Resampled Frontiers vs Diffuse Bayes: An Experiment
University of California at San Diego
Montclair State University - School of Business
Journal Of Investment Management, Vol. 1, No. 4, Fourth Quarter 2003
The experiment reported here compares two methods for handling uncertain inputs to a mean-variance analysis. Specifically, it compares Michaud's resampled frontier versus Bayesian inference with diffuse prior. A simulated "referee" generates ten "truths" about 8 asset classes. For each truth it randomly generates one hundred histories.
A simulated "Bayes Player" and "Michaud Player" process each history according to their respective methodologies, seeking portfolios to maximize given expected utility functions. Players are scored according to the actual utility achieved and their own estimates of this utility. The authors were surprised to find that, on average, the Michaud player won.
Keywords: Resampled Frontier, Bayesian analysis, diffuse Bayes, mean-variance analysis, sampling errors, Michaud
JEL Classification: G00Accepted Paper Series
Date posted: April 12, 2004
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