Hedge Fund Styles Research Articles

Risk in Fixed-Income Hedge Fund Styles

Risk in Fixed-Income Hedge Fund Styles

An Econometric Model of Serial Correlation and Illiquidity in Hedge Fund Returns

The returns to hedge funds and other alternative investments are often highly serially correlated in sharp contrast to the returns of more traditional investment vehicles such as long-only equity portfolios and mutual funds. In this paper, we explore several sources of such serial correlation and show that the most likely explanation is illiquidity exposure, i.e., investments in securities that are not actively traded and for which market prices are not always readily available. For portfolios of illiquid securities, reported returns will tend to be smoother than true economic returns, which will understate volatility and increase risk-adjusted performance measures such as the Sharpe ratio. We propose an econometric model of illiquidity exposure and develop estimators for the smoothing profile as well as a smoothing-adjusted Sharpe ratio. For a sample of 908 hedge funds drawn from the TASS database, we show that our estimated smoothing coefficients vary considerably across hedge-fund style categories and may be a useful proxy for quantifying illiquidity exposure.

Hedge Funds: A Walk Through The Graveyard

Prior research has identified a number of biases in hedge fund databases, notably due to survivorship and selective backfilling of returns. We update and extend on research by examining impact of survivorship on higher moments of distribution of hedge fund returns (volatility, skew and kurtosis) and pattern of survivorship across different hedge fund style groups. We also consider probable causes of death after trawling extensive TASS 'notes' fields for over 1000 defunct funds, referred to affectionately by TASS as the graveyard.

Portfolio Optimization and Hedge Fund Style Allocation Decisions

This article attempts to evaluate the out-of-sample performance of an improved estimator of the covariance structure of hedge fund index returns, focusing on its use for optimal portfolio selection. Using data from CSFB/Tremont hedge fund indices, we find that ex-post volatility of minimum variance portfolios generated using implicit factor-based estimation techniques is between 1.5 and 6 times lower than that of a value-weighted benchmark, such differences being both economically and statistically significant. This strongly indicates that optimal inclusion of hedge funds in an investor portfolio can potentially generate a dramatic decrease in the portfolio volatility on an out-of-sample basis. Differences in mean returns, on the other hand, are not statistically significant, suggesting that the improvement in terms of risk control does not necessarily come at the cost of lower expected returns.

Risk in Fixed-Income Hedge Fund Styles

The authors apply principal components analysis to groups of fixed-income hedge funds to extract common sources of risk and return. These common sources of risk are related to market risk factors, such as changes in interest rate spreads and options on interest rate spreads, or asset-based style factors (ABS). The conclusion is that fixed-income hedge funds tend to be exposed to a common ABS factor, credit spreads.

What the 'Indexes' Don't Tell You about Hedge Funds

In recent years, the number of firms offering hedge fund products, and assets allocated to hedge funds have grown at a rapid rate. This growth has been accompanied by a commensurate increase in the number of hedge fund research articles. A striking limitation of many analyses published to date is their focus on so-called indices, which in reality reflect the average returns of peer managers, categorized by investment style. We focus instead on individual manager return histories and investigate the relationship between individual manager performance and investable equity or fixed income market indexes. Our goal is to obtain reliable estimates of hedge funds' sensitivity to market returns, and to get a sense of the variability of outcomes across individual hedge fund managers of a given style. Using manager-level performance data from the Hedge Fund Research database, we refine and apply methods suggested in previous studies. Our approach has five notable features: - We correct for possible distortions in returns introduced by performance-based fees by using inferred gross-of-fees returns. - We regress individual manager returns on contemporaneous and lagged returns of broad market equity or fixed income indexes, as appropriate for the style of the manager being analyzed. - We correct for autocorrelation of residuals when appropriate. - We modify our regression models to detect differences in manager sensitivity to index returns in bull and bear markets. - We model participation-linked fees as call options and evaluate their impact on performance in a separate step. Our principal finding is that substantial variation in market-relative risk exists across managers within hedge fund style universes. Many of the style-level effects reported by other researchers were not observed in a majority of individual managers. This result suggests that informed manager selection helps investors avoid the unattractive performance characteristics identified by style-level analyses. Further, we find that the dramatic asymmetry noted by previous studies is largely a function of the volatility induced by the 1998 Russian Debt Crisis rather than some inherent asymmetry in hedge fund return patterns. For practitioners, the upshot is that designing a hedge fund strategy is an intensively bottom-up exercise. Generalizations at the style level are of little use when formulating a hedge fund strategy in the real world.

The Role of Hedge Funds in International Financial Markets

This paper analyses the risk and return characteristics of a wide universe of hedge funds in the period 1990–2000. Most major categories of hedge funds are found to have outperformed (often by a considerable margin) the performance of traditional asset classes. The potential impact of hedge fund trading on market spreads and volatilities is examined especially in the period 1998, so as to provide some guidelines in terms of regulation of such funds. It is shown, however, that despite hedge fund difficulties in that period, the inclusion of hedge funds in investor portfolios definitely moves the efficiency frontier outwards, and allows significantly higher levels of returns for given levels of risk. This is primarily because of the low level of correlation of certain hedge fund styles, especially arbitrage strategies, with other hedge fund styles and with traditional assets.(J.E.L.: G10, G11, G14, G23).

Portfolio Optimization and Hedge Fund Style Allocation Decisions

This paper attempts to evaluate the out-of-sample performance of an improved estimator of the covariance structure of hedge fund index returns, focusing on its use for optimal portfolio selection. Using data from CSFB-Tremont hedge fund indices, we find that ex-post volatility of minimum variance portfolios generated using implicit factor based estimation techniques is between 1.5 and 6 times lower than that of a value-weighted benchmark, such differences being both economically and statistically significant. This strongly indicates that optimal inclusion of hedge funds in an investor portfolio can potentially generate a dramatic decrease in the portfolio volatility on an out-of-sample basis. Differences in mean returns, on the other hand, are not statistically significant, suggesting that the improvement in terms of risk control does not necessarily come at the cost of lower expected returns.

Asset-Based Hedge-Fund Styles and Portfolio Diversification

Asset-based style factors link returns of hedge-fund strategies to observed market prices. They provide explicit and unambiguous descriptions of hedge-fund strategies that tells us both the nature as well as the quantity of risk. Asset-based style factors are key inputs to portfolio construction and for benchmarking hedge-fund performance on a risk-adjusted basis. The model in Fung and Hsieh (2001a) and Mitchell Pulvino (2001) can be used to construct asset-based style factors. In is shown that the model in Fung and Hsieh (2001a) correctly predicted the return behavior trend-following strategies during out-of-sample periods and particularly so during stressful market conditions like September 2001.

Hedge Fund and Commodity Fund Investments in Bull and Bear Markets

A primary motivation for investing in hedge funds and commodity funds is to diversify against falling stock prices. The authors evaluate the performance of 16 different such funds during rising and falling stock markets between 1990 and 1998 both as stand–alone assets and as portfolio assets. They use the Sharpe ratio and alternative safety–first criteria to evaluate performance. The conclusion is that commodity funds generally provide more downside protection than hedge funds. Commodity funds have higher returns in bear markets than hedge funds, and generally have an inverse correlation with stock returns in bear markets. Hedge funds typically exhibit a higher positive correlation with stock returns in bear markets than in bull markets. Three hedge fund styles—market–neutral, event–driven, and global macro—provide fairly good downside protection with more attractive returns over all markets than commodity funds.

Hedge Funds and Commodity Fund Investments in Bull and Bear Markets

This study examines the performance of sixteen different hedge fund and commodity fund investment styles during rising and falling stock prices over the period 1990:01 through 1998:08. Since a primary motivation for investing in hedge funds and commodity funds is to diversify against falling stock prices, it is important to examine the performance of these funds during bear stock markets. The study evaluates hedge funds and commodity funds both as stand-alone assets and as portfolio assets, and in both bull and bear stock markets. In addition, it utilizes the Sharpe ratio as well as alternative safety-first performance criteria to evaluate the funds. We conclude that commodity funds generally provide greater downside protection than do hedge funds. Commodity funds have higher returns in bear markets than do hedge funds, and generally have an inverse correlation with stock returns in bear markets, while hedge funds typically exhibit a higher positive correlation with stock returns in bear markets than in bull markets. However, three hedge fund styles - market-neutral, event-driven, and global macro - provide fairly good downside protection while still providing more attractive returns over all markets than do commodity funds.

A primer on hedge funds

In this paper, we provide a rationale for how hedge funds are organized and some insight on how hedge fund performance differs from traditional mutual funds. Statistical differences among hedge fund styles are used to supplement qualitative differences in the way hedge fund strategies are described. Risk factors associated with different trading styles are discussed. We give examples where standard linear statistical techniques are unlikely to capture the risk of hedge fund investments where the returns are primarily driven by non-linear dynamic strategies.