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Why has the aggregate level of hedge fund alpha (risk-adjusted return) decreased over the last decade? By studying the distribution of individual hedge fund alphas, we find that the large right tail (funds with positive alphas) that was once present has shrunk over time, while the left tail (funds with negative alphas) has remained unchanged. Thus, the decrease in average alpha is not due to an increasing percentage of funds with unskilled managers and negative alphas, as suggested by the hedge fund bubble hypothesis. Instead, it is due to a decrease in the proportion of funds capable of producing large positive alphas. Our evidence is consistent with the prediction of the capacity constraint hypothesis. Using quantile regression and counter-factual density analysis, we show that a change in fund characteristics combined with a change in market conditions contributes to the decrease in the proportion of funds with positive alphas. Furthermore, we find that fund-level flow has a positive (negative) impact on a fund's future performance for smaller (larger) funds, while strategy-level flow (flow into the strategy to which a fund belongs) always has a negative impact on the fund's future performance. Our results suggest that the economic reasons for capacity constraints arise both from the "unscalability" of managers' abilities and from the limited profitable opportunities in the market.

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... These findings are in line with other recent studies Fung et al., 2008). The downward trends in hedge fund returns have been partly attributed to capacity constraints in hedge fund allocation decisions Zhong, 2008). The significant increase in capital inflows, predominantly into highly performing (high alpha) hedge funds, during the last two decades is seen to have driven excess hedge fund (net-of-fee) returns down to nearly zero (Hedge Fund Research, 2011;Ben-David, Franzoni, & Moussawi, 2012). ...

... In particular, hedge fund styles like equity market neutral, fixed income arbitrage and convertible have actually delivered negative alpha over the past few years. Drawing on empirical findings of recent studies by Naik et al. (2007), Zhong (2008) and Fung et al. (2008) we conjecture that capital inflows and industry regulation lead to lower alpha, and lower alpha persistence. In the past, there were probably a lot of inefficiencies in the markets that hedge funds could identify. ...

... Empirical evidence has indicated that the arbitrage strategies, including convertible arbitrage, fixed income arbitrage and merger arbitrage, have suffered severe losses, contrary to macro strategies that have managed to deliver superior gains. Our empirical conclusions about the declined alpha of hedge fund strategies are in line with Naik et al. (2007), Zhong (2008) and Fung et al. (2008). The inadequacy of certain hedge fund strategies to produce attractive performance has inevitably exerted a negative impact on the constructed hedge fund portfolios. ...

... In line with many recent studies (Zhong, 2008;Sandvik et al, 2011), our empirical work shows that the α's related to hedge fund strategies tend to decrease through time. However, they remain positive, suggesting that hedge funds continue to deliver positive absolute returns. ...

... The α puzzle thus tends to recede through time, at least over our sample period. This result is shared with many recent studies (for example, Zhong, 2008;Sandvik et al, 2011;Cay and Liang, 2012). It is attributed to decreasing returns to scale, increased competition in the hedge fund sector and the sheer growth of assets under management in this sector. ...

Using an updated database that extends after the subprime crisis, we revisit the asymmetries of hedge fund behavior in recession compared with economic expansion. In this respect, we study the time-varying α’s and β’s associated with strategy returns using an innovative framework based on the Kalman filter and the multivariate GARCH. We find that hedge fund managers reduce drastically their risk exposure during financial crises while their behavior is much smoother in normal times. We also find that hedge funds continue to provide good prospects for investors in terms of risk-adjusted returns. Actually, the procyclicality of hedge fund strategies’ returns seems to decrease through time. Moreover, the strategies’ behavior in terms of α and β tends to become more heterogeneous in times of crisis. The strategy exposure to adverse shocks seems to recede even after accounting for the subprime crisis. Finally, many hedge fund strategies benefit from an increase in the volatility of stock market returns. Hedge fund strategies may thus constitute a way to offset the lower expected returns observed in the conventional financial markets and may contribute to portfolio diversification.

... Moreover, when hedge funds are traded on Hedgebay, they are closed to new investments and withdrawals -but for a shorter duration than closed-end mutual funds, which only rarely accept additional capital after their initial establishment by means of rights issues (see Khorana, Wahal and Zenner (2002)), and do not normally (apart from distributions or liquidations) repatriate capital to investors over their lifetimes. 6 Finally, the investors in hedge 4 For evidence on hedge fund capacity constraints see Naik, Ramadorai and Stromqvist (2007), Fung, Hsieh, Naik and Ramadorai (2008), Zhong (2008), Teo (2009) and Ramadorai (2009). 5 See "How hedge funds are bought and sold online", The Economist, August 4, 2005; and "All locked-up", The Economist, August 2, 2007. ...

... Both these variables are measured as (time-varying) ranks relative to all other funds in the universe to avoid concerns of non-stationarity, and lagged one month to avoid any mechanical association. Fund size is employed on account of the extensive evidence on capacity constraints in hedge fund strategies, which shows that larger hedge funds, or hedge funds which have experienced high capital ‡ows in the past have lower expected future alphas (see Fung, Hsieh, Naik and Ramadorai (2008), Zhong (2008) and Teo (2009) for hedge funds and Pollet and Wilson (2008) among others for mutual funds). Fund age is also employed as a performance measure. ...

Employing data from a new secondary market for hedge funds, this paper documents the existence of a closed-hedge fund premium, analogous to the closed-end mutual fund premium which has been extensively studied in the literature. Over the past decade, the two premia comove with one another at high and low frequencies, which is surprising given the numerous differences between the two markets. Rational theories put forward to explain the closed-end mutual fund premium are strongly supported as explanations for the variation in closed-hedge fund premia. These results are robust to correction for potential selection bias.

... Third, good past performance generates money inflows and growth in assets under management, which leads to an erosion of fund performance over time provided there are diseconomies of scale (Berk and Green, 2004;Goetzmann et al., 2003;Pastor et al., 2015;Zhong, 2008). Getmansky et al. (2004) study competition in the hedge fund industry and confirm decreasing returns to scale. ...

... In line with the existing literature, we are able to identify a positive alpha for all strategies in the time series and in the cross-section. However, our analysis challenges the conclusion of some recent research on a decreasing alpha over time (e.g., Fung et al., 2008; Zhong, 2008) and on capacity constraints in the hedge fund industry (e.g., Naik et al., 2007; Fung et al., 2008). The amount of capital invested in the hedge fund industry increased significantly during the period 1994 to 2008. 1 An expected consequence of this development is a decrease in hedge fund alpha. ...

This paper investigates the alpha generation of the hedge fund industry based on a recent sample compiled from the Lipper/TASS database covering the time period from January 1994 to September 2008. We find a positive average hedge fund alpha in the cross-section for the majority of strategies and a positive and significant alpha for roughly half of all funds. Moreover, the alpha of three-quarter of the strategy indices is positive and significant in the time series. A comparison of a factor model in which the risk factors are selected based on a stepwise regression approach and the widely used factor model proposed by Fung and Hsieh (2004) reveals that the estimated alpha is robust with respect to the choice of the factor model. In contrast to prior research, we find no evidence of a decreasing hedge fund alpha over time. Moreover, based on our sample, we cannot confirm prior evidence pointing to capacity constraints in the hedge fund industry. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1532742

... For example, while finding that some hedge funds have delivered positive risk-adjusted performance, Fung et al. (2008) find that hedge fund investor flows chase both past hedge fund returns and past hedge fund alphas. The future performance of highperforming hedge funds that receive these inflows suffers as a consequence, roughly consistent with the assumptions of the Berk and Green (2004) model (also see Zhong, 2008;Teo, 2008). ...

IntroductionEmpirical Work on Institutional InvestorsThe Returns of Institutional Investment Managers: Mutual FundsThe Returns of Institutional Investment Managers: Hedge FundsThe Holdings and Trades of Institutional Investment Managers: Low Frequency DataThe Holdings and Trades of Institutional Investment Managers: Higher Frequency DataCapital Flows to Institutional InvestorsDo Institutional Investors Always Behave Responsibly?Summary and Conclusions
Discussion QuestionsAbout the Author

... The robustness tests show that time-varying exposure to the emerging markets factor explains part but not all of the excess returns of the managerial skills strategies. In an attempt to more accurately assess hedge fund performance, recent papers have increasingly started to apply statistical procedures for the factor selection, mostly a forward stepwise regression approach (e.g., Agarwal and Naik, 2004; Titman and Tiu, 2011; Zhong, 2008; Ammann et al., 2011a Ammann et al., , 2011b). These papers show that, as expected, the explanatory power of factor models that select the risk factors based on stepwise regressions exhibit an increased explanatory power but a lower alpha as compared to the FH model. ...

There is still no consensus regarding a generally accepted factor model to assess risk-adjusted hedge fund performance. In this paper, we compare three alternative factor models: the widely used Fung and Hsieh (2004) seven-factor model, a recently proposed extension to an eight-factor model, and a model that selects the relevant risk factors based on a forward stepwise regression approach. Over a fairly long time period from 1994 to 2009, the differences in alphas resulting from the three alternative factor models are small. However, during crisis periods, such as the recent credit crisis, we find a substantial difference in alphas resulting from the Fung and Hsieh (2004) seven-factor model as compared to the other two models. The emerging markets factor, which is included in the eight-factor model and is chosen by the stepwise-based model for 7 out of 11 hedge fund strategies, seems to capture a large part of hedge fund return volatility during crisis periods. Both the stepwise and the eight-factor model generate qualitatively similar results even on the strategy level. Unlike the stepwise-based factor model, the eight-factor model uses the same set of risk factors for all hedge fund strategies. Given its much easier implementation, the eight-factor model seems to be a good choice for a broadly used factor model and a suitable successor for the widely used seven- factor model.

... FHNR's conclusions are similar to those reached by Berk and Green (2004) vis-à-vis actively managed mutual funds. Moreover, Zhong (2008) found that, on average, the alpha of hedge funds has declined; Zhong attributed the decline in aggregate hedge fund alphas to capacity constraints, which are caused by the nonscalability of managers' abilities and by limited profitable opportunities in the market. ...

In this study, we examine the evolution of the arbitrage spread between 1990 and 2007 and find that since 2002 the arbitrage spread has declined by over 400 basis points ("bps"). This decline is both economically and statistically significant. The decline in arbitrage spread corresponds with the decline in aggregate returns of M&A hedge funds as well as increased inflows into M&A hedge funds. We explore three possible explanations for the decline in arbitrage spread. Our study finds that a part of the decline in arbitrage spread may be explained by increased trading in the targets' stock subsequent to the merger announcement, reduced transaction costs, and changes in risk related to merger arbitrage. Our findings suggest some of the decline in arbitrage spread is likely to be permanent and thus investors seeking to invest in M&A hedge funds should focus on returns of the prospective funds since 2002 rather than returns over a longer period of time.

... Studies focusing on longer term hedge fund performance find hedge funds' alphas to fade out over time and, in aggregate, hedge funds do not anymore deliver the extreme outperformance they used to. Interestingly, this fact is due to a decrease in the number of funds producing large positive alphas rather than to an increase in the funds producing large negative alphas, see e.g. Zhong (2008). This trend seems to be consistent with the theoretical model proposed by Berk and Green (2004). ...

We propose a rational model of the behavior of hedge fund managers and investors that explains the variations of fees charged by hedge funds. Our work adapts the model of Berk and Green (2004) to the peculiarities of hedge fund remuneration schemes, in particular, to the fact that the fees paid depend on the timing of the investment and that remuneration is not linearly related to size. Flows rationally respond to expected abnormal returns. Managers modify their fees in order to maximize their income by capturing all the abnormal performance they generate. The predictions of our model are consistent with findings of other studies and are confirmed by our analysis of a unique data-set of fee revisions. We show that the marginal abnormal return is not significantly different from zero after fee increases. Investors respond by stopping to allocate to the funds that raise their fees. As a consequence, the remuneration of hedge fund managers remains constant after fee changes. All in all, our results are consistent with rational self-interested behavior of managers and investors.

... decline in arbitrage spread is likely to be permanent. 1 Meanwhile, the hedge fund literature also provides evidence that hedge funds have witnessed decreased hedge fund alpha over the past decade. For instance, Fung et al. (2007) and Naik et al. (2007) document that the overall level of hedge fund alpha has been in decline through the past decade. Zhong (2008) argues that this decline in hedge fund alpha is consistent with hedge fund capacity constraint. The economic reasons for capacity constraints can arise from the limited profitable opportunities in the market. ...

This paper examines the profitability of option-based merger arbitrage. We design a simple arbitrage strategy using stock options to examine merger arbitrage profitability from 1996 to 2008. This strategy longs target call and acquiror put options simultaneously. We show that option-based arbitrage strategy is a lot more profitable than stock-based arbitrage strategy. Option arbitrage grows $1 invested in merger deals in Jan 1996 into more than $17 by December 2008. In comparison, stock arbitrage grows $1 into approximately $7 over the same period. We also show that both strategies generate significant arbitrage portfolio returns that are robust to controls of traditional asset pricing factors.

... Third, good past performance generates money inflows and growth in assets under management, which leads to an erosion of fund performance over time provided there are diseconomies of scale (Berk and Green, 2004;Goetzmann et al., 2003;Pastor et al., 2015;Zhong, 2008). Getmansky et al. (2004) study competition in the hedge fund industry and confirm decreasing returns to scale. ...

Crypto Funds (CFs) represent a novel investor type in entrepreneurial finance. CFs intermediate Decentralized Finance (DeFi) markets by pooling contributions from crowd-investors and investing in tokenized startups, combining sophisticated venture-and hedge-style investment strategies. We compile a unique dataset combining token-based crowdfunding (or Initial Coin Offerings, ICOs) data with proprietary performance data of CFs. CF-backed startup ventures obtain higher ICO valuations, outperform their peers in the long run, and benefit from token price appreciation around CF investment disclosure in the secondary market. Moreover, CFs beat the market by roughly 2.5% per month. Their outperformance is persistent, suggesting that CFs deliver abnormal returns because of skill, rather than luck. These performance effects for CFs and CF-backed startups are driven by a fund's investor network centrality. Overall, our study paves the way for research on what some refer to as the "crypto fund revolution" in entrepreneurial finance.

... Fung et al. (2008) find that hedge fund alphas decrease due to capacity constraints. Zhong (2008) French (2008) also has similar limitations in the algorithm. Agarwal et al. (2009b) provide a comprehensive annual algorithm of incentive fees, gross returns and managerial incentive measures, which takes into account capital flows, high-water mark and hurdle rate provisions of individual investors. ...

... Overcapacity of the market is often blamed for diminishing performance in the hedge fund industry. Zhong (2008), and Naik, Ramadorai and Stromqvist (2007) we would expect to observe skilled managers more frequently underperforming unskilled 115 counterparts and conversely we would expect to observe unskilled managers more frequently outperforming skilled counterparts. ...

... Подобный анализ проводился в 2008 г. в работе Zhong «Why Does Hedge Fund Alpha Decrease over Time? Evidence from Individual Hedge Funds» [7] 6 , хотя в целом тот период характеризовался отличными результатами хеджфондов. ...

В работе исследуется вопросы выбора инвестиционных стратегий, соответствующих различным стадиям развития мировой экономики, применимых в условиях российской экономики.Основой для исследования является факт смены растущего тренда на понижательный, сопровождающийся высокой волатильностью. В таких условиях становится актуальным выбор инвестиционной стратегии, нацеленной на получение <альфы> от правильного распределения финансовых активов, а не <беты> от роста котировок всего рынка рискованных активов.В работе показано, что эффективность стратегий глобальных хеджфондов падает от кризиса к кризису. На российском же рынке остаются привлекательными стратегии игры на волатильности (CTA), особые ситуации (event driven). При этом эффективность операций на рынке облигаций стремительно падает по мере утилизации средств валютных РЕПО ЦБ РФРезультаты исследования примененимы в сфере управления активами крупных частных (family office) и институциональных инвесторов (SWF, Pension Funds, Insurance), которые по своему мандату могут вкладывать средства в хеджфонды или имеют внутренние подразделения, инвестирующие по стратегиям хеджфондов. Практический вывод работы состоит в том, что не стоит платить высокие комиссионные «2/20» - хеджфонды как класс перестали показывать адекватную им доходность и защиту от рыночных рисков. Поэтому управляющим крупными институциональными или частными портфелями следует уменьшить аллокацию на этот тип активов и/или модифицировать свои методы отбора фондов, которые бы могли устойчиво зарабатывать <альфу>.

... There is evidence on differences in the performance between large and small hedge funds, with small hedge funds outperforming. For instance, Zhong (2008) find that the impact of capital inflows on individual performance is positive for small hedge funds but negative for large ones. Getmansky et al. (2019) find that smaller hedge funds tend to set less restrictions on investors due to stronger desire of scaling up. ...

Analyzing trading of hedge funds facing substantial outflows, we find that hedge funds that "trade-against-the-flow" display significant stock picking skills. Stocks purchased by hedge funds facing large outflows deliver positive ex-post abnormal returns, which are larger than those of stocks purchased upon inflows. Such "revealed under pressure" stock-picking skills are associated with hedge funds that are more dependent on management fee income and more prone to sudden outflows due to less stringent share restrictions.

... There is evidence on differences in the performance between large and small hedge funds, with small hedge funds outperforming. For instance, Zhong (2008) find that the impact of capital inflows on individual performance is positive for small hedge funds but negative for large ones. ...

Analyzing trading of hedge funds facing substantial outflows, we find that hedge funds that "trade against the flow" display significant stock picking skills. Stocks purchased by hedge funds facing large outflows deliver positive ex-post abnormal returns, which are larger than those of stocks purchased upon inflows. Such "revealed under pressure" stock-picking skills are associated with hedge funds that are more dependent on management fee income and more prone to sudden outflows due to less stringent share restrictions.

... Third, good past performance generates money inflows and growth in assets under management, which leads to an erosion of fund performance over time provided there are diseconomies of scale (Berk and Green, 2004;Goetzmann et al., 2003;Pastor et al., 2015;Zhong, 2008). Getmansky et al. (2004) study competition in the hedge fund industry and confirm decreasing returns to scale. ...

Crypto Funds (CFs) represent a novel investor type in entrepreneurial finance. CFs intermediate Decentralized Finance (DeFi) markets by pooling contributions from crowd-investors and investing in tokenized startups, combining sophisticated venture-and hedge-style investment strategies. We compile a unique dataset combining token-based crowdfunding (or Initial Coin Offerings, ICOs) data with proprietary performance data of CFs. CF-backed startup ventures obtain higher ICO valuations, outperform their peers in the long run, and benefit from token price appreciation around CF investment disclosure in the secondary market. Moreover, CFs beat the market by roughly 2.5% per month. Their outperformance is persistent, suggesting that CFs deliver abnormal returns because of skill, rather than luck. These performance effects for CFs and CF-backed startups are driven by a fund's investor network centrality. Overall, our study paves the way for research on what some refer to as the "crypto fund revolution" in entrepreneurial finance.

The main purpose of this paper is to investigate if hedge funds create abnormal risk-adjustedreturns, both during bull and bear markets. The model applied is an extended multi-factor model. Thedataset consists of hedge fund return series with data from a fifteen-year period ranging from 1994 to2009. The whole set, as well as bull and bear sub periods, have been analyzed. We apply a slightlydifferent model from previous studies and we also, more importantly, use a more comprehensivedatabase. Analyzing data until February 2009, we are able to include the recent financial crisis in ourstudy. A limited amount of the hedge fund literature distinguishes between performance during bullmarkets and bear markets. We find that most hedge fund strategies reduce their exposure to the equitymarkets during adverse market conditions, and invest more in commodities. The inclusion of GlobalMacro and Managed Futures funds into an investor's portfolio offers a good hedge for bear marketconditions.

Institutional fund managers, fund of fund managers, high net-worth individuals and others invest billions with alternative asset managers. These managers charge investors fees to manage their money. These fees should align the interests of managers and investors. We argue that the current fees fail in this regard. In particular, we find that by growing their assets under management, managers increase their overall revenue via their management fees but, due to capacity constraints, decrease the returns to their investors. We suggest increasing contracting flexibility to resolve this conflict of interest.

We analyze the determinants of hedge fund management and incentive fees in a large consolidated hedge fund dataset. We detect time-series variation in fees by concentrating our attention on fund launches, and conditioning fees at launch on fund family characteristics. Larger and better performing fund families launch high fee funds. Funds with high management fees at launch do not perform any differently from low management fee funds, though funds with high incentive fees marginally outperform. Our results are robust to the use of an interval regression technique to uncover the underlying continuous distribution of fees from the discrete reported fees.

Employing a new dataset of over 9,000 expressed demands for over 700 hedge funds from a secondary market for hedge funds, this paper finds evidence suggesting that hedge fund investors rationally anticipate future hedge fund performance. Both buy and sell indications of interest arrive following periods of fund outperformance. Buy (sell) indications have some forecasting power for increases (decreases) in hedge fund performance, over and above other well-known forecasting variables. This information in investor demand co-exists with the presence of capacity constraints in hedge fund returns, confirming two main assumptions of Berk and Green (2004).

The returns of hedge fund investors depend not only on the returns of the funds they hold but also on the timing and magnitude of their capital flows in and out of these funds. We use dollar-weighted returns (a form of Internal Rate of Return (IRR)) to assess the properties of actual investor returns on hedge funds and compare them to buy-and-hold fund returns. Our main finding is that annualized dollar-weighted returns are on the magnitude of 3% to 7% lower than corresponding buy-and-hold fund returns. Using factor models of risk and the estimated dollar-weighted performance gap, we find that the real alpha of hedge fund investors is close to zero. In absolute terms, dollar-weighted returns are reliably lower than the return on the Standard & Poor's (S&P) 500 index, and are only marginally higher than the risk-free rate as of the end of 2008. The combined impression from these results is that the return experience of hedge fund investors is much worse than previously thought.

This paper analyzes the life cycles of hedge funds. Using the Lipper TASS database it provides category and fund specific factors that affect the survival probability of hedge funds. The findings show that in general, investors chasing individual fund performance, thus increasing fund flows, decrease probabilities of hedge funds liquidating. However, if investors chase a category of hedge funds that has performed well (favorably positioned), then the probability of hedge funds liquidating in this category increases. We interpret this finding as a result of competition among hedge funds in a category. As competition increases, marginal funds are more likely to be liquidated than funds that deliver superior risk-adjusted returns. We also find that there is a concave relationship between performance and lagged assets under management. The implication of this study is that an optimal asset size can be obtained by balancing out the effects of past returns, fund flows, competition, market impact, and favorable category positioning that are modeled in the paper. Hedge funds in capacity constrained and illiquid categories are subject to high market impact, have limited investment opportunities, and are likely to exhibit an optimal size behavior.

Since hedge funds specify significant lock-up periods, we investigate persistence in the performance of hedge funds using a multi-period framework in which the likelihood of observing persistence by chance is lower than in the traditional two-period framework. Under the null hypothesis of no manager skill (no persistence), the theoretical distribution of observing wins or losses follows a binormial distribution. We test this hypothesis using the traditional two-period framework and compare the findings with the results obtained using our multi-period framework. We examine whether persistence is sensitive to the length of return measurement intervals by using quarterly, half-yearly and yearly returns. We find maximum persistence at the quarterly horizon indicating that presistence among hedge fund managers is short term in nature.

"Hedge funds have generated significant absolute returns (alpha) in the decade between 1995 and 2004. However, the level of alpha has declined substantially over this period. We investigate whether capacity constraints at the level of hedge fund strategies have been responsible for this decline. For four out of eight hedge fund strategies, capital inflows have statistically preceded negative movements in alpha, consistent with this hypothesis. We also find evidence that hedge fund fees have increased over the same period. Our results provide support for the""Berk and Green (2004)""rational model of active portfolio management." Copyright 2007 The Authors Journal compilation (c) 2007 Blackwell Publishing Ltd.

The authors examine the performance of the off-shore hedge fund industry over the period 1989 through 1995 using a database that includes both defunct and currently operating funds. The industry is characterized by high attrition rates of funds, low covariance with the U.S. stock market, evidence consistent with positive risk-adjusted returns over the time, and little evidence of differential manager skill. Copyright 1999 by University of Chicago Press.

This article characterizes the systematic risk exposures of hedge funds using buy-and-hold and option-based strategies. Our
results show that a large number of equity-oriented hedge fund strategies exhibit payoffs resembling a short position in a
put option on the market index and therefore bear significant left-tail risk, risk that is ignored by the commonly used mean-variance
framework. Using a mean-conditional value-at-risk framework, we demonstrate the extent to which the mean-variance framework
underestimates the tail risk. Finally, working with the systematic risk exposures of hedge funds, we show that their recent
performance appears significantly better than their long-run performance.

We use a comprehensive data set of funds-of-funds to investigate performance, risk, and capital formation in the hedge fund industry from 1995 to 2004. While the average fund-of-funds delivers alpha only in the period between October 1998 and March 2000, a subset of funds-of-funds consistently delivers alpha. The alpha-producing funds are not as likely to liquidate as those that do not deliver alpha, and experience far greater and steadier capital inflows than their less fortunate counterparts. These capital inflows attenuate the ability of the alpha producers to continue to deliver alpha in the future. Copyright (c) 2008 The American Finance Association.

This paper provides evidence that the decline in the real value of the minimum wage and in the rate of unionization account for a significant share of the increase in wage inequality in the United States between 1979 and 1988. The role of the minimum wage is particularly important for women, while deunionization has the largest impact on men. The authors develop a semiparametric procedure that applies kernel density methods to appropriately weighted samples. The procedure provides a visually clear representation of where in the density of wages institutional and labor market forces exert the greatest impact. Copyright 1996 by The Econometric Society.

We present a new method for data‐based selection of the bandwidth in kernel density estimation which has excellent properties. It improves on a recent procedure of Park and Marron (which itself is a good method) in various ways. First, the new method has superior theoretical performance; second, it also has a computational advantage; third, the new method has reliably good performance for smooth densities in simulations, performance that is second to none in the existing literature. These methods are based on choosing the bandwidth to (approximately) minimize good quality estimates of the mean integrated squared error. The key to the success of the current procedure is the reintroduction of a non‐stochastic term which was previously omitted together with use of the bandwidth to reduce bias in estimation without inflating variance.

A simple minimization problem yielding the ordinary sample quantiles in the location model is shown to generalize naturally to the linear model generating a new class of statistics we term "regression quantiles." The estimator which minimizes the sum of absolute residuals is an important special case. Some equivariance properties and the joint aymptotic distribution of regression quantiles are established. These results permit a natural generalization to the linear model of certain well-known robust estimators of location. Estimators are suggested, which have comparable efficiency to least squares for Gaussian linear models while substantially out-performing the least-squares estimator over a wide class of non-Gaussian error distributions.

Abstract This paper studies the risk in fixed-income hedge fund styles. Principal component analysis is applied to groups of fixed-income hedge funds to extract common,sources of risk and return. These common sources of risk are related to market risk factors, such as changes in interest rate spreads and options on interest rate spreads. We call these assetbased style factors (“ABS”). The paper finds that fixed-income hedge funds tend to be exposed to a common,ABS factor: credit spreads. Hedge fund strategies came under intense scrutiny in the wake of the stressful market events surrounding the collapse of Long-Term Capital Management,(LTCM). Several studies have been sponsored by regulatory agencies of financial markets: the President’s Working Group on Financial Markets [1999], and Bank for International Settlements [1999a, b, and c]. In addition to the macro question as to whether hedge funds have a destabilizing influence on markets, these studies directed much of their attention to a particular type of strategy used by fixed-income hedge funds: Convergence Trading. Just what are the risk characteristics that caught the attention of financial regulators and how do they differ from other hedge fund strategies? Understanding hedge fund risk is a non-trivial task. Information on hedge funds is hard to come by. As private investment vehicles, hedge funds ,are exempt from the

Following a review of the data and methodological difficulties in applying conventional models used for traditional asset class indexes to hedge funds, this article argues against the conventional approach. Instead, in an extension of previous work on asset-based style (ABS) factors, the article proposes a model of hedge fund returns that is similar to models based on arbitrage pricing theory, with dynamic risk-factor coefficients. For diversified hedge fund portfolios (as proxied by indexes of hedge funds and funds of hedge funds), the seven ABS factors can explain up to 80 percent of monthly return variations. Because ABS factors are directly observable from market prices, this model provides a standardized framework for identifying differences among major hedge fund indexes that is free of the biases inherent in hedge fund databases.

This paper analyzes 4,750 mergers from 1963 to 1998 to characterize the risk and return in risk arbitrage. Results indicate that risk arbitrage returns are positively correlated with market returns in severely depreciating markets but uncorrelated with market returns in flat and appreciating markets. This suggests that returns to risk arbitrage are similar to those obtained from selling uncovered index put options. Using a contingent claims analysis that controls for the nonlinear relationship with market returns, and after controlling for transaction costs, we find that risk arbitrage generates excess returns of four percent per year.

Using a comprehensive data set of funds-of-hedge funds, we extend the results of Fung et al. (J. Finance 63:1777–1803, 2008) (FHNR) with an augmented version of the Fung and Hsieh (Financ. Anal. J. 60:65–80, 2004a; J. Empir. Finance 18:547–569, 2004b) model to document performance characteristics from January 2005 to December 2010. We find that our sample period is divided into three distinct subperiods: January 2005 to June 2007 (pre-subprime crisis); July 2007 to March 2009; and April 2009 to December 2010 (post-credit crunch) during which the average fund of hedge funds delivered positive alpha only in the first subperiod. We divide the funds of hedge funds sample into those who have alpha and the rest, which we call beta-only. The empirical results show a dramatic decline in the population of alpha producing funds of hedge funds post 2008 compared to the FHNR findings. When we repeat our analysis with a synthetic hedge fund index replicator, we find qualitatively similar results.

Using a robust bootstrap procedure, we find that top hedge fund performance cannot be explained by luck, and hedge fund performance persists at annual horizons. Moreover, we show that Bayesian measures, which help overcome the short-sample problem inherent in hedge fund returns, lead to superior performance predictability. Sorting on Bayesian alphas, relative to OLS alphas, yields a 5.5% per year increase in the alpha of the spread between the top and bottom hedge fund deciles. Our results are robust and relevant to investors as they are neither confined to small funds, nor driven by incubation bias, backfill bias, or serial correlation.

This paper presents evidence on the relation between hedge fund returns and restrictions imposed by funds that limit the liquidity of fund investors. The excess returns of funds with lockup restrictions are approximately 4–7% per year higher than those of nonlockup funds. The average alpha of all funds is negative or insignificant after controlling for lockups and other share restrictions. Also, a negative relation is found between share restrictions and the liquidity of the fund's portfolio. This suggests that share restrictions allow funds to efficiently manage illiquid assets, and these benefits are captured by investors as a share illiquidity premium.

This paper presents a parameter covariance matrix estimator which is consistent even when the disturbances of a linear regression model are heteroskedastic. This estimator does not depend on a formal model of the structure of the heteroskedasticity. By comparing the elements of the new estimator to those of the usual covariance estimator, one obtains a direct test for heteroskedasticity, since in the absence of heteroskedasticity, the two estimators will be approximately equal, but will generally diverge otherwise. The test has an appealing least squares interpretation.

This paper investigates the returns on British collectible postage stamps over the very long run, based on stamp catalogue prices. Between 1900 and 2008, we find an annualized return on stamps of 6.7% in nominal terms, which is equivalent to an average real return of 2.7% per annum. Prices have increased much faster in the second half of the 1960s, the late 1970s, and the current decade. However, we also record prolonged periods of real depreciation, for example in the 1980s. As a financial investment, stamps have outperformed bonds, but underperformed stocks. After unsmoothing the returns on stamps, we find that the volatility of stamp prices approaches that of equities. There is mixed evidence that stamps are a good hedge against inflation. Once the problem of non-synchronous trading is taken into account, stamp returns seem impacted by movements in the equity market.

This paper investigates the returns on British collectible postage stamps over the very long run, based on stamp catalogue prices. Between 1900 and 2008, we find an annualized return on stamps of 6.7% in nominal terms, which is equivalent to an average real return of 2.7% per annum. Prices have increased much faster in the second half of the 1960s, the late 1970s, and the current decade. However, we also record prolonged periods of real depreciation, for example in the 1980s. As a financial investment, stamps have outperformed bonds, but underperformed stocks. After unsmoothing the returns on stamps, we find that the volatility of stamp prices approaches that of equities. There is mixed evidence that stamps are a good hedge against inflation. Once the problem of non-synchronous trading is taken into account, stamp returns seem impacted by movements in the equity market.

Using a comprehensive hedge fund database, we examine the role of managerial incentives and discretion in hedge fund performance. Hedge funds with greater managerial incentives, proxied by the delta of the option-like incentive fee contracts, higher levels of managerial ownership, and the inclusion of high-water mark provisions in the incentive contracts, are associated with superior performance. The incentive fee percentage rate by itself does not explain performance. We also find that funds with a higher degree of managerial discretion, proxied by longer lockup, notice, and redemption periods, deliver superior performance. These results are robust to using alternative performance measures and controlling for different data-related biases. Copyright (c) 2009 the American Finance Association.

This note discusses some aspects of the estimation of the density function of a univariate probability distribution. All estimates of the density function satisfying relatively mild conditions are shown to be biased. The asymptotic mean square error of a particular class of estimates is evaluated.

We develop a simple rational model of active portfolio management that provides a natural benchmark against which to evaluate observed relationship between returns and fund flows. Many effects widely regarded as anomalous are consistent with this simple explanation. In the model, investments with active managers do not outperform passive benchmarks because of the competitive market for capital provision, combined with decreasing returns to scale in active portfolio management. Consequently, past performance cannot be used to predict future returns, or to infer the average skill level of active managers. The lack of persistence in actively managed returns does not imply that differential ability across managers is nonexistent or unrewarded, that gathering information about performance is socially wasteful, or that chasing performance is pointless. A strong relationship between past performance and the flow of funds exists in our model: indeed, this is the market mechanism that ensures that no predictability in performance exists. Choosing parameters to match the flow-performance relationship and survivorship rates, we find these features of the data are consistent with the vast majority (80%) of active managers having at least enough skill to make back their fees.

We examine the performance of the off-shore hedge fund industry over the period 1989 through 1995 using a database that includes both defunct and currently operating funds. The industry is characterized by high attrition rates of funds, low covariance with the U.S. stock market, evidence consistent with positive risk-adjusted returns over the time, and little evidence of differential manager skill.

Hedge fund strategies typically generate option-like returns. Linear-factor models using benchmark asset indices have difficulty
explaining them. Following the suggestions in Glosten and Jagannathan (1994), this article shows how to model hedge fund returns by focusing on the popular “trend-following” strategy. We use lookback
straddles to model trend-following strategies, and show that they can explain trend-following funds’ returns better than standard
asset indices. Though standard straddles lead to similar empirical results, lookback straddles are theoretically closer to
the concept of trend following. Our model should be useful in the design of performance benchmarks for trend-following funds.

We investigate the effect of scale on performance in the active money management industry. We first document that fund returns, both before and after fees and expenses, decline with lagged fund size, even after accounting for various performance benchmarks. We then explore a number of potential explanations for this relationship. This association is most pronounced among funds that have to invest in small and illiquid stocks, suggesting that these adverse scale effects are related to liquidity. Controlling for its size, a fund's return does not deteriorate with the size of the family that it belongs to, indicating that scale need not be bad for performance depending on how the fund is organized. Finally, using data on whether funds are solo-managed or team-managed and the composition of fund investments, we explore the idea that scale erodes fund performance because of the interaction of liquidity and organizational diseconomies.

This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also establishes consistency of the estimated covariance matrix under fairly general conditions.

Markov chain marginal bootstrap (MCMB) is a new method for constructing confidence intervals or regions for maximum likelihood estimators of certain parametric models and for a wide class of M estimators of linear regression. The MCMB method distinguishes itself from the usual bootstrap methods in two important aspects: it involves solving only one-dimensional equations for parameters of any dimension and produces a Markov chain rather than a (conditionally) independent sequence. It is designed to alleviate computational burdens often associated with bootstrap in high-dimensional problems. The validity of MCMB is established through asymptotic analyses and illustrated with empirical and simulation studies for linear regression and generalized linear models.

Hedge funds display several interesting characteristics that may influence performance, including: flexible investment strategies, strong managerial incentives, substantial managerial investment, sophisticated investors, and limited government oversight. Using a large sample of hedge fund data from 1988-1995, we find that hedge funds consistently outperform mutual funds, but not standard market indices. Hedge funds, however, are more volatile than both mutual funds and market indices. Incentive fees explain some of the higher performance, but not the increased total risk. The impact of six data-conditioning biases is explored. We find evidence that positive and negative survival-related biases offset each other. Copyright The American Finance Association 1999.

This article presents some new results on an unexplored dataset on hedge fund performance. The results indicate that hedge funds follow strategies that are dramatically different from mutual funds, and support the claim that these strategies are highly dynamic. The article finds five dominant investment styles in hedge funds, whichwhenadded to Sharpe's (1992) asset class factor model can provide an integrated framework for style analysis of both buy-and-hold and dynamic trading strategies

Risk, Return, and Equilibrium: Empirical TestsEmpirical Characteristics of Dynamic Trading Strate-gies: The Case of Hedge Funds

- E Fama
- J Macbeth Rfung
- D Hsieh

Fama, E., and J. MacBeth, 1973, “Risk, Return, and Equilibrium: Empirical Tests,” Journal of Political Economy, 81, 607–636. 26 rFung, W., and D. Hsieh, 1997, “Empirical Characteristics of Dynamic Trading Strate-gies: The Case of Hedge Funds,” Review of Financial Studies, 10, 275–302

On the Performance of Hedge Funds

- B Liang