Hedge Fund Strategies Research Articles

The (Mis)Behavior of Hedge Fund Strategies: A Network-Based Analysis

The authors discuss a network-based methodology that models hedge fund strategies across the superordinate–subordinate dimension to gain new insights into their interrelation. This methodology uncovers considerable misbehavior of various hedge fund strategies from the network perspective. Simply speaking, a misbehaving hedge fund strategy has undesired network proximity (similarity) with strategies from other classifications and/or undesired network-based risk properties. The authors conduct extensive static and dynamic (bootstrapping) analyses demonstrating misbehaviors for the full-sample data set. In addition, they demonstrate that numerous network-based behavioral properties of hedge fund strategies can explain future hedge fund returns. This aspect is of significant relevance, as it shows that network-based information has the potential to act as a value-adding warning indicator for funds of hedge funds. Summing up, the authors think that this article provides novel and valuable tools for hedge fund investors, managers, and analysts. TOPICS:Real assets/alternative investments/private equity, performance measurement

Hedge Fund Performance during and after the Crisis: A Comparative Analysis of Strategies 2007–2017

The performance of hedge funds is of interest to investors looking for ways of generating value over passive strategies, particularly in bad times. This study used the Hedge Index database with over 9500 hedge funds to analyse, in depth, the performance of ten major strategies, during and after the financial crisis (June 2007–January 2017). To the best of our knowledge, such a study covering the last ten years has not been published. Performance of the various strategies was analysed, using correlations, the Carhart’s four factor model, persistence of performance, and reward-risk ratios. The findings are that some hedge fund strategies which have persistent performances are also able to outperform the benchmark in some periods. In the crisis period, value-wise, all strategies did better than the S&P500, thereby, conserving value for investors, better than passive investment in the S&P500. Over the entire period of the research (June 2007–January 2017), seven strategies performed better than the S&P500: Global Macro, Multi Strategy, Emerging Markets, Long/Short Equity, Event Driven, Convertible Arbitrage, and Fixed Income Arbitrage. As hedge funds typically have skewed return distributions, performance was analysed in different periods, within conventional and downside risk frameworks. This research contributes to the advancement of knowledge on the outcomes of hedge fund strategies in different market conditions and the reliability of alternative risk frameworks in their evaluation. Apart from the theoretical implications, this research provides practical knowledge to managers and investors on which strategies hold better value and in what circumstances.

Hedge fund replication using strategy specific factors

Hedge funds have traditionally served wealthy individuals and institutional investors with the promise of delivering protection of capital and uncorrelated positive returns irrespective of market direction, allowing them to better manage portfolio risk. However, the financial crisis of 2008 has heightened investor sensitivity to the high fees, illiquidity, lack of transparency, and lockup periods typically associated with hedge funds. Hedge fund replication products, or clones, seek to answer these challenges by providing daily liquidity, transparency, and immediate exposure to a desired hedge fund strategy. Nonetheless, although lowering cost and adding simplicity by using a common set of factors, traditional replication products might offer lower risk-reward performance compared to hedge funds. This research explores hedge fund replication further by examining the importance of constructing clones with specific factors relevant to each hedge fund strategy, and then compares the strategy specific clone risk and reward performance against both actual hedge fund performance and hedge fund clones constructed using a more general set of common factors. Testing shows that using strategy specific factors to replicate common hedge fund strategies can offer superior risk-reward performance compared to previous general model clones.

Factors in Time: Fine-Tuning Hedge Fund Replication

Hedge fund replication has become a cottage industry in investing. Among the most popular hedge fund replication frameworks are factor models based on ordinary least squares (OLS) regression, a development that is no doubt due to its simplicity and familiarity among investment practitioners. Despite their widespread use, the OLS regression-based factor models that form the basis for many hedge fund replication programs are often overfitted to a single sample, severely undercutting their predictive effectiveness. As a remedy to the latter shortcoming, in this article the authors apply the regularization method known as “ridge regression” to the replication of hedge fund strategies. Ridge regression works by formally imbuing a regression with additional bias in exchange for a reduction in the variance between training and test samples. Using a simple yet robust methodology, the authors show how to dynamically calibrate the predictively optimal level of bias without significantly reducing the backward-looking explanatory power of a given model. In doing so, the authors demonstrate that ridge regression can help produce generalizable models that are useful in both the ex post risk analysis and ex ante replication of hedge fund strategies.

Do Macro News Surprises of the US Affect Forex Implied Volatility? The Evidence of Japanese Yen in 1997-2015

This paper aims to provide an updated research on how macroeconomic news announcements a�?ٴect forex option implied volatility (IV). Forex options are actively traded and used by corporations and financial institutions for risk management, arbitrage and speculation. According to Bank of International Settlement, forex options make up the second largest segment of the global OTC option market [1]. At the end of 2014, the notional amount of outstanding foreign exchange option contracts is totaled at US$15 trillion. Given the important role of IV in options pricing, risk management, trading, investment and forex transaction services, it is worthwhile to explore how IV is a�?ٴected by macroeconomic news. Implied volatility (IV) as important market information Many previous studies analyze how a realized volatility can be predicted by news surprises, information embedded in forex options IV and econometrics models. For instance, Andersen conclude that historical volatility in the forex market is more powerful than predicted volatility obtained from GARCH-related models in forecasting future realized volatility [2-5]. Bush applies heterogeneous autoregressive (HAR) model suggested by Corsi and demonstrates that IV remains to be useful to predict future volatility if it is considered with together jump components in the forex market [6,7]. However, in the crude oil futures market, Agnolucci finds that GARCH-type models seem to outperform IV in predicting realized volatility [8]. Нese studies focus mainly on realized volatility and ignore a fact that IV itself is a collective perception on risk and a fundamental input for derivatives pricing. As information on risk, IV itself can a�?ٴect how market makers manage their quotes. For instance, studies on bid-ask spreads, such as Bollerslev and Melvin and King, find that spreads tend to be higher when IV increases [9,10]. Traders may consider IV as a pre-condition of specific hedge fund strategies. Studies on currency carry trades, such as Egbers and Swinkels, suggest that carry-trade strategies tend to su�?ٴer serious lose when IV turns sharply higher [11]. Нis may explain why traders tend to reverse their carry-trade positions a�?er increased IV see, Menkho�?ٴ] 12]. All these indicate that IV, regardless of its association with realized volatility, is important market information for asset pricing and trading. How market participants form their risk perception and determine the IV is an interesting research area.

Performance Characteristics of Hedge Fund Indices

The focus of the study is to provide a detailed account of how various strategy-specific or composite hedge fund indices have performed in the past. The study analyses returns (monthly) of different hedge funds. The study selected popular categories of Hedge fund index against DJIA (Dow Jones Industrial Average) and Credit Suisse Hedge Fund Index. The Data is taken from January 1994 to December 2018 and is taken from Credit Suisse Hedge fund database. The study finds that most hedge fund indices witness a drop in returns over time, and most hedge funds do not provide additional diversification benefits with respect to traditional asset class. On a risk-adjusted basis, majority of hedge fund indices out-perform the broader equity market, risk-adjusted performances of various hedge fund strategies, does not change drastically with use of different risk-adjusted measures. As opposed to prevalent studies like Atil, Bali and Demirtas [1] [2], indicating Equity market neutral hedge fund index as the best performer in terms of risk-adjusted returns, the current study finds Event Driven Distressed hedge fund Index as the best performer.

Hedge Fund Investing or Mutual Fund Investing: An Application of Multi-Attribute Utility Theory

This paper contrasts high-risk, hedge fund trading, with low-risk, mutual fund trading, in terms of their differing utility functions. We envision hedge funds, led by informed traders who use information to seek out investment opportunities, timing market conditions, with the expectation that prices will move in their favor. Directional hedge funds act to influence prices, while non-directional hedge funds do not act to influence prices. We present utility functions based on steeply-sloping Laplace distributions and hyperbolic cosine distributions, to describe the actions of directional hedge fund traders. Less steeply-sloping lognormal distributions, Coulomb wave functions, quadratic utility functions, and Bessel utility functions are used to describe the investing style of non-directional hedge fund traders. Flatter Legendre utility functions and inverse sine utility functions describe the modest profit-making aspirations of mutual fund traders. The paper’s chief contribution is to develop optimal prices quantitatively, by intersecting utility functions with price distributions. Price distributions for directional hedge fund returns are portrayed as sharp increases and decreases, in the form of jumps, in a discrete arrival Poisson-distributed process. Separate equations are developed for directional hedge fund strategies, including event-driven arbitrage, and global macro strategies. Non-directional strategies include commodity trading, risk-neutral arbitrage, and convertible arbitrage, with primarily lognormal pricing distributions, and some Poisson jumps. Mutual funds are perceived to be Markowitz portfolios, lying on the Capital Market Line, or the International Capital Market Line, tangent to the Efficient Frontier of minimum variance-maximum return portfolios.

Testing the new Fama and French factors with illiquidity: A panel data investigation

Nous investiguons les cinq nouveaux facteurs de Fama et French (2015, 2016) rehaussés d’une mesure de liquidité bien connue (Pástor and Stambaugh, 2003) à l’aide d’une version du GMM qui recourt à des instruments robustes, cela dans le cadre d’une analyse en panel. Lorsque nous recourons à l’estimateur OLS, notre version du modèle de Fama-French semble avoir un pouvoir explicatif en regard des rendements d’un portefeuille à douze secteurs. Cependant, notre étude en panel suggère que le seul facteur significatif est la prime de risque du marché. Dépendamment de la technique utilisée, nous trouvons que les erreurs de mesure peuvent être à la source de ce résultat, ce qui tend à appuyer le modèle élargi de Fama-French. Comme test de robustesse, nous expérimentons également avec d’autres mesures de liquidité, telles que le ratio d’Amihud (2002) et la prime à terme, ainsi qu’avec des facteurs reliés aux marchés obligataires. Les résultats sont plutôt inchangés pour nos 12 portefeuilles. Nous testons également notre modèle élargi sur des portefeuilles gérés – i.e., des fonds de couverture (hedge funds). Ces portefeuilles semblent mieux adaptés au modèle élargi de Fama-French qui inclut des mesures de liquidités, et plus spécialement lorsque l’on introduit la crise des subprimes . Les nouveaux facteurs de Fama-French semblent également être très sensibles à nos mesures d’illiquidité.

Can Investors Benefit from Hedge Fund Strategies? Utility‐Based, Out‐of‐Sample Evidence

We report systematic, out-of-sample evidence on the benefits to an already well diversified investor that may derive from further diversification into various hedge fund strategies. We investigate dynamic strategic asset allocation decisions that take into account investors’ preferences as well as return predictability. Our results suggest that not all hedge fund strategies benefit a long-term investor who is already well diversified across stocks, government and corporate bonds, and REITs. Only strategies whose payoffs are highly nonlinear (e.g., fixed income relative value and convertible arbitrage), and therefore not easily replicable, constitute viable options. Most of the realized economic value fails to result from a mean-variance type of improvement but comes instead from an improvement in realized higher-moment properties of optimal portfolios. Medium to highly risk-averse investors benefit the most from this alternative asset class.

Hedge fund return higher moments over the business cycle

We investigate how macroeconomic and financial uncertainty impacts the behavior of hedge fund strategy higher moments—i.e., co-skewness and co-kurtosis—and their respective cross-sectional dispersions. Consistent with theoretical models, we find that strategy managers trade off these two higher moments when building optimal portfolios. Moreover, these trade-offs depend on the kind of strategy. Our experiments show that the VIX and its conditional variance are the most important factors affecting higher moment risk in the hedge fund industry. They also reveal that the behavior of hedge fund strategies is very asymmetric depending on the phase of the business cycle. In contrast to studies which rely on the mean-variance setting, we find that systemic risk—as measured by the cross-sectional dispersions of higher moments—tends to decrease in the low regime. The indicators of market volatility play a decisive role to explain this decline in systemic risk.

Trends Everywhere? The Case of Hedge Fund Styles

This paper investigates empirically whether time-series momentum returns can explain the performance of hedge funds in the cross-section. Following the trend following literature, a volatility-adjusted time-series momentum signal is applied on a daily basis across a large set of futures, covering the major asset classes. We build a hierarchical set of trend factors: the full version TREND can be split in summable factors across two dimensions, the horizon of the signals and the traded asset class. We show that Managed Futures, Global Macro and Fund of Hedge Funds strategies can be partly explained by a TREND exposure, whereas Equity Market Neutral and Quantitative Directional are only exposed to long term trend factors. Moreover, a TREND expo- sure is a significant determinant of hedge funds returns at the aggregate level, as well as at the fund level. Finally, funds with high TREND beta outperform by 41 basis points of alpha the funds with low Trend beta. These results prove useful when managing the risk of a portfolio of hedge funds strategies, since assessment of the Trend exposure is easier. Another contribution of this study is related to the understanding of the CTA space, composed of pure trend funds as well as funds that do not exhibit any TREND exposure.

Hedge Funds and Impact Investing: Considerations for Institutional Investors

Impact investing has grown rapidly over the last 10 years, in terms of both investment options and dollars invested. Much of this growth is attributed to the evolution from screening to proactive approaches. Many institutional investors are realizing that along with the social benefit, impact investing can be additive to returns, and they are looking for ways to incorporate this trend. Impact investing options are available in all asset classes, but the adoption rate within the hedge fund community has lagged all the others. This article focuses on three possible reasons for this: hedge fund strategies primarily rely on alpha for returns, possible time horizon mismatch between shorter term focused hedge funds and sustainability trends, and the below-market-return stigma associated with historical SRI investing. The article identifies strategies in which these obstacles may not apply and provides suggestions for ways institutional investors can engage with their hedge fund managers and incorporate these strategies into their hedge fund allocation.

Relative Value Hedge Funds: A Behavioral Modeling of Hedge Fund Risk and Return Factors

ABSTRACTThis study has 4 contributions to the literature. First, the authors analyze the risk characteristics for 11 Relative Value hedge fund strategies. Second, the authors introduce 3 families of behavioral factors, the D family, the L family, and the R family. In contrast to previous hedge fund studies, these new factors assume investors use historical and behavioral data such as average drawdown, run up, and liquidity from each hedge fund category to assess the risk. Third, additional macroeconomic variables, such as the CRB, Copper, and Oil are found to be statistically significant in some strategies. This economic and historical information, when included with asset pricing models, is more powerful in explaining hedge fund returns than previous models. Fourth, unlike the previous literature, these generated models are corrected for time-series assumptions violations and heteroskedasticity. To more fully understand the timing of risks and returns associated with investing in relative value hedge funds, pension funds and other investors should incorporate more economic factors and behavioral factors.

Can Investors Benefit from Hedge Fund Strategies? Utility‐Based, Out‐of‐Sample Evidence

We report systematic, out-of-sample evidence on the benefits to an already welldiversified investor that may derive from further diversification into various hedge fund strategies. We investigate dynamic strategic asset allocation decisions that take into account investors’ preferences as well as return predictability. Our results suggest that not all hedge fund strategies benefit a long-term investor who is already well diversified across stocks, government and corporate bonds, and REITs. Only strategies whose payoffs are highly nonlinear (e.g., fixed income relative value and convertible arbitrage), and therefore not easily replicable, constitute viable options. Most of the realized economic value fails to result from a mean-variance type of improvement but comes instead from an improvement in realized higher-moment properties of optimal portfolios. Medium to highly risk-averse investors benefit the most from this alternative asset class.

All Style Hedge Fund Analysis with Constant- and Time-Varying Factor Loading Models

Driven by vast historical growth and the recent crises, the hedge fund industry has undergone several changes. This thesis presents studies on the analysis of hedge fund returns within changing market states by applying different constant, asymmetric and time-varying factor loading models. Considered models include the CAPM, Fama-French 3-factor model, Carhart 4-factor model, Fama-French 5-Factor model, Agarwal-Naik 8-factor model and the Fung-Hsieh 7- and 8-factor models. In addition, and unlike previous research, 94 hedge fund strategy styles have been analysed individually to test whether the model performances differ among approaches. The first full-sample analysis exhibits generally low explanatory power whereby the more sophisticated models perform superiorly. Equity strategies, especially long-only funds, exhibit high adjusted R-Squared among all models, while fixed income, fundamental and technical hedge funds result in low significance. The CUSUM control chart based crisis/non-crisis dummy cannot substantially improve the explanatory power of the models. Hedge fund alpha and factor significance varies considerably among strategies and the power of the models remains similarly poor. Asymmetric up/down models exhibit slightly improved explanatory power while the significance of alpha diminishes. Replacing the conditional up/down variable by the crisis/non-crisis setting resulted in inferior results. Empirical analysis with asymmetric higher-moment models approves the asymmetries in hedge fund returns partially. Moreover, a time-varying approach substantially improves the explanatory power of all models while hedge fund alpha further diminishes. All dynamic models exhibit significant exposures on macro state variables for a high proportion of funds. To summarise, it has been shown how simple models can be fitted to increase the explanatory power. As a result, the adjusted R-Squared were improved by 73%. On a strategy level, equity funds are explained the best while fixed income, fundamental and technical hedge funds are the most difficult to analyse.

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.

A behavioural game-theoretic analysis of hedge fund regulation

ABSTRACTWe analyse the efficacy of hedge fund regulation in a behavioural game-theoretic model consisting of two players: a hedge fund manager and a regulator. The regulator decides whether or not to regulate hedge fund strategies, and location of key service providers (KSPs). The manager then decides (a) which KSP to choose, (b) whether to choose a safe or risky strategy, and (c) how much effort to exert in affecting the strategy’s success probability. We consider the effect of expected future fund flows on the manager’s incentives. Furthermore, we consider economic and behavioural factors affecting the regulator’s decision-making. Finally, we discuss how our two cases (myopic versus far-sighted managerial behaviour) may inform the debate over regulation over the entire financial market-cycle. Overall, our analysis contributes to the debate on hedge fund regulation.

Factor Investing and Risk Allocation: From Traditional to Alternative Risk Premia Harvesting

Sophisticated institutional investors have a growing interest in factor investing, a disciplined approach to portfolio management that is broadly meant to allow investors to harvest risk premia across and within asset classes through liquid and cost-efficient systematic strategies without having to invest with active managers. Although it is now well accepted that the average long-term performance of active mutual fund managers can to a large extent be replicated through a static exposure to traditional long-only risk premia, an outstanding question remains with respect to the best possible approach for harvesting alternative long–short risk premia. The focus of this article is to empirically analyze (1) whether systematic rules-based strategies based on investable versions of traditional and alternative factors allow for satisfactory in-sample and out-of-sample replication of hedge fund performance, and more generally (2) whether suitably designed risk allocation strategies may provide a cost-efficient way for investors to get attractive exposure to alternative factors, regardless of whether they can be regarded as proxies for any particular hedge fund strategy. The main findings can be summarized as follows. On one hand, the authors find that replication models for hedge funds strategies generally achieve a relatively low out-of-sample explanatory power, regardless of the set of factors and the methodologies used. On the other hand, they find that heuristic allocation strategies, such as risk parity strategies, applied to alternative risk factors could be a better alternative to hedge fund replication for efficiently harvesting alternative risk premia.

The (Mis)Behavior of Hedge Fund Strategies: A Network-Based Analysis

We discuss a network-based methodology that models hedge fund strategies across the superordinate-subordinate dimension to gain new insights into their interrelation. This methodology uncovers considerable misbehavior among various hedge fund strategies from the network perspective. Firstly, we conduct a static analysis demonstrating misbehaviors for the full-sample dataset. In addition, we perform dynamic bootstrapping analyses offering details on the misbehavior of selected hedge fund strategies. Finally, we demonstrate that numerous network-based behavioral properties of hedge funds strategies can explain current and future hedge fund returns. The last aspect is of significant relevance, as it shows that network-based information has the potential to act as a value-adding warning indicator for funds of hedge funds. Summing up, we think that this article provides novel and valuable tools for hedge fund investors, managers and analysts.

Analysis of Hedge Fund Investment Styles and Strategies During 2009-2010

This MSc paper analyses hedge fund alpha-seeking strategies in the aftermath of financial crisis.