Theses and Dissertations - UTB/UTPA

Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Business Administration

First Advisor

Dr. Haiwei Chen

Second Advisor

Dr. Damian Damianov

Third Advisor

Dr. Jan Smolarski


This dissertation consists of two essays on hedge fund performance. The first essay models exposure of hedge fund to risk factors and examines time-varying performance of hedge funds. From existing models such as ABS-factor model, SAC-factor model, and four-factor model, we extract the best six factors for each hedge fund portfolio by investment strategy. Then, we find combinations of risk factors that most explain variance in performance of each hedge fund portfolio by investment strategy. The results show instability of coefficients in the performance attribution regression. Incorporating time-varying factor exposure feature would be the best way to appropriately measure hedge fund performance. Furthermore, the optimal models with fewer factors exhibit greater explanatory power than existing models. Time-varying model customized by investment strategy of hedge funds would clearly show how sensitive to risk factors managements of hedge funds are according to market conditions

In the second essay, we first conduct multinomial logistic regression analysis to see how hedge fund attributes affect hedge fund managers‟ decision of whether to offer a hurdle rate and/or high-watermark. Hedge funds taking more risky position and collecting high performance fee are more likely to offer hurdle rate and/or high-watermark. Second, we conduct cross-sectional regression analysis to see how hedge fund attributes affect hedge fund performance. Our results indicate that hurdle rate and high-watermark are restrictions for hedge fund managers on collecting fee and that hurdle rate and high-watermark cannot be considered to be incentives. We also find that hedge funds collecting high performance fee and having large amount of funds are more likely to outperform those collecting low performance fee and having small amount of funds.

While conducting cross-sectional regression analysis, we use three different measures of hedge fund performance: alpha, palpha and Sharpe ratio. Alpha and palpha are obtained from the optimal model by investment strategy controlling for hedge fund risk associated with risk factors different by its investment strategy. In addition, we control for survivorship and instant history biases. So, our results from alpha and palpha are more credible than those of Soydemir et al. (2012) which employs only Sharpe ratio.


Copyright 2012 Sang Heon Shin. All Rights Reserved.

Granting Institution

University of Texas-Pan American