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Activity Number:
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100
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 7, 2006 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #305945 |
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Title:
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A Computational Approach to Bayesian Portfolio Selection
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Author(s):
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Refik Soyer*+
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Companies:
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The George Washington University
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Address:
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Funger Hall 415 Decision Sciences, Washington, DC, 20052,
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Keywords:
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decision analysis ; stochastic volatility ; MCMC
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Abstract:
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We consider multiperiod portfolio selection problems for a decisionmaker with a specified utility function when the variance of security returns is described by a discrete time stochastic model. We will present the Bayesian decision theoretic setup for the problem. The solution involves a dynamic programming formulation and backward induction. We will present a simulation-based method to solve these problems, adopting an approach that replaces the preposterior analysis by a surface fitting--based optimization approach. We will provide examples to illustrate the implementation of our approach.
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