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Title: Time-varying liquidity and profitability of hedge funds
Author: Li, Sheng
ISNI:       0000 0004 2672 0129
Awarding Body: London School of Economics and Political Science
Current Institution: London School of Economics and Political Science (University of London)
Date of Award: 2007
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The hedge fund industry has grown to be one of the most important segments of the financial services industry. Hedge funds are known for employing highly dynamic trading strategies and investing in illiquid assets to increase their profitability. In this thesis, we develop and test the models that capture the time-varying nature of liquidity and profitability of hedge funds. The thesis begins with the study of the liquidity of hedge funds' investments. We propose a method for determining the factors that affect the (unobservable) liquidity of hedge fund investments. We find substantial evidence of time variation in the liquidity of hedge fund returns, and that this time variation can be predicted with readily available data. We then examine the impact of market dispersion on the profitability of hedge funds. Market dispersion is measured by cross-sectional volatility, that is, the standard deviation across all asset returns in one time period. We exploit the information held in the cross-sectional dispersion of equity returns and find that market dispersion and the performance of hedge funds are positively related across all equity-oriented hedge funds. Furthermore, to gain a better understanding of hedge fund risk, in the third chapter we assess the empirical success of Fung-Hsieh, Fama-French and Statistical Factor Models for explaining hedge fund returns and compare their explanatory power for the cross section of hedge fund returns. In the final chapter, we introduce a general and flexible framework for hedge fund performance evaluation and asset allocation: stochastic dominance theory. Our approach utilizes statistical tests for stochastic dominance to evaluate the performance of hedge funds. To illustrate the method's ability to work with non-normal distributions, we form hedge fund portfolios by using stochastic dominance criteria and examine the out-of-sample performance of these hedge fund portfolios. Compared to performance of portfolios of randomly selected hedge funds and mean-variance efficient hedge funds, our results show that fund selection method based on stochastic dominance criteria greatly improves the performance of hedge fund portfolios.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available