Hedge Fund Performance Evaluation: A Stochastic Discount Factor Approach

Journal of Derivatives AccountingVol. 01, No. 02, pp. 187-194 (2004) ARTICLESNo AccessTHE GLOBAL MACRO HEDGE FUND CEMETERYMASOUD ASGHARIAN, FERNANDO DIZ, GREG N. GREGORIOU, and FABRICE ROUAHMASOUD ASGHARIANDepartment of Mathematics and Statistics, McGill University, Montreal, QC, Canada Search for more papers by this author , FERNANDO DIZWhitman School of Management, Syracuse University, Syracuse, New York, USA Search for more papers by this author , GREG N. GREGORIOUSchool of Business and Economics, State University of New York, 101 Broad Street, Plattsburgh, New York 12901, USACorresponding author. Search for more papers by this author , and FABRICE ROUAHFaculty of Management, McGill University, Montreal, QC, Canada Search for more papers by this author https://doi.org/10.1142/S0219868104000154Cited by:3 PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail AbstractThis study estimates the survival time distribution of the global macro class of hedge funds. We use methods of survival analysis to investigate how performance and nonperformance features of hedge funds could affect their lifetimes. We find that the effect of monthly returns and average assets under management is significant and has an impact on survival. We further discover that between 6 and 8 years of existence there is a sharp increase in the hazard of failure, which is most likely attributed to the Russian Ruble crisis of August 1998. The assumption by the media that many global macro hedge funds have been accused of failing due to their excessive leverage may in fact be wrong.Keywords:Hedge fund survivallife table estimatorKaplan–Meier estimator References Amin, G. S. and H. Kat (2002). Welcome to the dark side: hedge fund attrition and survivorship bias over the period 1994–2001. Working Paper, University of Reading, ISMA Centre, Reading, UK . Google Scholar Barès, P. A., R. Gibson and S. Gyger (2001). Style consistency and survival probability in the hedge fund industry. Working Paper, Swiss Federal Institute of Technology Lausanne EPFL and University of Zurich . Google Scholar Barry, R. (2002). Hedge funds: a walk through the graveyard. Working Paper, Applied Finance Center, Macquarue University, Sydney, Australia . Google Scholar Baquero, H., Horst, ter J. and M. Verbeek (2002). Survival, look-ahead bias and the performance of hedge funds. Working Paper, Erasmus University and Tilburg University, The Netherlands . Google Scholar Boyson, N. (2002). How are hedge fund manager characteristics related to performance, volatility and survival. Working Paper, Ohio State University . Google Scholar Brooks, C. and H. Kat (2001). The statistical properties of hedge fund index returns and their implications for investors. Working Paper, University of Reading ISMA Centre, Reading, UK . Google ScholarS. J. Brown, W. N. Goetzmann and J. Park, Journal of Finance 56(5), 1869 (2001), DOI: 10.1111/0022-1082.00392. Crossref, Google ScholarD. R. Cox, Journal of the Royal Statistical Society, Series B 34(2), 187 (1972). Google ScholarM. J. Howell, Journal of Alternative Investments 4(2), 57 (2001), DOI: 10.3905/jai.2001.319011. Crossref, Google Scholar Jen, P., C. Heasman and K. Boyatt (2001). Alternative asset strategies: early performance in hedge fund managers. Lazard Asset Management, London, UK . Google Scholar J. D. Kalbfleisch and R. L. Prentice , The Statistical Analysis of Failure Time Data , 2nd edn. ( John Wiley & Sons , New York, NY , 2002 ) . Crossref, Google ScholarB. Liang, The Journal of Financial and Quantitative Analysis 35(3), 309 (2000), DOI: 10.2307/2676206. Crossref, Google Scholar FiguresReferencesRelatedDetailsCited By 3Global MacroZura Kakushadze and Juan Andrés Serur14 December 2018References and Additional Reading17 August 2016Global Macro Investing3 October 2015 Recommended Vol. 01, No. 02 Metrics History KeywordsHedge fund survivallife table estimatorKaplan–Meier estimatorPDF download

This article presents some new results on an unexplored dataset on hedge fund performance. The results indicate that hedge funds follow strategies that are dramatically different from mutual funds, and support the claim that these strategies are highly dynamic. The article finds five dominant investment styles in hedge funds, which when added to Sharpe’s (1992) asset class factor model can provide an integrated framework for style analysis of both buy-and-hold and dynamic trading strategies.

An Academic Response to the 'Hedge Fund Mirage'

The purpose of this chapter is to critically evaluate the methods used to examine hedge fund performance, review and synthesize studies that attempt to explain the inconsistencies associated with the performance of hedge funds and to attempt to compare the returns of hedge funds against more liquid investments. In fact, research related to hedge fund performance seems to have been focused on whether hedge fund managers manipulate their performance and what investors should think about this performance manipulation; however, recent studies have questioned whether this perceived performance manipulation is manipulation per se or something else. In general, researchers have used a number of different techniques to attempt to model hedge fund performance and the relative opacity and latency that is evident in the reporting of hedge fund returns. Nevertheless, the very nature of the structure of a hedge fund makes it difficult to mark the returns to market on a frequent basis and even if managers wanted their performance marked to market, which would unveil their positioning through time, the relative illiquidity and stale pricing associated with some of the investments that are held by hedge funds make pricing the hedge fund a difficult and somewhat pointless exercise. To this end, studies that attempt to analyze and evaluate aggregate performance for hedge fund returns have focused on identifying the true determinates of hedge fund performance, attempted to account for and explain the relative staleness of pricing in hedge fund returns, and to relate the performance of hedge funds to more liquid and transparent investments. This chapter offers key suggestions for financial market participants such as hedge funds managers, portfolio managers, risk managers, regulatory bodies, financial analysts, and investors about their evaluation and interpretation of hedge fund performance. In addition, this critical review chapter can benefit investors, portfolio managers, and researchers in the establishment of a yardstick for the assessment of hedge fund performance and the performance of assets that have stale pricing and are relatively opaque.

On the Performance of Hedge Funds

The search for methodologies that accurately measure performance and performance persistence continues to evolve. This is especially true for investment strategies such as hedge funds, which have been shown, in several instances, to not be normally distributed. In this article, we evaluate performance of hedge funds using conditional approaches and GMM. Unlike the Sharpe ratio or Jensen9s alpha, our results would still be valid even if hedge funds were not normally distributed. We use the CISDM hedge fund database for this study. We create three portfolios to measure performance: an Active portfolio (which consists of funds in the active database), a Dead portfolio (which consists of funds in the defunct database), and an All portfolio (which consists of funds in both the active and defunct databases). We find that while the Active portfolios show evidence of positive risk-adjusted returns in most cases, the Dead portfolios do not and only some of the All portfolios show evidence of positive risk-adjusted returns. The results are similar irrespective of whether we use Jensen9s alpha or conditional approaches. Our results point to two conclusions: one, the explanatory variables used in this study may not be able to capture the type of trading strategies followed by hedge fund strategies and, two, the estimated alphas are good estimates of the true alphas which are mostly due to managers9 skills and hence cannot be explained by naïve static or dynamic trading strategies. In our analysis of market timing models, we show that hedge fund managers in general lack market timing ability and fund level analysis is required to determine the few that do have market timing ability. The results also suggest that hedge fund returns have option-like properties and future research should include option-based factors in performance evaluation.

Investors are constantly searching for methods to generate value above passive investment techniques. Therefore, analysing the performance of hedge funds as compared to mutual funds, particularly in the wake of Covid-19, can aid investors in their investment decision-making process. Those investors who desire above-average returns, particularly in volatile market conditions place an expectation on hedge funds to be able to achieve higher performance during economic downturns, given that they are designed to mitigate risk and to take advantage of harsh financial market conditions. Monthly, secondary data were collected from 30 September 2018 to 31 August 2021 to analyse and compare the risk-adjusted performance of five hedge funds and five mutual funds in South Africa. Both hedge and mutual funds indicated higher risk-adjusted returns from the pre-Covid-19 period compared to during the pandemic. Hedge funds were found to have higher risk-adjusted returns than mutual funds during the Covid-19 period. The novelty of these results indicated that hedge fund managers can achieve higher returns for investors during extreme market events.

Measured correlations between hedge fund returns and world equities are currently very high, prompting some pundits to question the diversification benefits of hedge funds. We show that this correlation is a short-term phenomenon driven by the pursuit of absolute returns by hedge funds. Measured correlations provide a very limited understanding of the relationship between a dynamic trading strategy and passive investment benchmarks. We estimate the performance contributions of alternative risk factors and show that they drive the evolution of hedge fund correlations to traditional investments. In addition, we observe that the non-alternative components of hedge fund performance exhibit more stable relationships with traditional investments. Our analysis clearly refutes the hypothesis that hedge funds have lost their diversification benefits.

Performance Evaluation of Hedge Funds with Option-Based and Buy-and-Hold Strategies

Empirical evidence indicates that hedge funds differ substantially from traditional investment vehicles, such as mutual funds. Unlike mutual funds, hedge funds follow dynamic trading strategies and have low systematic risk. Hedge funds' special fee structures apparently align managers' incentives with fund performance. Funds with “high watermarks” (under which managers are required to make up previous losses before receiving any incentive fees) significantly outperform those without. Hedge funds provide higher Sharpe ratios than mutual funds, and their performance in the period of January 1992 through December 1996 reflects better manager skills, although hedge fund returns are more volatile. Average hedge fund returns are related positively to incentive fees, fund assets, and the lockup period.

This work aims to contribute to the literature on investment funds in emerging markets to address the portfolio composition and performance of Brazilian hedge funds under the manager's perspective. This is because in emerging countries an efficient allocation of assets in the portfolios of the funds is subject to different risk characteristics of the active participants of these portfolios, in addition to the composition of the portfolios be a possible explanation for the differences in performance of the funds. Moreover, from the perspective of the manager, the choice of the assets that make up their portfolios and the performance of the funds it manages, may be subject to the influence of special features such as: experience, amount of funds under management, manager location and managers who have better performance than your peers. So the problem that prompted this research was: which variables related to the manager affect the portfolio composition and performance of hedge funds? Therefore, the Brazilian hedge funds registered with the CVM were analyzed, considering free survival bias samples for the period from September 2009 to January 2016. The first sample included 6,659 funds with 327,270 monthly observations and the second involved 5,309 funds, with an equal number of observations as contemplated indicators for the period. Hypothesis tests were conducted by econometric techniques in Stata® software. The results showed that the composition of the portfolio is influenced by characteristics of managers, as experience, amount of funds under management, manager and location managers who have better performance than their peers. These features of the manager, the experience and the amount of funds under management are also important to explain the performance achieved by hedge funds, beyond this be explained by the allocation of fixed and variable income assets. It should be noted that, when considering the confidence interval of the coefficients of these variables, the composition of the portfolios (fixed and variable income) is presented as the main factor that helps to explain a potential change of the performance of Brazilian hedge funds.

PurposeThe purpose of this paper is to examine whether there is significant evidence that hedge fund managers engage in deceptive manipulation of their reported performance results.Design/methodology/approachA model of hedge fund performance has been developed using standard regression analysis incorporating dependent lagged variables and an autoregressive process. In addition, the extreme bounds analysis technique has been used to examine the robustness and sensitivity of the explanatory variables. Finally, the conditional influence of the global stock market’s returns on hedge fund performance and the conditional return behavior of the Hedge Fund Index’s performance have been explored.FindingsThis paper begins by identifying a model of hedge fund performance using passive index funds that is well specified and robust. Next, the lag structure associated with hedge fund returns has been examined and it has been determined that it seems to take the hedge fund managers two months to integrate the global stock market’s returns into their reported performance; however, the lagged variables were reduced from the final model. The paper continues to explore the smoothing behavior by conditioning the dependent lagged variables on positive and negative returns and find that managers are conservative in their estimates of positive performance events, but, when experiencing a negative result, they seem to attempt to rapidly integrate that effect into the return series. The strength of their integration increases as the magnitude of the negative performance increases. Finally, the performance of returns for both the Hedge Fund Index and the passive indices were examined and no significant differences between the conditional returns were found.Research limitations/implicationsThe results of this analysis illustrate that hedge fund performance is not all that different from the performance of passive indices included in this paper, although it does offer investors access to a unique return distribution. From a management perspective, we are reminded that we need to be cautious about hastily arriving at conclusions about something that looks different or feels different from everything else, because, at times, our preconceived notions will cause us to avoid participating in something that may add value to our organizations. From an investment perspective, sometimes having something that looks and behaves differently from everything else, improves our investment experience.Originality/valueThis paper provides a well-specified and robust model of hedge fund performance and uses extreme bounds analysis to test the robustness of this model. This paper also investigates the smoothing behavior of hedge fund performance by segmenting the returns into two cohorts, and it finds that the smoothing behavior is only significant after the hedge funds produce positive performance results, the strength of the relationship between the global stock market and hedge fund performance is more economically significant if the market has generated a negative performance result in the previous period, and that as the previous period’s performance becomes increasingly negative, the strength of the relationship between the Hedge Fund Index and the global stock market increases.

Hedge fund strategies, performance &diversification: A portfolio theory & stochastic discount factor approach

Purpose This paper aims to determine if hedge fund performance is related to short-run initial public offering (IPO) success and if it is a better predictor of short-run IPO success than market performance. Design/methodology/approach This paper utilizes the event study metric that computes monthly returns for hedge funds and Center for Research in Security Prices (CRSP) market indices. These returns are used in a regression model with dependent variables consisting of measures of short-run IPO success (SUC). We use the Vuong’s likelihood ratio test to compare the impact of hedge funds and market indices on initial public offering success. Findings This paper offers two new major findings. First, hedge fund performance prior to and during the IPO month (month 0) manifest a significant negative association with all measures of short-run IPO success. Second, whereas market returns also exhibit a negative association with IPO success, we show that hedge fund returns have a greater negative impact than market returns. Research limitations/implications This paper does not have information on which individual hedge funds have a greater negative impact on short-run IPO success but only the hedge fund industry as a whole. Practical implications Stronger hedge fund performance around IPOs can be detrimental to their success. Social implications Hedge funds are a stronger force than market forces in influencing IPO success. Originality/value This paper is the first study to document the potential influence of hedge fund performance on the success of a security offering and to compare this performance with market performance.

Hedge Funds summarizes the academic research on hedge funds and commodity trading advisors. The hedge fund industry has grown tremendously over the recent years. According to some industry estimates, hedge funds have increased from USD 39 million in 1990 to about USD 972 million in 2004 and the total number of hedge funds has gone up from 610 to 7,436 over the same period. At the same time, hedge fund strategies have changed significantly. In 1990 the macro strategy dominated the industry while in 2004 the equity hedge strategy had the largest share of the market. There has also been a shift in the type of investor in hedge funds. In the early 1990s the typical investor was a high net-worth individual investor, today the typical investor is an institutional investor. Thus, the hedge fund market has not only grown tremendously, but the nature of the market has changed. Despite the enormous growth of this industry, there is limited information available on hedge funds. As a result, there is a need for rigorous research from both the investors’ and regulators’ point of view. Investors need research to better understand their investment and their risk exposure. This research also helps investors recognize the extent of diversification benefits hedge funds offer in combination with investments in traditional asset classes, such as stocks and bonds. Regulators can use this research to identify situations where regulation may be needed to protect investors’ interests and to understand the impact hedge funds trading strategies have on the stability of the financial markets. The first part of Hedge Funds summarizes hedge fund performance, including comparisons of risk-return characteristics of hedge funds with those of mutual funds, factors driving hedge fund returns, and persistence in hedge fund performance. The second part reviews research regarding the unique contractual features and characteristics of hedge funds and their influence on the risk-return tradeoffs. The third part reviews the role of hedge funds in a portfolio including the extent of diversification benefits and limitations of standard mean-variance framework for asset allocation. Finally, the authors summarize the research on the biases in hedge fund databases.