A unique view of hedge fund derivatives usage: Safeguard or speculation?

We study the common equity and equity option positions of hedge fund investment advisors over the 1999–2006 period. We find that hedge funds' stock positions predict future returns and that option positions predict both volatility and returns on the underlying stock. A quarterly tracking portfolio of stocks based on publicly observable hedge fund option holdings earns abnormal returns of 1.55% through the end of the quarter. Net of fees, hedge funds using options deliver higher benchmark-adjusted portfolio returns and lower risk than nonusers. The results suggest that hedge fund positions reflect significant timing and selectivity skill.     

The performance and diversification benefits of funds of hedge funds

We examine the performance and diversification potential of 332 funds of hedge funds (FOHFs) for the period from January 1990 to May 2003. Consistent with prior studies, we find that FOHFs appear to underperform the hedge fund index on a risk-adjusted basis. However, FOHFs have characteristics that offset their apparent underperformance. Their returns do not suffer from negative skewness that is a feature of many hedge fund strategies. Relative to the hedge fund index, we find that FOHFs have lower correlations with stock indices in both bull and bear markets, making them a better diversification tool in equity portfolios. For bond portfolios, however, FOHFs have no diversification advantage over hedge fund indexing.     

Risk and return in convertible arbitrage: Evidence from the convertible bond market

In this paper, we identify and document the empirical characteristics of the key drivers of convertible arbitrage as a strategy and how they impact the performance of convertible arbitrage hedge funds. We show that the returns of a buy-and-hedge strategy involving taking a long position in convertible bonds (“CBs”) while hedging the equity risk alone explains a substantial amount of these funds' return dynamics. In addition, we highlight the importance of non-price variables such as extreme market-wide events and the supply of CBs on performance. Out-of-sample tests provide corroborative evidence on our model's predictions. At a more micro level, larger funds appear to be less dependent on directional exposure to CBs and more active in shorting stocks to hedge their exposure than smaller funds. They are also more vulnerable to supply shocks in the CB market. These findings are consistent with economies of scale that large funds enjoy in accessing the stock loan market. However, the friction involved in adjusting the stock of risk capital managed by a large fund can negatively impact performance when the supply of CBs declines. Taken together, our findings are consistent with convertible arbitrageurs collectively being rewarded for playing an intermediation role of funding CB issuers whilst distributing part of the equity risk of CBs to the equity market.     

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.     

Overcoming limits of arbitrage: Theory and evidence

Limits to arbitrage arise because financial intermediaries may face funding constraints when mispricing worsens. Using a model with limits to arbitrage, where we allow arbitrageurs to secure capital even in case of underperformance, we show that arbitrageurs that are more protected from withdrawals have more mean-reverting and volatile returns. Using data on hedge fund performance, we find robust support for these hypotheses: Funds with contractual impediments to withdrawals, and funds with performance-insensitive outflows, recover more quickly after a bad year and have more volatile returns. Our evidence is consistent with the idea that some hedge funds overcome the limits to arbitrage.     

Synthetic hedge funds

We provide evidence on the performance and the replication success of a broad sample of 72 synthetic hedge funds from January 2009 to December 2013. Thereby, we assign the term “synthetic hedge fund” to mutual funds and exchange-traded funds with hedge fund indices as their benchmarks. Replication success is measured through different perspectives from distributional characteristics to risk-adjusted performance. We find an overall significant underperformance of synthetic hedge funds compared to an appropriate benchmark index. Furthermore, mutual funds (associated with active portfolio management) can produce return characteristics closer to hedge fund benchmarks than exchange-traded funds (associated with passive management) can. From a single strategy perspective, we find a picture of heterogeneity. Regarding the market environment, we show larger return differences for unusual market conditions than for regular ones.     

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.     

Hedge fund return predictability; To combine forecasts or combine information?

While the majority of the predictability literature has been devoted to the predictability of traditional asset classes, the literature on the predictability of hedge fund returns is quite scanty. We focus on assessing the out-of-sample predictability of hedge fund strategies by employing an extensive list of predictors. Aiming at reducing uncertainty risk associated with a single predictor model, we first engage into combining the individual forecasts. We consider various combining methods ranging from simple averaging schemes to more sophisticated ones, such as discounting forecast errors, cluster combining and principal components combining. Our second approach combines information of the predictors and applies kitchen sink, bootstrap aggregating (bagging), lasso, ridge and elastic net specifications. Our statistical and economic evaluation findings point to the superiority of simple combination methods. We also provide evidence on the use of hedge fund return forecasts for hedge fund risk measurement and portfolio allocation. Dynamically constructing portfolios based on the combination forecasts of hedge funds returns leads to considerably improved portfolio performance.     

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.     

Systematic risk and the cross section of hedge fund returns

This paper investigates the extent to which market risk, residual risk, and tail risk explain the cross-sectional dispersion in hedge fund returns. The paper introduces a comprehensive measure of systematic risk (SR) for individual hedge funds by breaking up total risk into systematic and fund-specific or residual risk components. Contrary to the popular understanding that hedge funds are market neutral, we find that systematic risk is a highly significant factor explaining the dispersion of cross-sectional returns while at the same time measures of residual risk and tail risk seem to have little explanatory power. Funds in the highest SR quintile generate 6% more average annual returns compared with funds in the lowest SR quintile. After controlling for a large set of fund characteristics and risk factors, systematic risk remains positive and highly significant, whereas the relation between residual risk and future fund returns continues to be insignificant. Hence, systematic risk is a powerful determinant of the cross-sectional differences in hedge fund returns.     

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.     

Failure Risk and the Cross‐Section of Hedge Fund Returns

Modeling a hedge fund's probability of failure with a dynamic logit regression, I find that the probability of a fund's failure has a significantly negative effect on the fund's future returns. A quintile portfolio with the highest failure probability underperforms a quintile portfolio with the lowest failure probability by 5% to 6% per year from 1997 to 2012. The results are robust to the definition of hedge fund failure and controlling for a large set of risk factors and fund characteristics. Moreover, the negative effect of failure probability on future fund returns is stronger for funds with weak share restrictions.     

Zur Risikoanalyse von Hedgefonds: Ein datenanalytischer Ansatz

Hedge fund returns have a number of specific features compared to traditional investments which result in problems when applying traditional methods of risk analysis (Markowitz portfolio selection theory, Sharpe Ratio, value at risk calculation based on normal returns). These problems have to be considered adequately by insurance companies when constructing internal risk models and performing risk management for hedge funds in their investment.The present paper has its focus on the departure of hedge fund returns from the normality hypothesis, especially with respect to the statistical quantities skewness and kurtosis (fat tail problem). A statistical analysis of hedge fund index returns gives evidence that the majority of hedge fund returns show substantial departures from normality. In addition, the analysis shows that hedge fund returns are adequately represented by the family of GH-distributions developed in exploratory data analysis. Following this result a risk analysis of hedge fund strategies is performed on the basis of the GH-value at risk.     

Hedge Fund Risk Dynamics: Implications for Performance Appraisal

Accurate appraisal of hedge fund performance must recognize the freedom with which managers shift asset classes, strategies, and leverage in response to changing market conditions and arbitrage opportunities. The standard measure of performance is the abnormal return defined by a hedge fund's exposure to risk factors. If exposures are assumed constant when, in fact, they vary through time, estimated abnormal returns may be incorrect. We employ an optimal changepoint regression that allows risk exposures to shift, and illustrate the impact on performance appraisal using a sample of live and dead funds during the period January 1994 through December 2005.     

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.     

Performance aspects of Greek bond mutual funds

This paper examines the performance characteristics of Greek bond funds and the impact of fund flows on portfolio returns. The evidence shows that on average bond funds do not offer risk-adjusted profits exceeding the returns of the benchmark index, which is in consistence with the US and international evidence. Returns before fees are slightly superior to the returns of the benchmark index, but when fees are considered they lag considerably. The security selection and market timing skills of fund managers are also tested using both an unconditional and a conditional model to test for the impact of public information variables. We also find that fund flows impact negatively on market timing.     

The financial crisis and hedge fund returns

The financial crisis has focused the lens of politicians and regulators on hedge funds as a source of systemic and operational risk in asset markets. We examine the extent to which available data can provide useful information regarding the impact of hedge funds on the financial system. Using data from January 1994 through September 2008, we find dramatic changes in the exposures of hedge funds to risk factors, accompanied by a significant and widespread increase in correlation between hedge fund and factor returns. Lastly, the discontinuity at zero in the cross-sectional distribution of hedge fund returns persists throughout the sample.     

On the High‐Frequency Dynamics of Hedge Fund Risk Exposures

We propose a new method to model hedge fund risk exposures using relatively high‐frequency conditioning variables. In a large sample of funds, we find substantial evidence that hedge fund risk exposures vary across and within months, and that capturing within‐month variation is more important for hedge funds than for mutual funds. We consider different within‐month functional forms, and uncover patterns such as day‐of‐the‐month variation in risk exposures. We also find that changes in portfolio allocations, rather than in the risk exposures of the underlying assets, are the main drivers of hedge funds' risk exposure variation.     

Hedge Fund Indices: Reconciling Investability and Representativity

Following a growing concern among investors about the quality of hedge fund index return data, this paper addresses the question of whether designing hedge fund indices that fulfil the usual requirements (in particular representative and investable) is or not a feasible task, given a variety of features that are specific to that industry. To test whether or not investability should necessarily come at the cost of representativity, we use a well‐known methodology in the asset pricing literature based on the concept of factor replicating portfolios. Our results suggest that it is actually possible to construct representative indices based on a limited number of funds that are open to new investments, except perhaps in the case of equity market neutral strategies, provided that: i) these funds are suitably selected and ii) a portfolio is constructed with the objective of replicating the common trend in hedge fund returns for a given strategy. A range of robustness tests are performed that show that high correlation of the factor replicating portfolios with the common factor of returns for each strategy is remarkably stable with respect to modifying the number of funds in the replicating portfolio or changing the frequency of rebalancing.     

Why are convertible bond announcements associated with increasingly negative issuer stock returns? An arbitrage-based explanation

While convertible offerings announced between 1984 and 1999 induce average abnormal stock returns of −1.69%, convertible announcement effects over the period 2000–2008 are more than twice as negative (−4.59%). We hypothesize that this evolution is attributable to a shift in the convertible bond investor base from long-only investors towards convertible arbitrage funds. These funds buy convertibles and short the underlying stocks, causing downward price pressure. Consistent with this hypothesis, we find that the differences in announcement returns between the Traditional Investor period (1984–1999) and the Arbitrage period (2000–September 2008) disappear when controlling for arbitrage-induced short selling associated with a range of hedging strategies. Post-issuance stock returns are also in line with the arbitrage explanation. Average announcement effects of convertibles issued during the Global Financial Crisis are even more negative (−9.12%), due to a combination of short-selling price pressure and issuer, issue, and macroeconomic characteristics associated with these offerings.