and perhaps controversially), long horizon event studies have been used to examine differences in firm returns due to changes that cannot precisely be pinned down to the day. Our use of event time is long horizon in nature—we examine hedge fund performance over years—but we know precisely when the hedge fund starts reporting performance. We use event time to measure hedge fund aging, which is similar to a cohort analysis, while still allowing us to create portfolios of hedge funds. Using portfolios allows us to test hypotheses while automatically accounting for correlations in returns across funds. This is because the standard errors we report are based on portfolio returns. In contrast, pooled cross-sectional regressions of individual fund returns are usually misspecified due to cross-sectional correlations in fund returns. Our econometric approach yields robust evidence that emerging managers tend to add value in their early years. In addition, when we form portfolios of emerging funds, we find that early performance (up to five years) is persistent. Importantly, the persistence we find is present both for the best performing quintile and the worst performing quintile of hedge funds. This result is important, as earlier studies of performance persistence tend to find performance persistence amongst only the worst performing furnds. As hedge funds become more established (i.e., age) the performance persistence that we document fades away, along with the outperformance exhibited in the funds’ early years. In further tests, we perform a cohort analysis, where we track over time all funds that start within a given year. This analysis allows us to more precisely control for changes in fund size. One possibility is that past good performance may lead to inflows, which results in the deterioration of fund performance over time, as in Berk and Green (2004). Under these conditions, the deterioration in fund performance is actually due to changes in fund size, and not fund age. When we control for managers, new managers, and new funds interchangeably. 6 fund size, we continue to find that younger funds perform better and this performance deteriorates over time. This paper is structured as follows. We review the rationale for emerging managers and relevant literature in Section II. Section III then describes the data and empirical setup. Section IV discusses the results. Concluding comments are contained in Section V. II. The Rationale for Emerging Managers Emerging managers may be attractive for a number of reasons. The first set of arguments is related to incentive effects. There are good reasons to believe that incentive effects are particularly important for the hedge fund industry. Incentives should help sort managers by intrinsic skills. We would expect the best asset managers to migrate to the hedge fund industry. In addition, incentives should induce greater effort by managers, as predicted by agency theory.5 In the mutual fund industry, Massa and Patgiri (2007) compare the usual fixed management fee setup with arrangements where this fee decreases as a function of asset size. This concave function provides a negative incentive effect, which is found to be associated with worse performance, as predicted. In the hedge fund industry, Agarwal et al. (2007) find that greater managerial incentives, managerial ownership, and managerial discretion are associated with superior performance. In addition, these effects explain the empirical evidence of return persistence for hedge funds, while little persistence has been reported for mutual funds.6 5 See for instance Jensen and Meckling (1976). 6 Jagannathan et al (2007) find evidence of persistence in hedge fund returns over 3-year horizons. They also provide a review of the literature on persistence in hedge fund returns. Kosowski, Naik, and Teo (2007) report mild evidence of persistence using classical OLS alphas but much stronger evidence in a Bayesian analysis. Baquero et al. (2005) report persistence at the quarterly and annual horizons, using raw and style-adjusted returns. Aggarwal, Georgiev, and Pinato (2007) show performance persistence for time horizons ranging from six months to over two years. Carhart (1997) reports no evidence of persistence in mutual fund returns using abnormal returns defined by a 4-factor model. These conclusions are reinforced by Carhart et al. (2002), who deal with survivorship and look-ahead biases for mutual funds. 7 Relative to more established and older managers, incentive effects should be even more important for emerging managers because their initial wealth is smaller. The marginal utility of the same dollar amount of fees should progressively decrease as the manager gets richer. In addition, the benefits of high-powered incentive contracts carry over a longer period, since emerging managers are generally younger. So, emerging managers should put more effort into enhancing performance. In their starting years, managers may also be more focused on generating performance rather than spending time marketing to new investors. The second set of arguments for emerging managers is related to size. They generally manage a smaller asset pool than the typical fund. Goetzmann et al. (2003) argue that arbitrage returns may be limited, leading to diseconomies of scale. They report that, in contrast with the mutual fund industry, large hedge funds frequently prefer not to grow. Diseconomies of scale also underpin Berk and Green (2004)’s model that explains many regularities in the portfolio management industry that are widely regarded as anomalous. Managers with skill attract inflows, but diseconomies of scale erode performance. As a result, the performance of skilled managers disappears over time. Getmansky (2004) studies competition in the hedge fund industry and finds decreasing returns to scale. For mutual funds, however, the evidence is mixed. Grinblatt and Titman (1989) and Wermers (2000) find no significant difference across the net performance of small and large funds. Chen et al. (2004) report some evidence of a negative relationship between fund returns and size, but this is exclusively confined to funds that invest in small stocks, which tend to be illiquid. This is confirmed by Allen (2007), who reports no difference across size for institutional investors except for the small cap category, which is capacity-constrained and for which small funds perform better. Another set of arguments for emerging managers is that they may have newer ideas for trades, whose usefulness can fade away over time. New funds may be established to take advantage of new 8 markets or new financial instruments. Finally, irrespective of a performance advantage, emerging managers are usually open to new investors and as a result, represent practical investment opportunities in hedge funds. So far, no academic paper has directly investigated the effect of fund age on hedge fund performance.7 Age sometimes appears as another factor explaining performance in mutual funds, with generally insignificant effects. In addition, the age factor is subject to a very significant backfill bias or instant-history bias with hedge funds. This bias arises from the option to report performance or not, and if so, to backfill performance produced during an incubation period. Interestingly, Evans (2007) reports a substantial incubation bias for mutual funds which parallels the backfill bias in hedge funds. Apparently, mutual fund families seed new funds without initially making their performance public. After a while, the fund may acquire a ticker symbol from the NASD, thus becoming public. Evans (2007) defines a fund as incubated if the period between the ticker creation date and the fund inception date is greater than 12 months. He reports a difference in performance of 4.7% between incubated funds during their incubation period and an age-matched sample of non-incubated funds. Fung and Hsieh (2000) describe the distribution of this incubation period for hedge funds. The median period is about 12 months based on the TASS database from 1994 to 1998. Fung and Hsieh (2000) then adjust for this bias by dropping the first 12 months of all return series. The adjusted series has an average return of 8.9%, against a 10.3% return for the raw series, yielding a 7 Some industry studies purport to demonstrate that young funds perform better. For example, Howell (2001) claims that young funds outperform old funds by 970 basis points on average. This analysis, however, fails to control for backfill bias. Similarly, Jones (2007) claims that young funds (with age less than 2 years) outperform old funds (with age greater than 4 years) by 566 basis points. 9 bias estimate of 1.4% per annum.8 The common practice in hedge fund academic research has become to drop the first 12 or 24 months to control for backfill bias.9 This adjustment, however, is peculiar. For funds with no instant history, this discards the first year of performance, which is perfectly valid and very informative. Moreover, for the 50% of funds with instant-history longer than 12 months, this still preserves a backfill bias. Whether this biases the results of the empirical analysis depends on the research objective. Clearly, backfill bias is of first-order importance when evaluating the initial performance of emerging managers. A better method to control for backfill bias is to minimize the period between inception of the fund and the first date of entry into the database.10 Thus, we focus on the group of funds for which there is no (or very little) backfill bias. In addition, traditional performance evaluation of hedge funds can be subject to survivorship bias, which arises when dead funds are excluded from the analysis. Fung and Hsieh (2000) estimate this bias at around 3%. To evaluate the effect of age, it is crucial to control for backfill bias, which would otherwise make early returns look better. Survivorship bias works in the other direction, making longer returns look better. Our analysis controls for both backfill and survivorship biases. The age effect that is the focus of our study is also related to the literature on career concerns of portfolio managers. For mutual funds, Chevalier and Ellison (1999) indicate that termination is more sensitive to performance for younger managers. Combined with the incentive structure in this industry, they argue that this should lead to less risk taking in younger managers. This is confirmed by their data. Given the vastly different incentives schemes, it is not clear whether these results should carry over to the hedge fund industry, however. Boyson (2005) 8 Malkiel and Saha (2005) also report estimates of this backfill bias over 1994 to 2003. 9 Kosowski, Naik, and Teo (2007) combine the TASS, HFR, CISDM, and MSCI database, adjusting for backfill bias by dropping the first 12 months of every fund. 10 Such information is available from the TASS and HFR databases. 1 0