Hedge Fund Alpha Research Articles

Can Factor Timing Explain Hedge Fund Alpha?

This paper empirically decomposes hedge fund excess return into factor timing, security selection, and risk premium using Lo (2008)’s performance measure. Portfolio-level tests show that security selection explains most of the excess return generated by hedge funds during 1994-2009, and the contribution of factor timing is small. Fund-level tests find significant evidence of both positive and negative timing, but the excess return of positive timing funds is not significantly higher than that of the other funds. These findings imply that factor timing is not the main source of hedge fund alpha, and the results are robust to different factor models.

Has Hedge Fund Alpha Disappeared?

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.

Redefining Hedge Fund Alpha and Risk Exposures after the Financial Crisis

The hedge funds industry has evolved tremendously in recent years. According to the CASAM CISDM Industry Report, assets under management in hedge funds had grown from less than USD 50 billion at the end of 1990 to over USD 2.1 trillion at the end of 2007. However, assets managed by hedge funds have dropped significantly since then to less than USD 1.3 trillion at the end of June 2009. Since hedge funds have been marketed to investors as risk diversifiers in addition to being return enhancers, the actual “manager skill” or “value added” or “alpha” deserves careful examination at this time. In this article we examine the validity of the concept of “alpha”. We use both single factor (Jensen’s alpha) and multi-factor models to estimate alpha. We use three different indices with vastly differing construction processes and compositions. Unlike most previous studies, we choose specific factors for each strategy. Our results show that strategy specific factors had greater explanatory power but were insufficient to explain the wide variety of fund exposures. Multi-factor models were an improvement but nevertheless insufficient. We conclude that quantitative analysis is generally insufficient when it comes to measuring manager skill (alpha). Manager skill or “alpha” should be determined in a qualitative setting as well. Unfortunately, there is no measure that encompasses both quantitative and qualitative attributes although hedge fund ratings agencies have made some headway in this regard.

Performance Measurement of Hedge Funds Portfolios in a Downside Risk Framework

This article starts with the recognition of the limits of a mean–variance framework to measure the performance of hedge funds, whose returns are often not normally distributed and usually asymmetric. It then introduces the literature focused on performance measurement in a downside-risk framework. The authors present both traditional and alternative performance measures, including an index of their own construction. They conclude that three well-accepted methods provide different rankings of hedge funds and, explaining the differences thus observed, suggest that the hedge fund alphas computed using their own approach are more correct. <b>TOPICS:</b>Real assets/alternative investments/private equity, risk management, statistical methods, performance measurement

Integrating volatility factors in the analysis of the hedge fund alpha puzzle

Estimation of financial models of hedge fund returns often gives rise to abnormally high alphas. This phenomenon may be due to mis-specified models, but recently the introduction of volatility factors in hedge fund returns models (Kuenzi and Xu, 2007) has been viewed as a solution to solve the alpha puzzle. This paper shows that modelling the volatility of the innovation term of hedge fund return models might be another way to explain the alpha puzzle. The model proposed in this paper is a factor model that incorporates an 'alternative' factor, which is the return of a short put on the Standard & Poor's 500 whose volatility is the VIX. This paper takes an overall view to analyse the problem of specification errors in financial models. To account for specification errors, it proposes a new estimator based on the generalised method of moments (GMM) whose instruments are the higher moments of returns, the GMM-hm. Some transformations of the basic factor model, which are recommended in the financial literature to improve the estimation of the alpha, are considered the n-CAPM and the conditional model. Some GARCH and EGARCH specifications of our basic model of returns are also estimated. Our results show that modelling the volatility of the innovation is the best way to lower the alpha. The n-CAPM has also had some success in reducing the alpha. The alpha is not the only garbage bag of a returns model (Jaeger and Wagner, 2005), but the alpha and the innovation both constitute the garbage bag.

Hedge Fund Alphas: Do They Reflect Managerial Skills or Mere Compensation for Liquidity Risk Bearing?

In this article, we study the eect of liquidity risk on the performance of various hedge fund portfolio strategies. The portfolio strategies in each hedge fund style are formed by incorporating predictability in: (i) managerial skills, (ii) fund risk loadings, and (iii) benchmark returns. As in Avramov et al. (2007), we find that, before taking into account the eect of liquidity risk, long-only constrained hedge fund style portfolios that incorporate predictability in managerial skills generate superior performance. However, the outperformance disappears or weakens dramatically for seven out of ten types of hedge fund style portfolios once the eect of liquidity risk is incorporated into the performance evaluation framework. Hence, for most hedge fund style-based portfolio strategies, “alphas” to a large extend reflect mere compensation for liquidity risk bearing. These results are robust to: (i) an alternative performance evaluation model (ii) an alternative liquidity risk proxy, (iii) the exclusion of the January eect on the liquidity premium and (iv) the exclusion of the recent financial crises data.

The Impact of Non-normality Risks and Tactical Trading on Hedge Fund Alphas

In recent years, hedge funds have become very popular, with institutional investors. This article contributes to the debate on hedge fund performance by quantifying the omission non-normality risks and tactical trading when evaluating hedge fund returns. This is done by evaluating hedge fund performance using a model that treats systematic non-normality risks as a potential source of hedge fund returns. In addition, the tactical asset allocation decisions of fund managers are explicitly modeled. The results show that the arrival of public information alters the asset allocation of hedge fund managers and induces a change in the risk profile and performance of hedge funds. Further they indicate that failure to account for these two features leads to incorrect statistical inference on the performance of 1 out of 4 hedge funds and overstates alpha estimates. Overall, non-normality risks and tactical asset allocation explain no less than 23.1% of the commonly perceived abnormal performance of hedge funds. <b>TOPICS:</b>Real assets/alternative investments/private equity, risk management, performance measurement, portfolio construction

Why Does Hedge Fund Alpha Decrease Over Time? Evidence from Individual Hedge Funds

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.

The Effect of Investor Flows on Hedge Fund Manager Performance and the Decision to Invest

The Hedge Fund Industry has grown tremendously over the last decade and a half and its importance is becoming more pronounced in the financial markets. This thesis examines if manager performance is driving the growth of hedge funds, and how the performance of the funds is affected by increasing investor flows. Using data on the monthly returns of 3668 hedge funds during the period January 1988 to December 2005, from a less frequently researched hedge fund database, CISDM, individual hedge fund alphas are estimated using an eight-factor model. It is found that manager alphas have compressed towards zero over time and investors are generally not likely to find managers who generate significant risk adjusted returns annually and persistently. Using a logistic regression, the determinants and influences on alpha and persistence are explored. It is found that managers increase their likelihood of having alpha and their likelihood of persistence in alpha by taking on less risk, as well as age tends to negatively affect alpha. Lastly, the relationship of investor flows to performance is examined. Investors are found to be rational because flows do not react to alpha, since most managers are unlikely to generate alpha persistently. Investors do however, base their flows on past raw returns and generally prefer funds with low volatility and more experience.

A First Cut Evaluation of the Impact of Industry Cash Flows on Hedge Fund Alpha

The current consensus that industry growth, as evidenced by massive cash flows and the proliferation of hedge funds, must lead to substantially lower returns across the wide spectrum of strategies clearly has both some intuitive attractiveness and some academic support. Yet only a more careful analysis can help determine whether it is really valid in practice or simply too sweeping to contain useful insights. In this brief article, the author summarizes work recently completed to address this issue in some more depth. A first cut analysis of manager alpha across several strategies or groups of strategies does suggest that there may have been more negative impact from cash flows in the absolute return space than in the area of semi-directional or managed futures strategies. This makes general sense when one observes that there are more conceivable limits to the number of trading opportunities available in the absolute return space than in other segments of the hedge fund industry. Yet even there, one should recognize that this analysis has identified interesting alpha trends, but has not focused on explaining them in an exhaustive and systematic manner. It would therefore be very interesting to conduct additional research, focused first on a more detailed definition of manager alpha and second on the explanation of changes in these levels of alpha, when these have evidently occurred.

The Art of Investing in Hedge Funds: Fund Selection and Optimal Allocations

With institutional investors increasingly involved in alternative investments, portfolio optimisation within a large universe of hedge funds has become a key area for research. This paper develops a portfolio construction model that is specifically designed for funds of hedge funds, incorporating specific controls for operational limitations, data biases and incompleteness. Absolute performance is targeted by selecting funds according to their alpha estimated with factor models. Whilst different factor models provide quite different estimates of a hedge fund's alpha, we can still use the ranking produced by them in the fund selection process. In an extensive out-of-sample historical analysis, funds of funds that are selected in this way and then allocated using constrained minimum variance optimisation are shown to perform much better than the equally weighted portfolio of all funds, or minimum variance portfolios of randomly selected funds. This is true even when hedge funds are selected according to their alphas produced by simple factor models. The best out-of-sample performance is obtained, out of the four factor models considered in this analysis, with the statistical factor model.