https://www.nber.org/system/files/working_papers/w11370/w11370.pdf

What Matters for Financial Development? Capital Controls, Institutions, and Interactions

This article presents some new results on an unexplored dataset on hedge fund performance. The results indicate that hedge funds follow strategies that are dramatically different from mutual funds, and support the claim that these strategies are highly dynamic. The article finds five dominant investment styles in hedge funds, which when added to Sharpe’s (1992) asset class factor model can provide an integrated framework for style analysis of both buy-and-hold and dynamic trading strategies.

/pdf/empirical-characteristics-of-dynamic-trading-strategies-the-1v6l37b0w0.pdf

Empirical Characteristics of Dynamic Trading Strategies: The Case of Hedge Funds

This article characterizes the systematic risk exposures of hedge funds using buy-and-hold and option-based strategies. Our results show that a large number of equity-oriented hedge fund strategies exhibit payoffs resembling a short position in a put option on the market index and therefore bear significant left-tail risk, risk that is ignored by the commonly used mean-variance framework. Using a mean-conditional value-at-risk framework, we demonstrate the extent to which the mean-variance framework underestimates the tail risk. Finally, working with the systematic risk exposures of hedge funds, we show that their recent performance appears significantly better than their long-run performance. It is well accepted that the world of financial securities is a multifactor world consisting of different risk factors, each associated with its own factor risk premium, and that no single investment strategy can span the entire ‘‘risk factor space.’’ Therefore investors wishing to earn risk premia associated with different risk factors need to employ different kinds of investment strategies. Sophisticated investors, like endowments and pension funds, seem to have recognized this fact as their portfolios consist

/pdf/risks-and-portfolio-decisions-involving-hedge-funds-3ddeaoadsv.pdf

Risks and Portfolio Decisions Involving Hedge Funds

Hedge fund strategies typically generate option-like returns. Linear-factor models using benchmark asset indices have difficulty explaining them. Following the suggestions in Glosten and Jagannathan (1994), this article shows how to model hedge fund returns by focusing on the popular “trend-following” strategy. We use lookback straddles to model trend-following strategies, and show that they can explain trend-following funds’ returns better than standard asset indices. Though standard straddles lead to similar empirical results, lookback straddles are theoretically closer to the concept of trend following. Our model should be useful in the design of performance benchmarks for trend-following funds.

/pdf/the-risk-in-hedge-fund-strategies-theory-and-evidence-from-3mwkha1h9a.pdf

The Risk in Hedge Fund Strategies: Theory and Evidence from Trend Followers

http://www3.tcmb.gov.tr/konferanslar/fsr/Sherman.pdf

Econometric measures of connectedness and systemic risk in the finance and insurance sectors

Following a review of the data and methodological difficulties in applying conventional models used for traditional asset class indexes to hedge funds, this article argues against the conventional approach Instead, in an extension of previous work on asset-based style (ABS) factors, the article proposes a model of hedge fund returns that is similar to models based on arbitrage pricing theory, with dynamic risk-factor coefficients For diversified hedge fund portfolios (as proxied by indexes of hedge funds and funds of hedge funds), the seven ABS factors can explain up to 80 percent of monthly return variations Because ABS factors are directly observable from market prices, this model provides a standardized framework for identifying differences among major hedge fund indexes that is free of the biases inherent in hedge fund databases

Hedge Fund Benchmarks: A Risk-Based Approach

It is well known that the pro forma performance of a sample of investment funds contains biases. These biases are documented in Brown, Goetzmann, Ibbotson, and Ross (1992) using mutual funds as subjects. The organization structure of hedge funds, as private and often offshore vehicles, makes data collection a much more onerous task, amplifying the impact of performance measurement biases. Theis paper reviews these biases in hedge funds. We also propose using funds-of-hedge funds to measure aggregate hedge fund performance, based on the idea that the investment experience of hedge fund investors can be used to estimate the performance of hedge funds.

Performance Characteristics of Hedge Funds and Commodity Funds: Natural vs. Spurious Biases

We use a comprehensive data set of funds-of-funds to investigate performance, risk, and capital formation in the hedge fund industry from 1995 to 2004. While the average fund-of-funds delivers alpha only in the period between October 1998 and March 2000, a subset of funds-of-funds consistently delivers alpha. The alpha-producing funds are not as likely to liquidate as those that do not deliver alpha, and experience far greater and steadier capital inflows than their less fortunate counterparts. These capital inflows attenuate the ability of the alpha producers to continue to deliver alpha in the future.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1883531_code267374.pdf?abstractid=778124&mirid=2

William Fung

Papers

Empirical Characteristics of Dynamic Trading Strategies: The Case of Hedge Funds

The Risk in Hedge Fund Strategies: Theory and Evidence from Trend Followers

Hedge Fund Benchmarks: A Risk-Based Approach

Performance Characteristics of Hedge Funds and Commodity Funds: Natural vs. Spurious Biases

Hedge Funds: Performance, Risk, and Capital Formation