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Published : 25.09.2014 | Author : admin | Categories : How To Bet On Football
Over the past years, a number of frameworks have emerged dividing hedge funds into several sub-categories, but the literature on the subject is still not in agreement on the number of distinct hedge fund investment styles. It should be apparent that, whilst impossible to cater for all sub-strategies depicted, hedge funds may be classified according to four broad themes as defined in the HFR database: Equity Hedge, Event Driven, Macro and Relative Value.
Tobias Adrian of the New York Fed looks at how to measure risk in the hedge fund industry, and uses the measures to assess current conditions.
Hedge funds—private investment partnerships that are not directly regulated—have grown in importance in recent years. A key determinant of hedge fund risk is the degree of similarity between the trading strategies of different funds. As this article shows, the distinction is more than a mere technicality: the correlation of hedge fund returns rose both in the period prior to the LTCM crisis and in recent times—but for different reasons.
Complementing this result is our finding that high correlations of returns generally do not precede increases in volatility in the hedge fund sector, but high covariances among hedge funds do.
The final part of our analysis compares hedge fund correlations and volatilities during the LTCM crisis with equity return correlations and volatilities. Hedge Fund RiskRisk is a critical component of hedge fund strategies, so the way in which it is measured is extremely important.
Cross-Sectional Dispersion of ReturnsOur preferred measure of risk is the cross-sectional dispersion of returns, which is the volatility of returns across funds at each point in time (see box).[4] One advantage of cross-sectional volatility as an indicator of hedge fund risk is that it captures the exact timing of spikes in risk. Alternative Correlation Measures Our finding that hedge fund correlations dropped to relatively low levels during the LTCM crisis differs from results in the contagion literature indicating that asset return correlations increase during crises.
The Temporal Relationship between Hedge Fund Covariances and Risk If the LTCM crisis was indeed preceded by elevated levels of hedge fund correlations, as our findings suggest, then it is reasonable to ask whether correlations predict volatilities—volatilities being our preferred measure of hedge fund risk.
A Comparison with Equity Market Comovement Our finding that the onset of the LTCM event was not associated with an increase in hedge fund correlations contrasts with other results showing how asset returns behave during financial crises.
Conclusion Our analysis of the relationship between hedge fund risk and comovement of returns generally produces no statistical evidence that increases in hedge fund correlations precede rises in hedge fund volatility. We also find that the evolution of hedge fund risk and comovement during the Long-Term Capital Management crisis differed from the behavior of broad financial market returns.
Follow the links below to search for Excel- and VBA-templates, or to find some additional information on hedge fund investments and related topics.
For visual purposes, a distinction is made between market directional and market neutral funds. Similar trading strategies can heighten risk when funds have to close out comparable positions in response to a common shock. The approach taken in this edition of Current Issues is to examine how closely together the funds’ returns move. The covariance across a group of funds essentially captures the extent to which their returns move together (or apart, in the case of negative covariance) in dollar terms.
While the LTCM collapse was preceded by high correlations and high covariances in an environment of increased hedge fund return volatility, the current environment is characterized by only average levels of covariances and low volatility. By the time the LTCM crisis broke in August 1998, hedge fund return correlations had dropped from their peak levels in 1996 and 1997 to a level that was not particularly high. This database has the advantage of including the returns of large hedge funds that do not report to the usual hedge fund databases.


By analyzing measures of risk across hedge funds, we seek to shed light on the evolution of risk in the hedge fund sector as a whole. The absolute value of returns is a measure of hedge fund volatility that increases with positive as well as with negative returns. This conclusion is reasonable, because covariances measure hedge fund return comovement in dollar terms while correlations are covariances normalized by volatilities. However, we do find that increases in hedge fund covariances tend to precede elevations in volatility. While the correlations of financial assets such as equities spiked at the same time as volatility shot up, hedge fund return correlations were not unusually high at the beginning of the crisis and they declined sharply as it unfolded.
Credit Suisse First Boston, “Equity Research Sector Review: Hedge Funds and Investment Banks,” March 9, 2005. It should be noted, however, that hedge funds belonging to the various sub-classifications may not be easily defined as strictly directional or market neutral. It should also be noted that Managed Futures, also referred to as Commodity Trading Advisors (CTAs), developed independently from hedge funds. Author Tobias Adrian explains that recent high correlations among hedge fund returns—returns moving in the same direction when facing similar market conditions—could suggest concentrations of risk comparable to those preceding the hedge fund crisis of 1998. Indeed, the collapse of the hedge fund Long-Term Capital Management (LTCM) in 1998 seemed to confirm fears that heavy losses by hedge funds have the potential to drain significant liquidity from key financial markets (Table 1). For example, many funds had to close out positions during the LTCM crisis to meet margin calls and satisfy risk management constraints. If the returns of many funds are either high or low at the same time, the funds could record losses simultaneously, with possible adverse consequences for market liquidity and stability.
A high covariance between two funds means that when one earns a larger-than-normal amount of money, the other is likely to do the same. Trading strategies are classified into ten groups according to asset class and investment style.[3] The indexes are available monthly since January 1994—except for Multi-Strategy, which is available since April 1994.
This approach is preferable to examining the riskiness of individual funds or strategies because it yields more representative results. This is an important advantage, because hedge funds use dynamic trading strategies and hold derivatives, practices that lead to time-varying exposures to systematic risk.[5] By comparison, a common alternative approach—gauging risk by calculating volatilities over twelve- or twenty-four-month periods and then averaging across funds—has the potential disadvantage of averaging periods of high and low volatility, making it difficult to determine the precise timing of shocks to risk. Recall that covariances are a measure of hedge fund comovement in dollar terms; correlations are covariances divided by volatilities (see box).
System risk can occur when returns in the hedge fund sector move significantly in dollar terms; whether such movement is high or low relative to the level of volatilities appears to be less relevant. This finding reflects the diverse effects of the crisis on the outcomes of different hedge fund strategies: some hedge funds profited during the event while others registered losses.
HFR includes 31 different sub-strategies and differentiates between four major classifications (Macro, Equity Hedge, Event Driven and Relative Value). Note that differentiation between directional and market neutral funds is defined by the author.
It is thus questionable whether or not they should be included in a hedge fund classification framework.
Additionally, clients can tailor views and reports for alternative investments such as hedge funds and private equity that require metrics unique to their specific asset classes.


Because volatility and covariances are lower today, the current hedge fund environment differs from the 1998 environment. These ongoing concerns about hedge fund vulnerability, coupled with the rapid growth of the funds, underscore the importance of understanding risk in this sector.
However, it matters little if two funds tend to gain or lose at the same time if such joint gains and losses are only a small fraction of the funds’ total returns.
By contrast, equity return correlations and volatilities increased sharply, a phenomenon known as financial market contagion.[2] Thus, this episode provides evidence that while returns on equities and similar financial assets tend to move together during crises, returns on hedge funds tend to react independently, reflecting the differences in hedge fund exposures to various shocks. The data reveal that average returns and standard deviations varied widely across hedge fund strategies during the 1994-2006 period (Table 2).
An increase in correlations can stem either from an increase in covariances or from a decrease in volatilities.[6] The spike in cross-sectional volatility in August 1998, depicted earlier in Chart 1, was accompanied by a large negative covariance of hedge fund returns (Chart 3). Recently, hedge fund covariance has increased, but it is not at particularly high levels by historical standards.
McGuire, Remolona, and Tsatsaronis (2005) construct measures of hedge fund leverage using rolling factor exposures of hedge fund returns.
Therefore, analysts “normalize” this measure by dividing the covariance of fund returns by the returns’ total variability. The unusually high correlation among hedge funds in the current environment is therefore attributable primarily to low hedge fund volatility—a reflection of the generally low volatility of financial assets.
This calculation tells us how closely hedge fund returns move together relative to their overall volatility—a different measure of comovement known as correlation. This pattern of covariances over time indicates that hedge fund returns diverged significantly as markets reacted to the Russian default. For instance, the correlation of different funds’ returns may rise either because the returns have moved more closely together (their covariance has increased) or because their volatility has fallen. The response by hedge funds was a closing out of positions, leading to the September increase in cross-sectional covariance.
Thereafter, covariances remained at fairly low levels, reflecting the reduced risk exposures of the funds. Chart 4 presents the cross-sectional correlation of hedge fund returns together with the twelve-month moving average.
However, a comparison of Chart 4 with Charts 1 and 3 shows that the source of the elevated levels of hedge fund correlations before the LTCM crisis differs from the source in recent months. As we observed earlier, hedge fund correlations did not spike during either the Russian default or the LTCM event.
Taken together, these results suggest that the investment strategies of hedge funds differ substantially from those of marginal equity investors. In particular, the spike in hedge fund cross-sectional volatility in August 1998 illustrates theheterogeneity of hedge fund investment strategies. In a related study, Boyson, Stahel, and Stulz (2006) find no evidence of contagion between hedge funds and market indicators—a result consistent with our finding that spikes in correlations and volatilities in the equity market do not coincide with those of hedge fund returns.



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