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Activity Number: 15
Type: Topic Contributed
Date/Time: Sunday, August 3, 2014 : 2:00 PM to 3:50 PM
Sponsor: Business and Economic Statistics Section
Abstract #313262
Title: Robust Bayesian Portfolio Choice
Author(s): Airu Cheng*+ and Evan Anderson
Companies: Northern Illinois University and Northern Illinois University
Keywords: mean-variance analysis ; model uncertainty ; parameter uncertainty ; Generalized Method of Moments
Abstract:

We propose a Bayesian averaging portfolio choice strategy with excellent out-of-sample performance. Every period a new model is born that assumes means and covariances are constant over time. Each period we estimate model parameters, update model probabilities, and compute robust portfolio choices by taking into account model uncertainty, parameter uncertainty, and non-stationarity. The portfolio choices achieve higher out-of-sample Sharpe ratios and certainty equivalents than rolling window schemes, the 1/N approach, and other leading strategies on a majority of 24 datasets.


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