Hedge Fund Performance Research Articles

HEDGE FUNDS: RISK AND PERFORMANCE

This paper models hedge fund exposure to risk factors and examines time-varying performance of hedge funds. From existing models such as asset-based style (ABS)-factor model, standard asset class (SAC)-factor model, and four-factor model, we extract the best six factors for each hedge fund portfolio by investment strategy. Then, we find combinations of risk factors that explain most of the variance in performance of each hedge fund portfolio based on investment strategy. The results show instability of coefficients in the performance attribution regression. Incorporating a time-varying factor exposure feature would be the best way to measure hedge fund performance. Furthermore, the optimal models with fewer factors exhibit greater explanatory power than existing models. Using rolling regressions, our customized investment strategy model shows how hedge funds are sensitive to risk factors according to market conditions.

Gamma Trading Skills in Hedge Funds

This paper explores the gamma trading, timing and managerial skills of individual hedge funds across categories. We replicate the non-linear payoffs of hedge funds with traded options, with the option features being endogenously defined in our replication model. On top of providing a flexible tool to create individual benchmarks for the payoff curvature of hedge fund, the model helps assigning hedge fund styles into three categories: directional with market timing skills, non-directional and market timers. Overall, our empirical results show that, on 30% of replicated funds in our sample (10,958 funds), there is no evidence of the presence of selection skills once a fund performance is adjusted with respect to the option-based benchmark and the traditional option-based factors of Agarwal and Naik (2004). This research has an incremental potential to stimulate additional research in the field of hedge funds performance replication through passive strategies.

Persistence of Hedge Fund Returns and Fee-Aware Portfolio Construction

The author presents an empirical study of the persistence of manager returns for two core hedge fund categories: equity long–short and macro/managed futures. The author finds that although beta to core risk factors and volatility of excess returns were indeed persistent over time for these strategies, it appeared to be difficult to reliably predict outperformance of one fund over another based on past results. The author suggests portfolio construction assumptions that are consistent with these empirical findings and incorporate another feature of hedge fund performance that is highly persistent: manager fees. The author believes that the suggested portfolio construction process offers several advantages for institutional investors: It is robust because it is anchored in those properties of hedge fund historical returns that are persistent, and it allows incorporation of active views and hedge fund manager fees into portfolio decisions in a transparent and consistent manner.

Cryptocurrency Hedge Fund Performance: Risks and Challenges

This discussion paper considers the risks and challenges posed to the hedge funds that are dedicated to investment mandates in the cryptocurrency space, including through the haemorrhaging loses faced in the wake of asset value declines across the entire asset class.

Alternatives to Alternative Assets: Assessing S&P 500 Index Option Strategies as Hedge Fund Replacements

Hedge funds should deliver good risk-adjusted returns and provide diversification for investors’ portfolios. However, the performance of hedge funds has deteriorated in recent years and many investors may not find investment in hedge funds suitable, due to the high costs, illiquidity, and lack of transparency. The focus of this study is to examine whether equity index option-based strategies may deliver the same coveted ideal hedge fund return characteristics, that is, good risk-adjusted returns, mitigated risk measures, and added diversification. A total of seven S&amp;P 500 Index-based generic option-writing strategies, named CP100 to CP0, are analyzed and compared with a comprehensive set of fourteen Credit Suisse hedge fund indexes using volatility or beta as matching metrics. The three series of CP100, CP80, and CP50, can be viewed as a solid suite of liquid alternatives to hedge funds. They match the fourteen Credit Suisse hedge fund indexes on beta levels, but deliver better risk-adjusted returns. Their annual returns and risk measures are better than or on par with the hedge fund indexes, except for the Credit Suisse Global Macro Index, which may be matched by a levered version of the CP100 option strategy. This suite of three option strategies are transparent, liquid, inexpensive, and easy to implement. They can achieve the same goals of hedge funds: attractive risk-adjusted returns, subdued risks, and added diversification. They may play multiple and important roles in institutional investors’ portfolios. <b>TOPICS:</b>Real assets/alternative investments/private equity, mutual funds/passive investing/indexing, options, performance measurement

Practical Applications of Man vs. Machine: Comparing Discretionary and Systematic Hedge Fund Performance

<h3>Practical Applications Summary</h3> Quantitative investing, which deploys machine learning and other algorithms, now more or less dominates financial markets. In this environment, it9s useful to step back and compare the performance and risk exposures of discretionary and systematic hedge fund managers. Many allocators to hedge funds, large and small alike, avoid allocating to systematic funds, either partially or entirely, believing them to be difficult to understand, to offer less transparency, and to deliver worse performance due to the use of data from the past. These reasons seem to be consistent with “algorithm aversion”—a distrust of systems. In their article Man vs. Machine: Comparing Discretionary and Systematic Hedge Fund Performance, published in the Summer 2017 issue of <b><i>The Journal of Portfolio Management</i></b>, Campbell R. Harvey, Sandy Rattray, Andrew Sinclair, and Otto van Hemert compare the past performance of systematic funds with their discretionary counterparts. They show that, after adjusting for volatility and factor exposures, the lack of confidence in systematic funds is not justified. <b>TOPICS:</b>Real assets/alternative investments/private equity, statistical methods, performance measurement, manager selection

Alternatives to Alternative Assets: Applications of S&P 500 Index Option Based Strategies

Hedge Funds should deliver good risk-adjusted returns and provide diversification for investors’ portfolios. However, the performance of hedge funds deteriorated in recent years and many investors may not be suitable to invest in hedge funds due to their high costs, illiquidity, and lack of transparency. The focus of this study is to examine whether equity index option-based strategies may deliver the same coveted ideal hedge fund return characteristics, i.e., good risk adjusted returns, mitigated risk measures, and added diversification. A total of seven S&P 500 Index based generic option-writing strategies, named CP100 to CP0, are analyzed and compared with a comprehensive set of 14 Credit Suisse hedge fund indexes using volatility or beta as matching metrics. The three series of CP100, CP80, and CP50, can be viewed as a solid suite of liquid alternatives to hedge funds. They match the 14 Credit Suisse hedge fund indexes on beta levels but deliver better risk-adjusted returns. Their annual returns and risk measures are better than or on par with the hedge fund indexes with the exception of the Credit Suisse Global Macro Index, which may be matched by a levered version of the CP100 option strategy. This suite of three option strategies are transparent, liquid, inexpensive, and easy to implement. They can achieve the same goals of hedge funds: attractive risk-adjusted returns, subdued risks, and added diversification. They may play multiple and important roles in institutional investors’ portfolios.

Thriving in a disrupted market: a study of Chinese hedge fund performance

We study a group of newly-emerged hedge funds in China, focusing on their performance and growth under a series of recent regulatory changes. These include the implementation of short sale restrictions and a circuit breaker. We find that the funds in our sample generally outperformed the stock market despite these regulatory disruptions. The best-performing equity-related strategies were long-short and multiple strategies. Our results indicate that the ability to sell short is important for all funds adopting equity-related strategies other than the long strategy. The imposition of short sale restrictions significantly reduced hedge fund performance, and the performance differential between “winner” and “loser” funds converged over time. The evidence suggests that the regulatory changes have greatly affected the hedge fund industry in China.

Hidden Costs in Hedge Fund Performance Fee Payment Frequencies

Hedge funds calculate and pay performance fees at different frequencies: daily, monthly, quarterly or annually. Using data from a public hedge fund database, we document considerable variation in hedge funds’ performance fee payment frequencies. Despite the higher costs associated with more frequent performance fee payments, funds with more frequent performance fee payments were not associated with lower management fees. Liquid and more volatile hedge fund categories also tend to have more frequent payment frequencies. To estimate hidden costs due to more frequent performance fee payment, we propose a simple linear model including the management fee, performance fee, and strategy volatility.

Hedge fund performance attribution under various market conditions

We investigate US hedge funds' performance. Our proposed model contains exogenous and endogenous break points, based on business cycles and on a regime switching process conditional on different states of the market. During difficult market conditions most hedge fund strategies do not provide significant alphas. At such times hedge funds reduce both the number of their exposures to different asset classes and their portfolio allocations, while some strategies even reverse their exposures. Directional strategies share more common exposures under all market conditions compared to non-directional strategies. Factors related to commodity asset classes are more common during these difficult conditions whereas factors related to equity asset classes are most common during good market conditions. Falling stock markets are harsher than recessions for hedge funds.

Relationship between mutual funds and hedge funds performance in different periods

The hedge fund literature has already shown that hedge funds and mutual funds follow a different strategy. One result of the literature was that mutual funds herd into or out of stocks following the herd of hedge funds one quarter later. The aim of this paper is to find out whether herding behavior of mutual funds have changed after the financial crisis. Our paper compares mutual funds and equity hedge funds in general (not only large hedge funds). The hypothesis is that mutual funds are not herding to equity hedge funds as strong as before the crisis. We use OLS regressions and correlation analysis to test the aforementioned hypothesis. We found that the monthly returns of hedge funds and mutual funds have synchronized in developed markets after the financial crisis. Therefore, the argument that mutual funds herd hedge funds is at least not as strong as before. The improving effectiveness and price informativeness could be an explanation for this changing environment.

Is Stellar Hedge Fund Performance for Real?

We apply a robust bootstrap to evaluate the performance of a large universe of hedge funds. Our bootstrap estimates indicate that the performance of the top hedge funds cannot be attributed to chance alone. This is true even after adjusting for back fill bias, serial correlation, and structural breaks. Also, we find that hedge fund alpha differences persist over three year horizons. However, an investment strategy designed around this will run into difficulties as the persistence is often confined to small funds that are effectively closed to new inflows. Moreover, Bayesian estimates suggest that standard alphas may be overestimated by 41% for the average top fund.

The Role of Strategy Distinctiveness in Hedge Fund Performance

We examine the relationship between deviating from the benchmark and subsequent performance for hedge funds. We propose a simple new measure of benchmark deviations, termed the Dispersion Contribution Index (DCI), which is based on a fund's return-distance from the mean return of same-style funds. We find that funds which deviate the most from their benchmark tend to underperform relative to their less distinctive peers, after accounting for their risk profile and various fund characteristics. This relative underperformance stems primarily from the higher subsequent risk exposure associated with pursuing a unique strategy.

Dodd-Franking the hedge Funds

This paper analyzes hedge fund performance, risk, and fund flows before and after the implementation of the Dodd–Frank Act. The data indicates that, relative to non-US hedge funds, US hedge funds that are regulated under Dodd–Frank have lower fund alphas in the post-Dodd–Frank implementation period, both statistically and economically significant, while the evidence on its effect on risk (standard deviations and idiosyncratic risk) is mixed. We find evidence that there is more fund outflow (or less fund inflow) for certain US hedge fund strategies after the implementation of Dodd–Frank. We show some differences in these findings dependent on fund size and strategy. The findings are robust to difference-in-differences analyses comparing US to non-US funds.

Relationship of Commodity and Equity Indices on Hedge Fund Performance

The golden times of the hedge fund industry ended with the beginning of the financial crisis of 2007/08. Since then hedge funds have underperformed against the S&P 500. This study shows that the Dodd Frank Act regulation was responsible for a completely changing environment for hedge funds. We have developed a model where equity indices and the CRB index are explanatory variables for hedge fund performance. Concerning methodology, data of two different phases are considered, namely the time period from 1990 to July 2010 (implementation of Dodd Frank Act) and the time period from August 2010 to April 2015. Surveys for the second time period showed that regulation was a major issue for the hedge fund industry. Especially small hedge funds find it problematic to get leverage from prime brokers and capital from investors. Another trend shown with the surveys is a general increase in the long only strategy (especially of small hedge funds). Our hypothesis assumes that the explanatory character of the MSCI Emerging Market (MSCI EM), the S&P 500, and the CRB index for hedge fund performance is increasing in the second period. The hypothesis is found to be correct.

Hedge fund managers and deceit: is the accusation of performance manipulation valid?

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.

Man vs. Machine: Comparing Discretionary andSystematic Hedge Fund Performance

In this article, the authors analyze and contrast the performance of discretionary and systematic hedge funds. Systematic funds use rules-based strategies, with little or no daily intervention by humans. In the authors’ experience, some large allocators shy away from systematic hedge funds altogether. One possible explanation is what the psychology literature calls “algorithm aversion.” However, the authors find no empirical basis for such an aversion. For the period 1996–2014, systematic and discretionary manager performance is similar, after adjusting for volatility and factor exposures (that is, in terms of their appraisal ratio). It is sometimes claimed that systematic funds have a greater exposure to well-known risk factors. However, the authors find that for discretionary funds (in aggregate), more of the average return and the volatility of returns can be explained by risk factors.

Volatility of aggregate volatility and hedge fund returns

This paper investigates empirically whether uncertainty about equity market volatility can explain hedge fund performance both in the cross section and over time. We measure uncertainty via volatility of aggregate volatility (VOV) and construct an investable version through returns on lookback straddles on the Chicago Board Options Exchange (CBOE) volatility index, VIX. We find that VOV exposure is a significant determinant of hedge fund returns. After controlling for fund characteristics, we find a robust and significant negative risk premium for VOV exposure in the cross section of hedge fund returns. We corroborate our results using statistical and parameterized proxies of VOV over a longer sample period.

Optimal Hedge Fund Performance Fees

Optimal Hedge Fund Performance Fees

To Hedge or Not to Hedge: Factor Dependence and Skill among Hedge Funds

As average hedge fund performance continues to wane, investors are increasingly seeking objective criteria to distinguish talented hedge fund managers from among the herd. Differentiating the contributions of systematic and idiosyncratic factors in a fund’s return stream is one way to accomplish this goal. In this article, the authors combine two related, but distinct, measurements of these quantities. Using the Carhart four-factor model, the Fung–Hsieh seven-factor model, and principal components analysis, they find that the hedge funds with the highest factor-adjusted alpha (a proxy for skill) and lowest R2 to these factor models (a proxy for factor dependence) produce the strongest subsequent returns and factor-adjusted alphas. They also find that those managers with high trailing factor-adjusted alpha have lower exposure to systematic risk factors in general.