Authors

David Cru

Type

Text

Type

Dissertation

Advisor

Robert Frey | Hu, Jiaqiao | John Pinezich | Tucker, Ann | Peter Djuric.

Date

2010-05-01

Keywords

Applied Mathematics -- Economics, Finance -- Operations Research | Hedge Funds, Liquidity, Lockups, Markov Decision Process, Portfolio Optimization, Regime Switching

Department

Department of Applied Mathematics and Statistics

Language

en_US

Source

This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.

Identifier

http://hdl.handle.net/11401/70970

Publisher

The Graduate School, Stony Brook University: Stony Brook, NY.

Format

application/pdf

Abstract

Portfolio Selection as introduced by Harry Markowitz laid the foundation for Modern Portfolio Theory. However, the assumption that underlying asset returns follow a Normal Distribution and that investors are indierent to skew and kurtosis is not practically suited for the Hedge Fund environment. Additionally, the Lockup and Notice provisions built into Hedge Fund contracts make portfolio rebalancing dicult and justify the need for dynamic allocation strategies. Market conditions are dynamic, therefore, rebalancing constraints in the face of changing market environments can have a severe impact on return generation. There is a need for sophisticated yet tractable solutions to the multi-period problem of Hedge Fund portfolio construction and rebalancing. In this thesis we Generalize the Hedge Fund asset return distribution to a Multivariate K-mean Gaussian Mixture Distribution; model the multi-period Hedge Fund allocation problem as a Markov Decision Process (MDP); and propose practical rebalancing strategies that represent aconvergence of literature on Hedge Fund investing, Regime Switching, and Dynamic Portfolio Optimization.

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