Modeling the evolution of market uncertainty- Hedge Fund returns and Volatility of Aggregate Volatility within a dynamic perspective

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This paper investigates, in a dynamic perspective, whether uncertainty about equity market returns can have implications on hedge fund portfolio decisions over time. Therefore, the thesis wants to ascertain if the risk originated by that uncertainty is an explanatory factor for cross-sectional differences in returns over time. I develop this research employing an expanded version of the seven-factor Fung and Hsieh model (2004). To model exposures’ time-variation, I use three different Generalized Autoregressive Score models where: (i) all loadings are time-varying; (ii) only volatility-of-aggregate-volatility loading is time-varying; (iii) selected loadings are time-varying. I analyze a 9,381 hedge funds sample in the period between January 1994 and December 2013 and I find a negative and significant relation between time-varying volatility-of-aggregate-volatility exposures and hedge fund returns. Results show that exposure to uncertainty about volatility is a priced factor in the cross-section of hedge fund returns at a 0.01 significance level. The use of the ‘All time-varying parameters’ GAS model improves hedge fund performance evaluation, highlighting a clear time-variation in the data. Results are robust to other volatility-of-aggregate-volatility proxies.

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MSc in Finance

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Master Degree Project
2019:143

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