JSM 2005 - Toronto

Abstract #303043

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 324
Type: Contributed
Date/Time: Tuesday, August 9, 2005 : 2:00 PM to 3:50 PM
Sponsor: Business and Economics Statistics Section
Abstract - #303043
Title: Asymmetric Nonlinear Shrinkage Estimation in Optimal Portfolio Selection
Author(s): Andrew Siegel*+
Companies: University of Washington
Address: Business School, Seattle, WA, 98195, United States
Keywords: Stein Shrinkage ; Portfolio Estimation ; Finance
Abstract:

The goal of this research is to create a new statistical estimation method that will compensate for the expected loss of financial utility due to the use of statistical estimates obtained from past asset price data in forming utility maximizing portfolios. These new statistical estimates will be based on the financial-utility-motivated expected loss function for the associated multivariate statistical estimation problem. The functional form of this loss function is very different from the one for which Stein shrinkage estimators were developed, as was learned recently from theoretical approximations. In particular, the statistical loss function is asymmetric, in that losses differ by coordinate direction even when the covariance structure is symmetric. In addition, when approximated as a sum of squared errors, the loss function has nonlinear instead of constant weights. My hope is to use this knowledge to modify the Stein shrinkage weights and thereby improve the portfolio selection process.

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