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The purpose of this paper is to test the new Fama and French (2015) five-factor model relying on a thorough sample of hedge fund strategies drawn from the Barclay’s Global hedge fund database.

The authors use a stepwise regression to identify the factors of the q-factor model which are relevant for the hedge fund strategy analysis. Doing so, the authors account for the Fung and Hsieh seven factors which prove very useful in the explanation of the hedge fund strategies. The authors introduce interaction terms to depict any interaction of the traditional Fama and French factors with the factors associated with the q-factor model. The authors also examine the dynamic dimensions of the risk-taking behavior of hedge funds using a BEKK procedure and the Kalman filter algorithm.

The results show that hedge funds seem to prefer stocks of firms with a high investment-to-assets ratio (low conservative minus aggressive (CMA)), on the one hand, and weak firms’ stocks (low robust minus weak (RMW)), on the other hand. This combination is not associated with the conventional properties of growth stocks – i.e., low high minus low (HML) stocks – which are related to firms which invest more (low CMA) and which are more profitable (high RMW). Finally, small minus big (SMB) interacts more with RMW while HML is more correlated with CMA. The conditional correlations between SMB and CMA, on the one hand, and HML and RMW, on the other hand, are less tight and may change sign over time.

To the best of the authors’ knowledge, the authors are the first to cast the new Fama and French five-factor model in a hedge fund setting which account for the Fung and Hsieh option-like trading strategies. This approach allows the authors to better understand hedge fund strategies because q-factors are useful to study the dynamic behavior of hedge funds.

The purpose of this paper is to propose that simple measures of linear association are unable to capture accurately the dependence between the survival of hedge funds and funds of funds, respectively. The paper then aims to advocate the use of copulas to model the joint survival of hedge funds and funds of funds managed by the same manager.

The paper uses both a one‐step approach where the margins and the copula parameters are estimated jointly, and a two‐step approach where the margins are fitted first and the copula parameter is estimated thereafter given the fixed margins. The margins are estimated non‐parametrically, semi‐parametrically, and parametrically, respectively.

First, the paper finds that Kendall's tau and Spearman's rho are anywhere between three and eight times larger than the corresponding sample based measures when various families of copulas are employed. Second, additional tests show that the two survival functions are strongly dependent, with the degree of nonlinear association increasing in the lower left quadrant.

This is the first paper to use copulas to model the joint survival of hedge funds and funds of funds. The results highlight the asymmetric dependence between hedge funds and funds of funds, which has implications for risk management practices.

Explains the popularity of hedge funds as a convenient way to park pension fund and endowment fund money onshore or offshore in times of volatile stock and bond markets; as a result, hedge fund assets have risen to almost $650 billion. Relates this to why they are vulnerable to scams: they are largely unregulated and operate in secrecy, as the proprietary investment strategies of the manager cannot be revealed because of the added value they bring to the fund. Asks where the auditors were in cases of abuse, and gives examples of billion dollar frauds. Recommends measures to minimise risk of hedge fund fraud: put managers and staff under scrutiny for criminal convictions, perform due diligence and background tests, ensure proper audits, and meet with current fund clients.

Hedge fund replication gained considerable attention during the period surrounding 2007 when it was anticipated to become for hedge fund investors what index funds are for equity investors. The hedge fund replication concept only lacked a track record. This paper aims to present an updated evaluation.

Performance is evaluated on both a raw‐return basis and a risk‐adjusted basis using Fung and Hsieh's 8‐factor model. Particular emphasis is given to analyzing the performance of these products during the financial crisis and to highlighting the specific characteristics that distinguished them from their hedge fund cousins during this period.

The results show that the hedge fund replication space is definitely proving its existence as a credible hedge fund investment alternative. Talented hedge fund managers will always be in high demand, but they may have to just prove their high compensation a bit harder.

Although this study is based on a short sample period, the results indicate that hedge fund replication products delivered returns that were at par with the returns of hedge funds. The replication products performed comparatively well during the crisis probably as a result of having less exposure to illiquid assets.

To the best of the authors' knowledge, this article uses the most extensive data set of 22 hedge fund replication products to analyze their performance.

The purpose of this paper is to explore how hedge fund database biases developed during the 2007‐2009 financial crisis.

The sample consists of 8,935 hedge funds from the Lipper TASS Hedge Fund Database for the January 2002‐September 2010 time period. The theoretical foundation of this paper draws from Fung and Hsieh who argue that time series of funds of hedge funds should be less prone to some of the documented database biases. The paper uses a sampling technique to create hedge fund portfolios, and then compares them using fund of fund data.

The paper finds empirical evidence that fund of hedge fund data is less biased than single hedge fund data, and that the impact of the survivorship and backfilling biases has increased since the financial crisis. It also finds that the attrition rate for hedge funds has nearly doubled since the financial crisis, and that an elevated attrition rate has a negative impact on the quality and representativeness of hedge fund data due to the liquidation bias. The liquidation bias increased strongly in the aftermath of the financial crisis. It also fluctuates over time, and it can account for an overestimate of performance of over 10 percent p.a.

Given this increase and the volatile nature of hedge fund biases, we believe investors (for benchmarking) and academics (for empirical studies) should consider refraining from using single hedge fund index data.

This chapter aims to determine whether diversification benefits accrue from adding emerging market hedge funds (EMHFs) to an emerging market bond/equity portfolio, and subsequently whether the type of exposure hedge funds provide is justified by their fees. We use multivariate cointegration analysis to show that the advantages of adding hedge funds to balanced portfolios are limited for the three regions of Asia, Eastern Europe, and Latin America, as well as for the entire global emerging market universe. In summary, we find that emerging market hedge funds are generally redundant for diversifying long-only emerging market investment portfolios with long-term investment horizons. This result also holds when we extend our sample by the global financial crisis in 2008 and 2009 and allow for structural breaks according to the Gregory-Hansen (1996) test. Hence, even during the global financial crisis in 2008 and 2009, when risk diversification was most needed, long-term comovements between hedge funds and traditional assets is, with the exception of the Eastern European region, not disrupted. Because EMHF returns are heavily influenced by the emerging market equity and bond markets, we conclude that the “alpha fees” charged by EMHFs may not always be appropriate for the three main regions under consideration. This also holds, however, to a lesser extent, for a global diversification among hedge funds and traditional assets in emerging markets.

The purpose of this paper is to gain a better understanding of the market timing skills displayed by hedge fund managers during the 2007‐08 financial crisis.

The performance of a market timer can be measured through the 1966 Treynor and Mazuy model, provided the regression alpha is properly adjusted by using the cost of an option‐based replicating portfolio, as shown by Hübner. The paper adapts this approach to the case of multi‐factor models with positive, negative or neutral betas. This new approach is applied on a sample of hedge funds whose managers are likely to exhibit market timing skills. This concentrates on funds that post weekly returns, and analyzes three hedge funds strategies in particular: long‐short equity, managed futures, and funds of hedge funds. The paper analyzes a particular period during which the managers of these funds are likely to magnify their presumed skills, namely around the financial and banking crisis of 2008.

Some funds adopt a positive convexity as a response to the US market index, while others have a concave sensitivity to the returns of an emerging market index. Thus, the paper identifies “positive”, “mixed” and “negative” market timers. A number of signs indicate that only positive market timers manage to acquire options below their cost, and deliver economic significant performance, even in the midst of the financial crisis. Negative market timers, by contrast, behave as if they were forced to sell options without getting the associated premium. This behaviour is interpreted as a possible result of re sales, leading them to liquidate positions under the pressure of redemption orders, and inducing negative performance adjusted for market timing.

The paper suggests that the convexity in returns that is generally associated with market timing can be attributed to three sources: timing skills, exposure to nonlinear risk factors, or liquidity pressures. It manages to identify the impact of the latter two effects in the context of hedge funds.

The purpose of this paper is to investigate the return performance of different investment strategies in the hedge fund sector, with a particular emphasis on the recent US financial crisis of 2007‐2010. Additionally, the paper aims to investigate the comovement of hedge fund index returns.

The paper identifies broad hedge fund investment strategies using data from the Dow Jones Credit Suisse Hedge Fund Database. It examines the return comovement using the cross‐sectional volatility, covariance, and correlation metrics proposed in Adrian (2007). In addition, the paper examines whether correlations and covariance are important determinants of future volatility via traditional time‐series regressions.

The paper finds that the majority of the broad hedge fund investment strategies incurred record level losses and gains during the 2007‐2010 period. In addition, it finds that the crisis period was preceded by high correlations, attributed primarily to a rise in cross‐sectional hedge fund covariances. However, during the crisis period, a decrease in average correlations, stemming from an increase in hedge fund volatility, is documented. The time‐series regressions are supportive of a strong relationship between cross‐sectional covariances and subsequent volatility, suggesting that systemic risk occurs in the hedge fund sector when returns move significantly in dollar terms.

This study is one of the first investigations that focus on the comovement and volatility of hedge fund index returns during the US financial crisis of 2007‐2010.

The purpose of this paper is to examine the possibility of creating hedge funds “clones” using liquid exchange traded instruments.

Authors analyze the performance of fixed weight and extended Kalman filter generated clone portfolios (EKF) for 14 hedge fund strategies from February 2004 to September 2009. EKF approach does not indeed impose any normality constraints on the error terms which allow the filter to find the optimal recursive process by itself. Such models could adjust even faster to sudden shifts in market conditions vs a standard Kalman filter.

For five strategies out of 14, this work finds that EKF clones outperform their corresponding indices. Thus, for certain strategies, the possibility of cloning hedge fund returns is indeed real. Results should be however considered with caution.

This paper suggests that the most important benefits of clones are to serve as benchmarks and to help investors to better understand the various risk factors that impact hedge fund returns.

Rather than using fixed‐weight and rolling windows approaches (as Hasanhodzic and Lo), this work considers an extended version of the Kalman filter, a computational algorithm that better captures the time changing dynamics of hedge fund returns. Also, in order to be practical, this research considers investable factors and that the models themselves could not be constant over time.