Asset Allocation Under Distribution Uncertainty
Marcin T. Kacperczyk
New York University (NYU) - Leonard N. Stern School of Business; National Bureau of Economic Research (NBER); New York University (NYU) - Department of Finance
University of Texas at Austin - McCombs School of Business
April 18, 2011
McCombs Research Paper Series No. IROM-01-11
This paper shows how uncertainty about the type of return distribution (distribution uncertainty) can be incorporated in asset allocation decisions by using a novel, Bayesian semiparametric approach. To evaluate the economic importance of distribution uncertainty, the extent of changes in ex-ante optimal asset allocations of investors who factor in distribution uncertainty into their portfolio model is examined. The key findings are: (a) distribution uncertainty is highly time varying; (b) compared to investors facing parameter uncertainty, investors under distribution uncertainty, on average, allocate less money to risky assets; their allocations are less variable; and their certainty-equivalent losses from ignoring distribution uncertainty can be economically significant; (c) portfolio strategies of such investors generate statistically higher returns, even after controlling for common factors.
Number of Pages in PDF File: 55
Keywords: Asset Allocation, Distribution Uncertainty, Bayesian Semiparametric Model
JEL Classification: G11, G12, C11, C14, C15working papers series
Date posted: April 20, 2011 ; Last revised: June 18, 2011
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