Bayesian Inference and Portfolio Efficiency (Revised: 4-93)
Robert McCulloch and
Rodney L. White Center for Financial Research Working Papers from Wharton School Rodney L. White Center for Financial Research
Bayesian posterior distributions allow one to investigate the approximate efficiency of a portfolio without specifying the maximum degree of inefficiency a priori. The difference in expected returns between the value-weighted equity portfolio and an efficient portfolio of equal variance has a disperse posterior distribution, and our experiments confirm that such uncertainty is inherent in the sample sizes typically encountered in empirical studies. The maximum correlation between the value-weighted portfolio and an efficient portfolio has a posterior that is concentrated, often around low values, but this result appears to reflect nonlinearity in the function rather than information in the sample.
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Working Paper: Bayesian Inference and Portfolio Efficiency (Revised: 4-93)
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