Quantile regression analysis of hedge fund strategies

Extending previous work on hedge fund pricing, this paper introduces the idea of modelling the conditional quantiles of hedge fund returns using a set of risk factors. Quantile regression analysis provides a way of understanding how the relationship between hedge fund returns and risk factors changes across the distribution of conditional returns. We propose a Bayesian approach to model comparison which provides posterior probabilities for different risk factor models that can be used for model averaging. The most relevant risk factors are identified for different quantiles and compared with those obtained for the conditional expectation model. We find differences in factor effects across quantiles of returns, which suggest that the standard conditional mean regression method may not be adequate for uncovering the risk-return characteristics of hedge funds. We explore potential economic impacts of our approach by analysing hedge fund single strategy return series and by constructing style portfolios.     

The risk in hedge fund strategies: Theory and evidence from long/short equity hedge funds

Theory suggests that long/short equity hedge funds' returns come from directional as well as spread bets on the stock market. Empirical analysis finds persistent net exposures to the spread between small vs large cap stocks in addition to the overall market. Together, these factors account for more than 80% of return variation. Additional factors are price momentum and market activity. Combining two major branches of hedge fund research, our model is the first that explicitly incorporates the effect of funding (stock loan) on alpha. Using a comprehensive dataset compiled from three major database sources, we find that among the three thousand plus hedge funds with similar style classification, less than 20% of long/short equity hedge funds delivered significant, persistent, stable positive non-factor related returns. Consistent with the predictions of the Berk and Green (2004) model we find alpha producing funds decays to “beta-only” over time. However, we do not find evidence of a negative effect of fund size on managers' ability to deliver alpha. Finally, we show that non-factor related returns, or alpha, are positively correlated to market activity and negatively correlated to aggregate short interest. In contrast, equity mutual funds and long-bias equity hedge funds have no significant, persistent, non-factor related return. Expressed differently, L/S equity hedge funds, as the name suggests, do benefit from shorting. Besides differences in risk taking behavior, this is a key feature distinguishing L/S funds from long-bias funds.     

Higher risk,lower returns: What hedge fund investors really earn

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.     

Style analysis and Value-at-Risk of Asia-focused hedge funds

In this paper we identify risk factors for Asia-focused hedge funds through a modified style analysis technique. Using an Asian hedge fund index, we find that Asian hedge funds show significant positive exposures to emerging equity markets. For both a static and rolling period style analysis, our model provides a high explanatory power for returns of the considered hedge fund index. We further conduct a Value-at-Risk analysis using the results of a rolling window style analysis as inputs. Our findings suggest that the considered parametric models outperform a simple historical simulation that is purely based on past return observations.     

Do Hot Hands Exist among Hedge Fund Managers? An Empirical Evaluation

In measuring performance persistence, we use hedge fund style benchmarks. This allows us to identify managers with valuable skills, and also to control for option-like features inherent in returns from hedge fund strategies. We take into account the possibility that reported asset values may be based on stale prices. We develop a statistical model that relates a hedge fund's performance to its decision to liquidate or close in order to infer the performance of a hedge fund that left the database. Although we find significant performance persistence among superior funds, we find little evidence of persistence among inferior funds.     

Emerging Market Exposures and the Predictability of Hedge Fund Returns

We examine emerging market and global macro hedge funds and find a significant positive relation between hedge funds’ future returns and their exposure to both emerging market equities and emerging market currencies. We present evidence that the strong predictive power of emerging market betas is related to the superior market‐timing ability of these fund managers. Results are robust after controlling for commonly used hedge fund factors, the emerging market equity index, lagged fund returns, liquidity risk, and fund characteristics. Our results suggest that hedge funds can earn positive excess returns by timing their exposure to emerging market securities.     

Changing investment styles: style creep and style gaming in the hedge fund industry

Notwithstanding their common features, hedge funds remain an extremely diverse asset class. Information on fund styles is important for numerous purposes, such as portfolio construction, performance attribution and risk management. With fund self‐declaration being prone to (strategic) misclassification, return‐based taxonomies grouping funds along similarities in realized returns provide a useful alternative. We provide a consistent classification system of homogeneous groups of hedge funds based on self‐organizing maps. Whereas some fund categories such as managed futures are largely consistent in their self‐declared strategies, others, especially so‐called ‘equity hedge’ funds, display no or very limited return similarities. Furthermore, we also find evidence of fund managers performing undisclosed changes of their trading style over time. Those funds that misclassified themselves once are particularly likely to change their trading style again. Although style self‐declaration can, therefore, be quite misleading, our results indicate that hedge funds do not misdeclare their style strategically to improve their relative performance. Copyright © 2006 John Wiley & Sons, Ltd.     

Hedge funds and optimal asset allocation: Bayesian expectations and spanning tests

This paper analyzes the contribution of hedge funds to optimal asset allocations between 1993 and 2010. The preferences of specific institutional investors are captured by implementing a Bayesian asset allocation framework that incorporates heterogeneous expectations regarding hedge fund alpha. Mean-variance spanning tests are used to infer the ability of hedge funds to significantly enhance the mean-variance efficient frontier. Further, a novel democratic variance decomposition procedure sheds light on the dynamics in the co-movement of hedge fund returns with a set of common benchmark assets. The empirical findings indicate that portfolio benefits of hedge funds are time-varying and strongly depend on investor optimism regarding hedge funds’ ability to generate alpha. In general, allocations to hedge funds improve the global minimum variance portfolio even after controlling for short-selling restrictions and minimum diversification constraints. However, due to dynamics underlying the composition of the aggregate hedge fund universe, the factor structure of hedge fund returns has become more similar to the benchmark assets over time.     

HEDGE FUNDS: WHAT DO WE KNOW?

Hedge funds are attracting increased attention because of their reputation for earning superior (risk-adjusted) returns. Hedge Fund Research Inc. estimates that in 2001 there were about 7,000 hedge funds with investor capital of about $600 billion. And yet the diversity of hedge funds, combined with a general lack of transparency, makes the hedge fund industry something of a "black box."
This article provides an overview of the legal structure of hedge funds, the various fund investment strategies, and the existing research on overall hedge fund performance. Without uniform and comprehensive reporting requirements, it is difficult to ascertain the size and scope of hedge fund investments. Nonetheless, current research provides persuasive evidence that hedge funds earn positive risk-adjusted returns, on average, in contrast to their counterparts in the mutual fund industry. In an attempt to explain these higher returns, the authors begin by noting that hedge funds are subject to considerably less regulation than other investment institutions because their client base is limited to wealthy individuals and institutions. Hedge funds can thus employ investment strategies that mutual funds and pension funds are prohibited from pursuing, such as short selling, high leverage, derivatives, concentrated holdings, and limited redemptions. As a result, the funds may be able to earn excess returns by operating in illiquid and specialized markets where there is a shortage of arbitrage capital. At the same time, and perhaps even more important, hedge funds are in a better position than conventional mutual funds to attract skilled managers because of their use of performance-based incentive fee structures.     

Convertible Bond Arbitrage: Risk and Return

Abstract:  This paper specifies a simulated convertible bond arbitrage portfolio to characterise the risks in convertible bond arbitrage. For comparison the risk profile of convertible bond arbitrage hedge fund indices at both monthly and daily frequencies is also examined. Results indicate that convertible bond arbitrage is positively related to default and term structure risk factors. These risk factors are augmented with the simulated convertible bond arbitrage portfolio, mimicking a passive investment in convertible bond arbitrage, to assess the risk and return of individual hedge funds. We provide estimates of the performance of two hedge fund indices (an equally weighted and value weighted index) and a sample of convertible bond arbitrage hedge funds using a factor model methodology. Lagged and contemporaneous observations of the risk factors are specified, controlling for illiquidity in the securities held by funds. Our results cover two time periods. Initially we find evidence of abnormal risk adjusted returns in the individual hedge fund data and the equally weighted hedge fund index and no evidence of abnormal risk adjusted returns in the value weighted hedge fund index. When we examine performance during the credit crisis of 2007 and 2008 we find evidence of negative abnormal returns amongst individual hedge funds and the hedge fund indices.     

Should hedge funds be cautious reporting high returns?

In a recent article, Schuster and Auer (2012) show that fund managers with a certain positive performance need to be aware of the fact that too high prospective excess returns can lower the empirical Sharpe ratio of their funds. In this note, we investigate the empirical relevance of this effect. We analyse whether hedge funds being evaluated on the basis of the Sharpe ratio negatively influence their performance by reporting too high returns. Our results show that a economically significant number of hedge funds listed in the CISDM hedge fund database has at least once reported a high return causing this effect.     

The Style Consistency of Hedge Funds

This study examines the style classification and the style consistency of hedge funds using a new proprietary database over the period May 1989 to April 1999. First, a hard clustering procedure is applied to classify hedge funds into homogeneous groups. It is shown that the methodology is robust and can be used to build stable hedge funds indexes. The method performs equally well as the principal component analysis in explaining in‐ and out‐of‐sample cross‐sectional hedge funds' returns. Second, we extend hard to fuzzy cluster memberships, relaxing the full assignment of the funds to individual clusters. We apply the fuzzy clustering methodology to estimate hedge funds' probabilistic exposure to various styles. We introduce three consistency indicators to quantify the hedge fund managers' style opportunism levels. We finally document that there is no evidence that style consistency leads to superior hedge funds' performance.     

Capacity Constraints and Hedge Fund Strategy Returns

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.     

Speculative capital and currency carry trades

In this paper, we study a two-country general equilibrium model with partially segmented financial markets, where hedge funds emerge endogenously. Empirically, we show that the hedge fund investment strategy predicted by our model, which we call the “risk-adjusted carry trade” strategy, explains more than 16% of the overall hedge fund index returns and more than 33% of the fixed income arbitrage sub-index returns. The flow of new money to hedge funds affects market interest rates, exchange rates, and both the hedge funds’ contemporaneous and expected future returns as predicted by the model.     

Commonality in hedge fund returns: Driving factors and implications

We measure the commonality in hedge fund returns, identify its main driving factor and analyze its implications for financial stability. We find that hedge funds’ commonality increased significantly from 2003 until 2006. We attribute this rise mainly to the increase in hedge funds’ exposure to emerging market equities, which we identify as a common factor in hedge fund returns over this period. Our results show that funds with a high commonality were affected disproportionately by illiquidity and exhibited negative returns during the subsequent financial crisis, thereby providing little diversification benefits to the financial system and to investors.     

Capturing hedge fund risk factor exposures: Hedge fund return replication with ETFs

We develop a new factor selection methodology of spanning the space of hedge fund risk factors with all available exchange traded funds (ETFs). We demonstrate the efficacy of the methodology with out-of-sample individual hedge fund return replication by ETF clone portfolios. This is consistent with our interpretation of ETF returns as proxies to risk factors driving hedge fund returns. We further consider portfolios of “cloneable” and “noncloneable” hedge funds, defined as top and bottom in-sample R² matches, and demonstrate that our ETF clone portfolios slightly outperform cloneable hedge funds out of sample.     

Tax-Efficient Asset Management: Evidence from Equity Mutual Funds

We investigate the relation between tax burdens and mutual fund performance from both a theoretical and an empirical perspective. The theoretical model introduces heterogeneous tax clienteles in an environment with decreasing returns to scale and shows that the equilibrium performance of mutual funds depends on the size of the tax clienteles. Our empirical results show that the performance of U.S. equity mutual funds is related to their tax burdens. We find that tax-efficient funds exhibit not only superior after-tax performance, but also superior before-tax performance due to lower trading costs, favorable style exposures, and better selectivity.     

Conditional Properties of Hedge Funds: Evidence from Daily Returns*

Using daily returns on a set of hedge fund indices, we study (i) the properties of the indices' conditional density functions and (ii) the presence of asymmetries in conditional correlations between hedge fund indices and other investments and between hedge fund indices themselves. We use the SNP approach to obtain estimates of conditional densities of hedge fund returns and then proceed to examine their properties. In general, a nonparametric GARCH(1,1) model appears to provide the best fit for all strategies. We find that the conditional third and fourth moments are significantly affected by changes in the current volatility of returns on hedge fund indices. We examine changes in the conditional probability of tail events and report significant changes in the probability of extreme events when the conditioning information changes. These results have important implications for models of hedge fund risk that rely on probability of tail events. We formally test for the presence of asymmetries in conditional correlations to determine if there is contagion between hedge funds and other investments and between various hedge fund indices in extreme down markets versus extreme up markets. We generally do not find strong evidence in support of asymmetric correlations.     

Hedge fund allocation: Evaluating parametric and nonparametric forecasts using alternative portfolio construction techniques

We propose a model for constructing Asian funds of hedge funds. We compare the accuracy of forecasts of hedge fund returns using an ordinary least squares (OLS) regression model, a nonparametric regression model, and a nonlinear nonparametric model. We backtest to assess these forecasts using three different portfolio construction processes: an “optimized” portfolio, an equally-weighted portfolio, and the Kelly criterion-based portfolio. We find that the Kelly criterion is a reasonable method for constructing a fund of hedge funds, producing better results than a basic optimization or an equally-weighted portfolio construction method. Our backtests also indicate that the nonparametric forecasts and the OLS forecasts produce similar performance at the hedge fund index level. At the individual fund level, our analysis indicates that the OLS forecasts produce higher directional accuracy than the nonparametric methods but the nonparametric methods produce more accurate forecasts than OLS. In backtests, the highest information ratio to predict hedge fund returns is obtained from a combination of the OLS regression with the Fung–Hsieh eight-factor variables as predictors using the Kelly criterion portfolio construction method. Similarly, the highest information ratio using forecasts generated from a combination of the nonparametric regression using the Fung–Hsieh eight-factor model variables is achieved using the Kelly criterion portfolio construction method. Simulations using risk-adjusted total returns indicate that the nonparametric regression model generates superior information ratios than the analogous backtest results using the OLS. However, the benefits of diversification plateau with portfolios of more than 20 hedge funds. These results generally hold with portfolio implementation lags up to 12 months.