Hedge Fund Risk Research Articles

A tale of regulatory divergence: contrasting transatlantic policy responses to the alleged role of alternative investment funds in financial instability

This article analyzes the regulatory measures adopted to address the potential contribution of hedge funds to financial instability in the U.S. and the EU in the wake of the Global Financial Crisis. The relevant provisions of the Dodd-Frank Act include two sets of direct regulatory measures. The first set of these measures addresses information problems, whereas the second set is intended to address potential too-big-to-fail problems by imposing prudential regulation on systemically important nonbank financial companies. The article then studies the Volcker Rule, as an indirect regulatory measure intended to address the potential systemic risk of hedge funds originating from their interconnectedness with Large Complex Financial Institutions (LCFIs). The second part of this article analyzes the European Directive on Alternative Investment Fund Managers and its attempt to address the potential contribution of hedge funds to financial instability.Despite the common driving forces of hedge fund regulation across the Atlantic, ultimate policy outcomes were significantly divergent. Primarily concerned with creating a single market for Alternative Investment Funds, EU regulators prioritized the EU passport mechanism, which engendered demand for investor protection and more stringent and direct regulatory measures. In contrast, the main concern in the U.S. remained to be addressing potential systemic risk of hedge funds. Such differential regulatory objectives gave birth to indirect regulation of hedge funds with a focus on their interconnectedness with LCFIs. This is mainly embedded in the provisions of the Volcker Rule; a rule whose absence is significantly palpable in the EU regime for regulating hedge funds.

Hedge funds risk and connectedness

This paper focused on measuring the volatility spillovers and parametric Value-at-Risk (VaR) models for hedge fund strategies. In reference to the first, a volatility spillover index was created to measure the connectedness and relationships between strategies. Results suggest that during periods of distress, volatility spillovers tend to increase across strategies. Equity-Hedge and Event-Driven strategies seem to be the most connected, while the Equity-Market-Neutral strategy exhibits the least connectedness with other strategies. With regard the second, unconditional and conditional parametric VaR models under Gaussian and t-distributions were measured. In general, conditional GARCH-type models outperform their unconditional counterparts, particularly at the onset of the recent financial crisis. This suggests that GARCH-type VaRs are better in protecting against downside risk. Moreover, conditional Gaussian models are more suitable for mild periods, while those under the t-distribution effectively capture risk in extremely volatile period. Finally, to unravel the connection between the two measures, common hits between hedge fund strategies were examined. The results validate the results of the volatility spillover index.

A Tail of Two Cities: On the Downside Risk and LossProfile of Asian and North American Hedge Funds

This article analyzes the downside risk and loss profiles of hedge funds in North America and Asia to identify any significant differences between the geographic markets and to determine how these differences have converged or diverged over time. An attempt is made to understand the performance drivers that differentiate Asian from North American hedge funds. In the downside-risk analysis of 2,631 North American and 994 Asian hedge funds from January 1995 to February 2013, event-driven investment strategies for both geographic regions perform better than the other hedge fund investment strategies in relation to both risk and return and downside risk. More diversified funds, such as multistrategy hedge funds, do not necessarily perform better than single-manager strategies in relation to downside risk, while relative value strategies exhibit the most similar characteristics across the two geographies. Following their lackluster performance during the Asian financial crisis, Asian hedge funds improved their risk-adjusted performance, particularly during the recent global financial crisis when their loss profile reached a level similar to that of their North American peers. Lastly, nearby funds (i.e., funds whose managers are located in the same investment geography) have slightly worse loss profiles than distant funds in both geographic markets, a result that is slightly contrary to extant empirical evidence.

Hedge Funds and Systemic Risk

The public media and politicians regularly debate the potential for hedge funds to contribute to systemic risk in financial markets. Because the hedge fund industry experienced substantial growth over the past two decades, concerns about hedge funds’ systemic risk have increased and regulators have taken measures to mitigate possible risks associated with these funds. The chapter summarizes the pre- and post-crisis debate and highlights the post-crisis evidence regarding hedge funds’ alleged systemic risk. In particular, the authors examine evidence regarding specific factors surrounding hedge funds’ possible contributions to systemic risk, including risk management incentives, leverage, liquidity characteristics, regulation, financial stability, transparency, and their potential to induce and perpetuate market contagion.

ANÁLISE DE ESTILO DINÂMICA DE FUNDOS MULTIMERCADOS: APLICAÇÃO PARA O MERCADO BRASILEIRO

Este artigo aplica o modelo de análise de estilo baseado em retornos (RBSA) considerando explicitamente a presença de exposições variantes no tempo. Inicialmente, o modelo é estimado assumindo que os estilos são constantes ao longo do tempo. Posteriormente, é utilizada a abordagem do filtro de Kalman para modelar as exposições dos fundos multimercados variantes ao longo do tempo. Usando uma base de dados de fundos multimercados brasileiros, os resultados mostram que a RBSA pode explicar mais de 50% da variância dos retornos dos fundos. Também evidencia significante exposição ao mercado de ações e que a exposição a fatores relacionados ao mercado de renda fixa vem crescendo. Finalmente, a modelagem considerada capta mudanças importantes no estilo de exposição a fatores de risco dos fundos multimercados brasileiros decorrentes da recente crise financeira global (2008-2009).

Gauging Form PF: Data Tolerances in Regulatory Reporting on Hedge Fund Risk Exposures

This paper examines the precision of the U.S. Securities and Exchange Commission’s Form PF as an instrument for measuring market risk exposures in the hedge fund industry. We introduce a novel methodology that systematically presents the measurement instrument, Form PF, with a range of simulated portfolios with observable characteristics. We assess the measurement tolerances of Form PF by examining the range of actual market risk exposures – measured directly from portfolio details – that are consistent with a given, fixed presentation on the form. We find that Form PF’s measurement tolerances are sufficiently large to allow private funds with dissimilar actual risk profiles to report similar risks to regulators. We also find that the form’s stratification by value at risk (Form PF Question 40) helps significantly to narrow the measurement tolerances.

Optimising Asset Allocation between Hedge Funds and Private Equity

This paper explores the optimisation of asset allocation within “alternative” investments, i.e. between private equity and hedge funds, as well as between private equity and public equities. It uses our proprietary Portfolio Blender tool. As a preliminary step before the optimisation, we compared the respective risk and return profiles of private equity and hedge funds to those of traditional assets. We compared private equity to public equities because of the equity component inherent to both asset classes, whereas we compared hedge funds to bonds because of their historical low level of volatility. Then, we used two complementary optimisation approaches: the first approach verifies the respective role of asset classes; the second one specifically addresses the question of optimising within constraints. Finally, and based on the results of both approaches, we made broad suggestions on how an investor could allocate between hedge funds and private equity, depending on what they expect from “alternative” investments.

Unique Hedge-Fund Risk Considerations

As the hedge-fund business expands relative to traditional asset management, researchers are developing risk measures to take into consideration the nonstandard performance characteristics of hedge funds. This article gives three examples of proposals that have been published recently. Each proposal notes that conventional risk measures might understate the risk of hedge-fund strategies.Researchers are also grappling with how to extract useful risk information from brief and flawed historical data. This article discusses two proposals to address this difficulty.

Hedge fund return predictability; To combine forecasts or combine information?

While the majority of the predictability literature has been devoted to the predictability of traditional asset classes, the literature on the predictability of hedge fund returns is quite scanty. We focus on assessing the out-of-sample predictability of hedge fund strategies by employing an extensive list of predictors. Aiming at reducing uncertainty risk associated with a single predictor model, we first engage into combining the individual forecasts. We consider various combining methods ranging from simple averaging schemes to more sophisticated ones, such as discounting forecast errors, cluster combining and principal components combining. Our second approach combines information of the predictors and applies kitchen sink, bootstrap aggregating (bagging), lasso, ridge and elastic net specifications. Our statistical and economic evaluation findings point to the superiority of simple combination methods. We also provide evidence on the use of hedge fund return forecasts for hedge fund risk measurement and portfolio allocation. Dynamically constructing portfolios based on the combination forecasts of hedge funds returns leads to considerably improved portfolio performance.

Calpers Absolute Return Strategies: Hedge Fund Risk and Return

This case is suitable for students in both undergraduate and MBA-level investments courses. With an estimated $3 trillion in assets under management, hedge funds have become an important component of many institutional investors' portfolios. For many of these investors, investments in these funds are motivated by the potential for diversification combined with equity-like and bond-like risk. At the same time, the difficulty of appropriately benchmarking hedge fund returns and risk, in addition to the high fees associated with these funds, has some investors questioning their decision to invest in these strategies. Using CalPERS's April 2014 reexamination of its Absolute Return Strategies/hedge fund investments as a backdrop, this case examines the decision to invest in hedge funds as a part of a well-diversified institutional portfolio. Excerpt UVA-F-1735 Jun. 29, 2015 CalPERS Absolute Return Strategies: Hedge Fund Risk and Return The California Public Employees' Retirement System (CalPERS) headquarters near the Sacramento River was as beautiful as it was functional. With courtyards and terraces, beautiful landscaping, an architecturally stunning glass-and-steel entry pavilion, and a soaring glass atrium that flooded the building with natural light, it appeared to be as tranquil a work setting as the Zenlike spaces that dotted its interior and exterior. In the spring of 2014, however, internal sources suggested that a storm was brewing within the building over CalPERS's hedge fund investments. Two of CalPERS's most senior investment professionals, Curtis Ishii and Egidio “Ed” Robertiello, disagreed strongly about the future of these investments. Hedge funds had been a part of CalPERS's portfolio for 22 years, but there was a strong push by Ishii, the senior investment officer responsible for fixed income, to eliminate CalPERS's allocation to Absolute Return Strategies (ARS). In addition to the high fees CalPERS was paying to hedge fund managers, Ishii was convinced that hedge fund investments were an unacceptable risk for the pension fund. On the other hand, Robertiello, the senior portfolio manager for ARS, believed that the ARS allocation should be almost tripled. Robertiello argued that not only would an increased allocation to hedge funds help to diversify CalPERS's portfolio generally, but that hedge funds offered better downside protection than equities. . . .

Beyond Bayesian vs. VaRR Dilemma to Empirical Model Risk Management: How to Manage Risk (After Risk Management Has Failed) for Hedge Funds

In aftermath of the Financial Crisis, some risk management practitioners advocate wider adoption of Bayesian inference to replace Value-at-Risk (VaR) models for minimizing risk failures (Borison & Hamm, 2010). They claim reliance of Bayesian inference on subjective judgment, the key limitation of Bayesian methodology as underscored by statisticians (Kass & Raftery, 1995; Kruschke, 2011; Lynch, 2007), as the most significant advantage compared with VaR (Christoffersen, 2012). Despite its well-known limitations, just like all other quantitative models (Derman, 1996; Morini, 2011), VaR – [mostly] non-Bayesian and [increasingly] Bayesian – continues to be a key methodological foundation of risk management and regulation related risk modeling practices in global Finance (Danielsson et al., 2014; Zangari, 1996). Bayesian inference modeling and VaR modeling frameworks are outlined to facilitate model risk management (Derman, 1996; Morini, 2011; US Fed & OCC, 2011) for minimizing risk of any model – Bayesian, VaR, or Bayesian VaR. VaR frameworks are empirically applied for hedge fund risk modeling (Darbyshire & Hampton, 2012, 2014) of a multi-asset fund of funds portfolio of a large Wall Street investment bank. Multiple risk models and measures with transparent assumptions to cross-validate convergent findings across multiple levels of risk analysis are examined for empirical model risk management.

How Risky are Low-Risk Hedge Funds?

This paper investigates the determinants of the average level of risk of hedge funds, which provide high liquidity to their investors and report their returns on a daily basis. We find that larger funds and funds charging higher incentive fees exhibit lower risk, whereas funds charging higher management fees, imposing longer notice periods, and stemming from large fund-families take more risk. There is considerable variation in the risk levels between funds reporting in Euro and USD, with Euro funds being consistently less risky, suggesting that these funds target different types of investors with other preferences.

A Tail of Two Cities: On the Downside Risk and Loss Profile of Asian and North American Hedge Funds

This paper analyzes the downside risk and loss profiles of hedge funds in North America and Asia to identify any significant differences between the geographic markets and determine how these differences have converged or diverged over time. An attempt is made to understand the performance drivers that differentiate Asian from North American hedge funds. In the downside-risk analysis of 2,631 North American and 994 Asian hedge funds from January 1995 to February 2013, event-driven investment strategies for both geographic regions perform better than the other hedge fund investment strategies in relation to both risk and return, and downside risk. More diversified funds such as multi-strategy hedge funds do not necessarily perform better than single-manager strategies in relation to downside risk, while relative value strategies exhibit the most similar characteristics across the two geographies. Following their lackluster performance during the Asian Financial Crisis, Asian hedge funds improved their risk-adjusted performance, particularly during the recent Global Financial Crisis when their loss profile reached a level similar to that of their North American peers. Lastly, “nearby” funds, i.e., funds whose managers are located in the same investment geography, have slightly worse loss profiles than “distant” funds in both geographic markets, which result is slightly contrary to extant empirical evidence.

Hedge Fund Performance Using Scaled Sharpe And Treynor Measures

The Sharpe ratio is widely used as a performance measure for traditional (i.e., long only) investment funds, but because it is based on mean-variance theory, it only considers the first two moments of a return distribution. It is, therefore, not suited for evaluating funds characterised by complex, asymmetric, highly-skewed return distributions such as hedge funds. It is also susceptible to manipulation and estimation error. These drawbacks have demonstrated the need for new and additional fund performance metrics. The monthly returns of 184 international long/short (equity) hedge funds from four geographical investment mandates were examined over an 11-year period.This study contributes to recent research on alternative performance measures to the Sharpe ratio and specifically assesses whether a scaled-version of the classic Sharpe ratio should augment the use of the Sharpe ratio when evaluating hedge fund risk and in the investment decision-making process. A scaled Treynor ratio is also compared to the traditional Treynor ratio. The classic and scaled versions of the Sharpe and Treynor ratios were estimated on a 36-month rolling basis to ascertain whether the scaled ratios do indeed provide useful additional information to investors to that provided solely by the classic, non-scaled ratios.

Risk Measures for Autocorrelated Hedge Fund Returns

Standard risk metrics tend to underestimate the true risks of hedge funds because of serial correlation in the reported returns. Getmansky, Lo, and Makarov (2004) derive mean, variance, Sharpe ratio, and beta formulae adjusted for serial correlation. Following their lead, we derive adjusted downside and global measures of individual and systemic risks. We distinguish between normally and fat-tailed distributed returns and show that adjustment is particularly relevant for downside risk measures in the case of fat tails. An empirical analysis reveals that unadjusted risk measures can considerably underestimate the true extent of individual and systemic risks for hedge funds.

The Bias Ratio As A Hedge Fund Fraud Indicator: An Empirical Performance Study Under Different Economic Conditions

The Sharpe ratio is widely used as a performance evaluation measure for traditional (i.e., long only) investment funds as well as less-conventional funds such as hedge funds. Based on mean-variance theory, the Sharpe ratio only considers the first two moments of return distributions, so hedge funds characterised by complex, asymmetric, highly-skewed returns with non-negligible higher moments may be misdiagnosed in terms of performance. The Sharpe ratio is also susceptible to manipulation and estimation error. These drawbacks have demonstrated the need for augmented measures, or, in some cases, replacement fund performance metrics. Over the period January 2000 to December 2011 the monthly returns of 184 international long/short (equity) hedge funds with investment mandates that span the geographical areas of North America, Europe, and Asia were examined. This study compares results obtained using the Sharpe ratio (in which returns are assumed to be serially uncorrelated) with those obtained using a technique which does account for serial return correlation. Standard techniques for annualising Sharpe ratios, based on monthly estimators, do not account for serial return correlation this study compares Sharpe ratio results obtained using a technique which accounts for serial return correlation. In addition, this study assess whether the Bias ratio supplements the Sharpe ratio in the evaluation of hedge fund risk and thus in the investment decision-making process. The Bias and Sharpe ratios were estimated on a rolling basis to ascertain whether the Bias ratio does indeed provide useful additional information to investors to that provided solely by the Sharpe ratio.

Histogram-valued data on value at risk measures: a symbolic approach for risk attribution

In this article, we develop the concept of histogram-valued data on value at risk for the classification of hedge fund risk. By using recent developments in data mining, it is a question of the classification of heterogeneous data in order to sort hedge funds by risk class. In practical terms, risk levels relative to measures of histogram-valued data on VaR are calculated as an aid to decision-making. The empirical study was carried out on 1023 HFR-based hedge funds, where we had estimated monthly ARMA-GARCH or asymmetric GARCH VaR and CVaR measures between 01 January 2003 and 31 December 2008. We identify two sub-periods: from 2003 to 2005, and from 2006 to 2008 in order to identify a recovery period after the 2001–2002 crisis and the impact of the 2007–2008 crisis. First, the symbolic approach allows us to construct the measures of histogram-valued data on VaR by optimizing the definition of categories. A symbolic principal component analysis shows that the indices coming from the VaR of the GARCH and asymmetrical GARCH are the most pertinent. Second, we apply a criterion of inter-class inertia and retain a partitioning of hedge funds into three classes by dynamic K-means cluster analysis. For each of our sub-periods and for each class, a risk level is defined on the basis of the categories of the most discriminating variable.

Hedge Fund Performance Evaluation Using The Sharpe And Omega Ratios

The Sharpe ratio is widely used as a performance evaluation measure for traditional (i.e., long only) investment funds as well as less-conventional funds such as hedge funds. Based on mean-variance theory, the Sharpe ratio only considers the first two moments of return distributions, so hedge funds characterised by asymmetric, highly-skewed returns with non-negligible higher moments may be misdiagnosed in terms of performance. The Sharpe ratio is also susceptible to manipulation and estimation error. These drawbacks have demonstrated the need for augmented measures, or, in some cases, replacement fund performance metrics. Over the period January 2000 to December 2011 the monthly returns of 184 international long/short (equity) hedge funds with geographical investment mandates spanning North America, Europe, and Asia were examined. This study compares results obtained using the Sharpe ratio (in which returns are assumed to be serially uncorrelated) with those obtained using a technique which does account for serial return correlation. Standard techniques for annualising Sharpe ratios, based on monthly estimators, do not account for this effect. In addition, this study assesses whether the Omega ratio supplements the Sharpe Ratio in the evaluation of hedge fund risk and thus in the investment decision-making process. The Omega and Sharpe ratios were estimated on a rolling basis to ascertain whether the Omega ratio does indeed provide useful additional information to investors to that provided by the Sharpe ratio alone.

The Direct Regulation of Potential Systemic Risk of Hedge Funds in the U.S. before and after the Dodd-Frank Act

This article compares the direct regulation of hedge funds in the U.S. prior to the Dodd-Frank Act with the direct regulatory measures to address potential systemic risks of hedge funds ensued in its aftermaths. The direct regulation involves regulatory measures focusing immediately on the regulation of the target industry. In contrast, the imperatives or commands of indirect regulation is mediated by or transmitted through an intermediary to the (primarily intended) regulated entity or activity, which is ultimately the target. To address the potential contribution of hedge funds to financial instability, the Dodd-Frank Act uses a mix of direct and indirect regulatory measures. This article focuses solely on the direct regulatory measures.The first part of the article briefly sketches the regulatory environment of hedge funds in the U.S. prior to the enactment of the Dodd-Frank Act. The second part analyzes the relevant provisions of the Dodd-Frank Act intended to address the potential contribution of hedge funds to financial instability with direct regulatory measures. On the one hand, these measures mainly address the information problems in the hedge fund industry through the imposition of the registration and disclosure requirments on hedge funds and collection of systemic risk data. On the other hand, as an additional direct regulatory measure, the Dodd-Frank Act requires the Federal Reserve (Fed) to impose prudential regulation for hedge funds contingent upon their designation as Systemically Important Non-bank Financial Companies (SINBFCs) by the Financial Stability Oversight Council (FSOC). This article concludes that in the absence of the indirect regulatory measures focusing on the banking entities placing restrictions on their relationships with private funds (embodied in the Volcker Rule), the direct regulation of hedge funds is unlikely to mitigate the potential systemic risk of hedge funds.

DO HEDGE FUNDS ADD VALUE FOR INVESTORS?

ABSTRACT This paper discusses whether hedge funds create value for investors. To determine whether those investment vehicles add value, three dimensions will be taken into account. First, this study will analyse whether hedge funds have had higher returns than mutual funds and major equity indices for the last two decades. Secondly, in order to take into account the risk, the risk-adjusted performance of hedge funds will be discussed. This study will underline the fact that hedge fund returns datasets are biased and that traditional methods to adjust for the risk fail to properly capture the risk of hedge funds. Therefore, modern techniques have to be used in order to properly assess the risk-adjusted performance. Finally, the potential diversification that hedge funds can provide as part of a portfolio will be discussed. Keywords funds, investors, returns