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Performance and Risk Reporting
Review of Current Research
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Hedge Fund Performance
C. Brooks, A. Clare, and N. Motson. Brooks, Clare, and Motson look into whether an examination of pre-fee (gross) or post-fee returns (net) is more appropriate to an analysis of hedge fund risk and performance. In addition to management fees, which usually range from 1 to 3% of assets under management, hedge funds charge incentive fees. Incentive fees depend on profits, not on assets under management, and are charged if the return clears a hurdle and if the fund value is above a high-water mark. More...
27/08/08

Hedge Fund Performance
J. Hasanhodzic and A.W. Lo. Due to the very frequent criticism aimed at hedge funds, such as their lack of transparency, lack of liquidity or excessive fees, the replication of hedge fund returns is receiving increasing interest from academics. Kat and Palaro, for example, have introduced a copula-based approach. However, Hasanhodzic and Lo choose a more traditional approach based on a linear regression model. They argue that the copula-based approach fails as it is “more complex than the hedge fund strategies they intend to replicate.” More...
02/11/06

Hedge Fund Performance
S. Hossain, L. T. P. Nguyen, M. O. Sy, and C. M. Yu. The measure of performance persistence attempts to answer the following question: do winners and losers repeat? While an extensive literature is now available on hedge fund performance persistence, the study by Hossain, Nguyen, Sy, and Yu has two specificities. First, it focuses on Asian hedge funds. Second, it takes methods that other studies have used in two-period frameworks and uses these methods in a multi-period framework. Theoretically, a multi-period framework has the advantage of reducing the likelihood of observing persistent “hot hands” that are in fact the result of chance. More...
10/04/08

Hedge Fund Performance
P. Jylhä.Misreporting return is a type of fraud in which the manager intentionally reports higher-than-actual returns. In a previous study by Bollen and Pool (2009) {1}, attracting capital flows turned out to be the main motive for misreporting. In this study, Jylhä deals with this issue from the perspective of time-varying incentives to misreport returns. The goal is to extend Bollen and Pool's analysis by “studying the factors that affect fund managers’ misreporting behaviour”. The author examines the relationship between hedge fund managers’ propensity to misreport and the following time-varying proxies: net capital flows into the funds, the fund age, and the strength of the fund’s flow-performance relation—what Jylhä terms “managerial incentives”—and the protection of the fund's shareholders from dilution when it receives a large redemption or subscription. More...
07/01/11

Hedge Fund Performance
A. Grecu, B. G. Malkiel, and A. Saha. Why do hedge funds stop reporting performance? According to Grecu, Malkiel, and Saha, there are two possible explanations. First, funds stop reporting when they underperform their peers. Second, they stop when they do not need to attract additional capital. Through performance comparisons, hazard rate computations, and the identification of factors increasing the risk of reporting failure, the authors attempt to determine the more likely of the two possible explanations. More...
06/12/07

Hedge Fund Performance
S. Darolles, C. Gouriéroux. Gouriéroux and Darolles propose a methodology to compute Sharpe performance measures for hedge fund rankings. They present a conditionally fitted Sharpe performance measure, so called because it is an “investor driven” performance measure. In other words, it is an attempt to take into account, for example, the initial holding or the investment horizon of the investor. Each investor could therefore have his own fund ranking, depending on his investment environment. More...
10/12/08

Hedge Fund Replication
N. Papageorgiou, B. Remillard and A. Hocquard. The authors propose an extension of the payoff-distribution approach, one of three possible replication approaches, along with the factor-based and rules-based approaches. The authors propose a modified version of Kat and Palaro’s method, arguing that it remedies some of the shortcomings. In their view, one of the weaknesses of Kat and Palaro’s method comes from the use of a Black-Scholes framework that ignores the higher moments of the distributions, while “the hedge fund returns and traded assets are clearly non-normal”. More...
02/11/08

Hedge Funds
Y. Li and J. Mehran. In this study, Li and Mehran deal with the impact of age on the risk-taking of funds of hedge funds. The goal is to determine if new funds of hedge funds take more risk than their older peers. If there is a difference, does it have an impact on risk-adjusted performance? They analyse the period from 1995 to 2003. Each year, they define “new funds,” in contrast to “existing funds,” as funds with a return history of less than one year. 1,120 funds of hedge funds are studied. More...
07/05/09

Hedge fund performance
M. Eling. Eling focuses on relative performance persistence, that is, the persistence of the performance ranking in a sample of funds. In an extensive literature review, the author reports the methodologies and the results of twenty-five studies, the first published in 1998, of relative persistence. These studies differ by database provider, investigation period, time horizon (the persistence of monthly or yearly returns, for example), performance measure, and persistence measure. More...
08/02/09

Hedge fund performance
J. Joenväärä and H. Kahra. Can hedge funds’ characteristics be exploited to pick hedge funds? Is a characteristics-based strategy more profitable than a naïve strategy? Joenväärä and Kahra address these questions by using three hedge fund characteristics—managerial incentives, the length of the notice period, and fund size. This approach is derived from a previous paper by Brandt, Santa-Clara, and Valkanov (2008), who exploited the characteristics of equities to build an optimal equity portfolio. The authors’ work assumes that these characteristics impact hedge fund performance, as looked into by other studies that focus on explicit micro-factor models. More...
03/07/09

Hedge fund performance
M. Eling. Eling focuses on relative performance persistence, that is, the persistence of the performance ranking in a sample of funds. In an extensive literature review, the author reports the methodologies and the results of twenty-five studies, the first published in 1998, of relative persistence. These studies differ by database provider, investigation period, time horizon (the persistence of monthly or yearly returns, for example), performance measure, and persistence measure. Among the methods the papers use to measure persistence are the Cross Product Ratio test, the Chi-square test, the rank information coefficient, More...
08/02/09

Performance
M. Eling. An extensive body of literature documents the problems of hedge fund performance measurement and introduces new performance indicators that integrate these problems. In this paper, Eling analyses hedge fund returns by taking into account three well-known and distinct problems: the autocorrelation in hedge fund returns, survivorship bias, and the presence of extreme risks (namely the risk of asymmetry and fat-tail risk). Eling uses an Adjusted Modified Sharpe Ratio to adjust the performance for these problems. More...
23/02/06

Performance
J. Brunel. The increasing number of hedge funds and the growing amounts invested in this area are sources of debate on the hedge fund market's capacity to continue to generate high yields, in spite of a potential erosion of the various market opportunities. In this study, where the hedge fund universe is separated into three groups (traditional absolute return strategies, semi-directional strategies and managed futures), the author conducts a polynomial trend analysis of the alphas, on periods from December 1990 to June 2004 and from January 1993 to July 2003. He recognizes the possible limitations of his study due to the fact that the alpha is calculated in a “unidimensional” way, by subtracting the return of an “asset class benchmark”. More...
13/05/05

Performance
Greg N. Gregoriou. Survivorship bias is one of the potential biases that affect databases. Survivorship bias occurs if the database only contains information on “surviving” funds. Since this bias has a positive impact on returns, it is interesting to analyse the mortality of funds as part of performance measurement. In this paper, Gregoriou conducts a survival analysis that focuses on the market neutral and event driven strategies. The data used, provided by Zurich Capital Markets, covers the period from January 1990 to December 2001. It contains 325 live and 205 defunct market neutral funds and 142 live and 71 defunct event driven funds. The effects on survival time of several predictor variables are examined. These covariates are average monthly return, average millions managed, age, performance fees, management fees, leverage, redemption period and minimum purchase. More...
30/06/05

Performance
R.G. Ibbotson and P. Chen. Chen and Ibbotson propose a study on two subjects that are now well-documented in the hedge fund area, survivorship and backfill biases on the one hand, and the sources of returns on the other. The database, provided by TASS, covers January 1994 to March 2004. Funds of funds are excluded. The sample contains 2,054 live funds and 1,484 dead funds. In order to estimate the survivorship and backfill biases, six sub-samples are formed: live funds only with backfill data, live funds only without backfill data, live and dead funds with backfill data, live and dead funds without backfill data, dead funds only with backfill data and dead funds only without backfill data. More...
17/08/05

Performance
P.G. Perez. The author introduces this study by underlining that hedge fund return distributions simultaneously present “fat tails” and “occasional large negative returns”. Fat tails correspond to high kurtosis, and occasional large negative returns relate to negative skewness, in other words a departure from normality. Perez uses the Johnson (1949) translation system in order to approximate the empirical distributions of hedge fund returns. From January 1994 to February 2003, nine strategies are examined: Convertible Arbitrage, Dedicated Short Bias, Emerging Markets, Equity Market Neutral, Event Driven, Fixed Income Arbitrage, Global Macro, Long/Short and Managed Futures. These strategies are proxied by their respective CSFB/Tremont hedge fund indices. More...
31/05/05

Performance
C. Alexander and A. Dimitriu. In this paper, Alexander and Dimitriu examine a method for constructing hedge fund portfolios that display attractive “out-of-sample” return characteristics. For this purpose, the authors combine a minimum variance approach with a fund selection process based on alpha ranking. The aim is to show that it is preferable to select funds on the basis of the alpha and then optimize the portfolio via a minimum variance approach, rather than optimizing on alpha estimates, which implies model risk. More...
07/03/06

Performance
Martin H. Herzberg and Haim A. Mozes. This study deals with the persistence of the success of hedge fund strategies over time and the use of quantitative techniques to identify the best managers on the basis of past performance.The first step involves measuring the persistence of basic fund attributes. After that, the authors focus on four parameters that are liable to have an impact on the persistence of hedge fund performance: the length of the fund history, assets under management, the seasonability of returns and the redemption policy. The stability of the relationship between risk, return and the Sharpe ratio is also tested. As a final step, the authors develop a multifactor Hedge Fund Selection Model (HFSM), based on the following factors: return, maximum drawdown, standard deviation, assets under management, change in assets under management, Sharpe ratio, Sortino ratio, Calmar ratio and Sterling ratio. More...
09/12/03

Performance
Milind Sharma. This study introduces an innovative risk-adjusted performance measure that is especially designed to be applied to hedge funds. The new measure is called Alternative Investments Risk Adjusted Performance (AIRAP). The author justifies the proposition of a new risk-adjusted performance by the fact that the specific characteristics of hedge funds cause the current performance measures, namely the Treynor ratio, the Sortino ratio, the Jensen’s alpha and the Sharpe ratio, to be inappropriate. More...
12/12/03

Performance
N. M. Boyson. The aim of the paper is to analyse and explain the relationship between hedge fund manager age and risk-taking behaviour, and the impact of this relationship on the hedge fund returns. The risk-taking behaviour is studied in the light of agency costs and career concerns. More...
16/01/04

Performance
R.J. Davies, H.M. Kat, and S. Lu. Single strategy funds of hedge funds, by investing in funds that pursue a specific strategy, suffer from under-diversification in the context of a mean-variance analysis. The aim of the paper is to demonstrate that conclusions differ in a four-moment framework. More...
30/01/04

Performance
D. Capocci, A. Corhay and G. Hübner. Using a ten-factor combined model, Capocci, Corhay and Hübner analyse the performance of hedge funds over two successive sub-periods that correspond to bullish and bearish periods. The analysis is also carried out at a strategy level, and the contribution of each factor is studied. The persistence is tested in the final part of the paper. The advantage of this approach is to compare the behavior of hedge fund performance in two opposing stock market situations. More...
09/02/04

Performance
N. M. Boyson. An increasing amount of literature is being published on the question of the persistence of hedge fund performance, with a broad variety of test methods employed. The author deals with this subject through a new approach, introducing the notion of manager tenure. Moreover, style factors are added to the model. More...
11/02/04

Performance
R. McFall Lamm, Jr. While the issue of the optimal hedge fund portfolio has been mainly examined in terms of allocation to stocks, bonds and hedge funds, this paper analyses the optimal allocation to the different hedge fund strategies. The author highlights the importance of the asymmetric returns of hedge funds in the application of portfolio optimization techniques. More...
26/02/04

Performance
C. Bang Christiansen, P. Brink Madsen, M. Christensen. The authors use Principal Component Analysis (PCA) in order to identify relevant groups of hedge fund strategies. Because of the dynamic trading strategies of hedge funds, the authors choose a multi-factor model with buy-and-hold and option strategies. They follow Agarwal and Naik’s methodology (2000), by including Location factors (buy-and-hold strategy) and Trading Strategy factors (option-like strategies) in Sharpe’s multi-factor style model. The inclusion of the factors follows a step-wise procedure, which avoids the potential problems of multicollinearity. More...
16/10/03

Performance
J.-F. Bacmann and S. Scholz. The Sharpe ratio and the Sortino ratio, two very well-known performance indicators, exhibit some drawbacks when they are applied to hedge funds. In order to improve the risk approach in the context of hedge funds, Bacmann and Scholz compare the results of the Sharpe ratio and the Sortino ratio to the results obtained through two alternative measures, the Omega measure and the Stutzer index. More...
01/07/03

Performance
M. Getmansky, A. W. Lo, I. Makarov. The most common explanation for the presence of serial correlation in asset returns is a violation of the Efficient Markets Hypothesis. In an informationally efficient market, price changes must be unforecastable if they fully incorporate the expectations and information of all market participants. In the context of hedge fund returns, More...
30/04/03

Performance
F. Koh, W. T. H. Koh, M. Teo. This study approaches the issue of hedge fund return persistence from two interesting angles: the selected funds invest a significant portion of their assets in Asian countries, and the Kolmogorov-Smirnov multi-period test of persistence is used (the only previous paper to use this method to test hedge fund return persistence is by Agarwal and Naik (2000)). More...
28/07/03

Performance
Hossein Kazemi and Thomas Schneeweis. This study provides an interesting contribution to the search for an efficient hedge fund performance measurement model. According to the authors, the distributions of hedge funds returns are neither normal, nor identical through time. That is why the traditional performance evaluation models are not appropriate. Kazemi and Schneeweis propose a conditional model of performance: the Stochastic Discount Factor model. More...
01/04/03

Performance
R. Kouwenberg. This study investigates the benefit of investing in hedge funds for an uninformed and passive investor, holding stocks and bonds. In order to take into account the non-normality of hedge funds return distributions, after evaluating its effects, Kouwenberg uses an alpha with a power utility function and an extended model with option selling strategies. The author provides computation of the alpha for each strategy and finally tests the persistence of the hedge fund returns. More...
30/04/03

Performance
V. Agarwal, N.D. Daniel, N.Y. Naik. Agarwal, Daniel and Naik examine the determinants of money-flows and performance, for individual hedge funds and funds of hedge funds, from January 1994 to December 2000. This well-documented study presents several new findings, following two different approaches. The first approach involves investigating the possible determinants of money-flows. This approach is based on the assumption that investors recognize the importance of some factors to invest in individual hedge funds and funds of funds. The second approach involves investigating the impact of flows, size and incentives on the future performance and on the persistence in future returns. It allows the question of economies of scale to be dealt with. More...
06/10/03

Performance
M.J. Howell. This study discusses the benefits of investing in hedge funds of a specific maturity. Young hedge funds are usually defined as those offering a track record of less than three years. The author sorts the funds contained in the database used into deciles according to their maturity, and compares the returns of the youngest hedge funds to the whole sample median and to the returns of the oldest hedge funds. Non-adjusted returns and returns adjusted for the risk of failure are computed. More...
18/07/03

Performance
B. Gupta, B, Cerrahoglu and A. Daglioglu. On the assumption that hedge fund managers pursue dynamic trading strategies, the induction of time variation to Jensen’s model (1968) is a potential source of a more accurate estimation of the parameters. A linear relationship between Beta and a set of mean zero information variables available at time t-1 enables a conditional performance evaluation model, in contrast to static models, to be obtained. More...
19/06/03

Performance
Greg N. Gregoriou, Fabrice Rouah. The existence of a relationship between asset size and hedge fund performance is interesting for two reasons. For the investor, it’s about taking into account the size of the fund before investing. For the fund manager, it concerns the maximal asset size he will choose. The authors deals with the impact of size on hedge fund performance by carrying out statistical tests. More...
24/02/03

Performance
B. Liang. Unlike previous studies on alternative investment vehicles, Liang examines Commodity Trading Advisors (CTAs), hedge funds and funds of hedge funds as three distinctive investment classes. The distinction is due to the dramatic differences between the classes. The trading strategies, regulations and correlation structures of CTAs and hedge funds are different. The fee structures of funds of funds and hedge funds are different. The author chooses a portfolio approach to investigate the performance and risk characteristics of the three groups. More...
14/05/03

Performance
Harry M. Kat and Joëlle Miffre. Static asset pricing models imply that the risk and performances are constant over time. Due to investment decisions based on public information and dynamic trading strategies, in the case of hedge funds, static models present the risk to be misspecified. If the risk profile is modified over the calculation period, it can have strong impact on the abnormal performance. This assumption is in opposition with several studies which use multi-factor asset pricing models, where the risk exposure remains constant. That is why the authors attempt to improve the statistical significance of the performance evaluation, by constructing a time-varying expected return asset pricing model. More...
12/06/03

Performance
P.-A. Barès, R. Gibson and S. Gyger. The authors examine the persistence of hedge fund performance in three different ways: the relative performance persistence of individual hedge funds, the performance persistence of hedge fund portfolios on a "raw" performance basis, and the performance persistence of hedge fund portfolios on a risk-adjusted basis. More...
23/07/03

Performance
Les Gulko. The author presents an ex-post performance evaluation method that takes the return and volatility of the hedge funds and their correlations with stocks and bonds into account, in the Markowitz mean-variance framework. The advantage of this method is that it gives the contribution of a hedge fund style to a market portfolio. More...
04/04/03

Performance
H. M. Kat, F. Menexe. The fact that many allocations to hedge funds are based on their track record implies that investors believe that performance persists. This study, which considers two main aspects, is interesting. Firstly, the authors distinguish between two performance persistence approaches: the persistence in the risk-adjusted returns and the persistence in the risk profile. Kat and Menexe base their investigations on the second approach. Secondly, they distinguish between "persistence" and "predictability": the persistence of a risk profile does not imply that it can be predicted. More...
14/05/03

Performance
V. Agarwal, N.Y. Naik. Hedge funds capture risk premia linked to dynamic trading strategies or spread-based strategies, and they can take both long and short positions in securities. That's why hedge funds can offer exposure to risk-factors that traditional long-only strategies cannot. Thus, the main goal of the study is to extend the understanding of hedge funds risks to a wide range of equity-oriented hedge fund strategies. More...
01/04/03

Performance
Guillermo Baquero, Jenke ter Horst, Marno Verbeek. This paper provide an empirical analysis of persistence in the performance of U.S. hedge funds over the period 1994-2000. The authors take the look-ahead bias into account by using a correction method. Performance persistence is examined for both raw and risk-adjusted returns. More...
01/04/03

Performance
Bing Liang. Even if convenient performance indicators - associated to well-specified models - are used, performance measurement which is based on an inaccurate database is biased in all cases. The choice of an accurate database, before investigating the problems of the return calculation, is of major interest in the context of the hedge fund industry. The study focuses on two well-known databases marketed by TASS Management Limited and U.S. Offshore Fund Directory. More...
15/07/03

Performance
Paul D. Kaplan and James A. Knowles. Kappa, introduced by Kaplan and Knowles, is presented as a generalized downside risk-adjusted performance measure. "Generalized" means that this indicator can become any risk-adjusted return measure, through a single parameter. The authors illustrate that Kappa is a generalized performance measure by an application on the Sortino ratio and Omega. More...
10/03/04

Performance
R. M. Ennis and M. D. Sebastian. The authors firstly debate the representativeness of indexes in the hedge fund industry. They argue that "after-the-fact" indexes, i.e. indexes constructed from marketed databases, display overstated returns. Funds of Funds, which display an "actual" measure (as opposed to "after-the-fact" indexes) of hedge fund performance, are more representative. In order to analyse the market exposure of the HFR Fund of Funds index, Ennis and Sebastian use an Effective Style Mix (ESM) benchmark, which refers to the return based-style analysis introduced by Sharpe (1992). Concerning performance, due to the specific characteristics of hedge funds, as far as performance is concerned, a Sharpe ratio adjusted for autocorrelation is used. The authors also focus on pre and post-peak performance, to study the correlation of hedge fund returns to the stock market. More...
04/11/03

Performance
N. Posthuma and P. J. van der Sluis. The authors concentrate on the backfill bias and its implications for hedge fund returns. This bias is due to the backfilling performed by data providers for hedge funds that decide to report only when they obtain good returns. It generally leads to overestimated returns. The authors highlight the fact that after the correction of the backfill bias biases can remain because of lockup periods and fund liquidation. Consequently, three scenarios are developed. The first scenario is based on the hypothesis that lockup periods and fund liquidation have no impact on the returns, i.e. the funds concerned have no additional negative returns outside the database: therefore the extra return is zero. The second and third scenarios are based on the hypothesis that the two characteristics have an impact on the returns: consequently the extra negative return is respectively 50% and 100% in the month the funds stop reporting. More...
21/11/03

Performance
L. Favre and A. Ranaldo. The authors deal with the traditional CAPM, and its possible extensions, from an interesting point of view, that of coskewness and cokurtosis. Coskewness and cokurtosis are the skewness and kurtosis of a given asset analysed with the skewness and kurtosis of the reference market. For example, hedge funds with a significant level of coskewness will increase or decrease market skewness if added to the market portfolio. Similarly, the insertion of hedge funds with a positive cokurtosis coefficient will add kurtosis to the market portfolio. More...
14/11/03

Performance
K. Chen and A. Passow. Chen and Passow propose a multi-factor model to select hedged equity funds (long-short equity, dedicated short bias and equity market neutral). It mainly consists of eliminating the funds that exhibit large exposure to one or more risk factors. The aim is to obtain higher risk-adjusted return than the whole long-short hedge fund universe. More...
26/03/04

Performance
Hung-Gay Fung, Xiaoqing Eleanor Xu and Jot Yau. The calculation of risk-adjusted excess returns can be impacted by several biases. Firstly, the performance of a group of hedge funds has to be compared to an index related to the same style. That is why this paper focuses on the equity-based style. Secondly, the presence of stale prices has to be taken into consideration. Therefore Dimson’s approach (1979) is used. Thirdly, skewness and kurtosis have to be taken into account. This is done by the authors through a modified single-factor CAPM. More...
07/05/04

Performance
Greg N. Gregoriou and Jean-Pierre Gueyie. Applied to the hedge fund universe, traditional performance measures that assume a mean-variance framework suffer from some limitations, mainly due to the non-normality of returns. The authors propose an improvement to the original Sharpe ratio through the use of the modified Value-at-Risk (MVaR). The new performance measure is named the Modified Sharpe ratio. More...
11/06/04

Performance
C. De Souza and Suleyman Gokcan. The selection of individual managers is a key step in hedge fund investing. Indeed the risk and return dispersion in the same strategy highlights the heterogeneity among managers, to differing degrees among strategies. Consequently, strategy factor risk is not a sufficient basis to construct a portfolio of hedge funds. Moreover, a simple diversification of fund-specific risk via an increase in the number of funds can engender an increase in the exposure to market risk factors. Instead of diversifying fund-specific risk, the authors advocate reducing it through manager selection. Here the authors focus on quantitative features, namely performance persistence, due diligence and ongoing monitoring. More...
05/07/04

Performance
Greg N. Gregoriou. Survivorship bias is one of the potential biases that affect databases. Survivorship bias occurs if the database only contains information on 'surviving' funds. Since this bias has a positive impact on returns, it is interesting to analyse the mortality of funds as part of performance measurement. In this paper, Gregoriou conducts a survival analysis that focuses on funds of hedge funds (henceforth FoHFs). The data used, provided by ZCM, covers the period from January 1990 to December 2001. It contains 344 live and 191 defunct funds. More...
23/07/04

Performance
Greg N. Gregoriou. It is now well-known that the Sharpe ratio, which is considered a traditional performance measure, introduces a bias when the distribution of returns is not normal, because the use of standard deviation as a measure of the risk exposure is inadapted. The tail risk is underestimated when the variance is used, and consequently the Sharpe ratio overestimates performance. To alleviate these difficulties in considering risk exposure, the value-at-risk measure (henceforth VaR) has received increasing acceptance. However, the normal VaR, considering only the mean and the standard deviation, is not a relevant alternative. More...
02/11/04

Performance
Y. F. Yao, B. Clifford and R. Berens. This study is dedicated to the leading hedge fund strategy in terms of assets under management, namely long/short equity. Depending on the number of sectors in which long/short equity hedge fund managers invest, they are classified as specialists or generalists. A sector specialist invests in one specific sector, while a sector generalist invests in several sectors. The authors propose to compare generalists and specialists according to their diversification benefits and their risk-adjusted performance. They underline the need to use distinct benchmarks, because the investment universe differs: a broad market index is required for generalists (in the paper the HFR Equity Hedge Fund Index is used, and their long-only counterpart is the Russell 3000 Index), in contrast with specialists, which have to be associated with the appropriate sector market indices... More...
27/12/04

Performance
K. A. Clark and K. Winkelmann. Performance can be viewed as the combination of the exposure to market moves (passive risk) and manager skill (active risk). The information ratio is the ratio of the average alpha to the residual risk, where residual risk is the standard deviation of alpha over time. The formulation of alpha as the product of the information ratio and the residual risk permits two sources of alpha to be highlighted: the manager’s investment skill (information ratio) and the exposure to active risk (residual risk). The authors use data from the CISDM hedge fund index to develop a risk budgeting process. Six strategies are studied, namely market neutral, fixed income arbitrage, event driven, equity long/short and tactical trading, over the period from January 1994 to November 2003. More...
11/02/05

Performance
R. Kosowski, N.Y. Naik and M. Teo. This paper examines hedge fund returns from the angle of a bootstrap method, in order to test whether they can be explained by luck alone. A short performance persistence analysis, focused on alpha, is also conducted. The database contains datasets provided by CISDM, HFR, MSCI and TASS. It gives a more complete picture of the hedge fund universe. The period is from January 1991 to December 2002. More...
07/10/04

Performance
Bernd Scherer. The determination of confidence intervals is a non-negligible step in a performance analysis problem, in addition to the calculation of risk-adjusted ratios. However, confidence bands are difficult to determine in the presence of arbitrary risk-adjusted returns, sample sizes and distribution. More...
31/10/04

Performance
C. Alexander and A. Dimitriu. Alexander and Dimitriu study switching hedge fund strategies. This involves the fact that return distributions and/or exposures to risk factors and/or alphas depend on the regime, which could be the market environment. The following example of switching is given: a long/short equity strategy is long during bull markets and short during bear markets. According to the authors, linear models cannot take switching strategies into account. They propose the use of a Markov switching model. Two types of models are used: a single factor model and a two-factor model. More...
10/08/05

Performance
R.J. Surz. Surz examines the application of Monte Carlo Simulation (henceforth MCS) to hedge funds, by testing the hypothesis “Performance is good”. MCS is presented as an alternative to traditional performance measurement approaches. According to the author, traditional peer groups and indexes cannot be used in the hedge fund area. The test is conducted as follows: the actual performance is compared to all the possible outcomes previously evaluated (“what could have happened”). More precisely, the possible outcomes correspond to the possible portfolios that a hedge fund manager could have constituted. These portfolios are created on the basis of the investment parameters followed by the hedge fund manager, for example the investment style, the long and short positions, the fees and the leverage. The author applies the MCS by focusing on the Market Neutral strategy. More...
08/06/05

Performance
Lars Jaeger. Jaeger argues that modelling returns of hedge fund indices can give reliable results, in spite of the shortcomings of the indices. This is due to the fact that the shortcomings only impact absolute performance measurement, and not the risk characteristics. To model each hedge fund strategy, a macro explicit factor model is used, including linear and non-linear factors. For each strategy, the dependent variable is the corresponding return of the hedge fund index, provided by Hedge Fund Research. Returns are regressed from January 1994 to December 2004. An autocorrelation factor is added to take into account persistent price lags in the valuation of hedge funds. The regressions result in a wide range of R². More...
29/10/05

Performance
Ammann and Moerth. Ammann and Moerth study the relationship between fund size and performance. The conclusions could be useful in constructing an explicit micro-factor model, where fund characteristics are selected as return factors. A significant relationship between fund size and performance can lead to fund size being included in an explicit micro-factor model. More...
09/11/05

Performance
H. Kazemi and T. Schneeweis.Stale prices occur when managers, because they trade in illiquid securities, have the ability to smooth prices. The consequence is underestimated volatility, resulting in overestimated risk-adjusted returns. More...
14/10/04

Performance
Gordon H. Dash and Nina Kajiji. Two leading approaches can be followed to predict returns: a return-level approach and a classification-based approach. The first method involves predicting a future return level, while the second method involves predicting the direction of the returns. The results of three different test algorithms are presented: the Kajiji radial basis function (henceforth RBF) algorithm, the SPPS RBF algorithm and the Statsoft RBF algorithm. The study focuses on the monthly returns of 13 hedge fund indexes provided by CSFB/Tremont, covering the period from January 1994 to December 2002. The Dedicated Short Bias index exhibits the highest volatility. The Equity Market Neutral index displays the lowest volatility. A Shapiro-Wilk test shows that returns are not normally distributed. More...
04/01/05

Performance
Alexander M. Ineichen. Returns that are not normally distributed are asymmetric. According to Ineichen, when the investment process is not driven by market benchmark but by P&L, risk is defined in absolute terms, and investors prefer a right-skewed distribution over a normal distribution. Hedge fund managers that are sector specialists manage a special type of long/short equity fund and typically have a long bias, which means that there is a high correlation to the sector in which they invest. The absolute drawdowns induced by high correlations defeat the notion of capital preservation. Consequently, the goal is to maximise the P in P&L, and to avoid the L. Three sectors are studied, More...
07/12/04

Performance
J. Loeys and L. Fransolet. Market opportunities can be exploited in two ways: exploiting structurally high risk premia and exploiting temporary market opportunities. In both cases, several high-return opportunities are identified by the authors. Concerning the structural exploitation of high risk premia, there are term premia at the short end of the interest rate curve, credit spreads at the short end of the curve, the mispricing of BBs, the forward bias in foreign exchange, equity anomalies and mispricings in options. More...
28/01/05

Performance
V. Karavas, H. Kazemi, G. Martin and T. Schneeweis. In this paper, Karavas, Kazemi, Martin and Schneeweis study the impact of leverage on risk and return in the hedge fund universe. They examine 6 strategies, namely Convertible Arbitrage, Equity Hedge, Event Driven, Distressed Securities, Merger Arbitrage and Equity Market Neutral, on the basis of CISDM and TASS databases, from January 2000 to March 2003 (39 monthly observations). After dividing the sample into two equal-weighted indexes that represent respectively funds with reported leverage information and funds which do not report leverage information, the Welch t-test and the Kolmogorov-Smirnov test exhibit that for the six strategies the distributional characteristics do not differ between the two indexes. More...
06/05/05

Performance
Gaurav S. Amin and Harry M. Kat. This study examines the appropriateness of including hedge funds in a portfolio of stocks and bonds, on the basis of a mean-variance analysis and a mean-variance-skewness analysis. A mean-variance-skewness analysis allows the specific features of the return distribution of the hedge funds to be taken into account. More...
22/10/03

 
   
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