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Mean-Variance-Skewness-Kurtosis efficiency of portfolios computed via moment-based bounds

Steftcho DokovSchool of Computer and Information Engineering, INHA University in Tashkent, Tashkent, UzbekistanDavid P. MortonDepartment of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, USAIvilina PopovaDepartment of Finance and Economics, Texas State University, San Marcos, TX, USA
2017en
ABI

Abstract

We analyze moment-based bounding approximations on the expected value of a utility function. We show that optimizing these bounds yields a solution, which is mean-variance (MV) or MV-skewness-kurtosis (MVSK) efficient depending on how many moments are included in the approximation. To illustrate the approach we apply it to an asset allocation model with a shortfall utility function. Numerical results are presented for an out of sample trading strategy using sixteen years of daily trading for a portfolio of six assets. The strategy significantly outperforms a standard market index, Dow Jones Industrial Average.

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