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

Steftcho Dokov, David P. Morton, Ivilina Popova

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

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.

Original languageEnglish (US)
Title of host publication2017 International Conference on Information Science and Communications Technologies, ICISCT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781538621684
DOIs
StatePublished - Dec 12 2017
Event2017 International Conference on Information Science and Communications Technologies, ICISCT 2017 - Tashkent, Uzbekistan
Duration: Nov 2 2017Nov 4 2017

Publication series

Name2017 International Conference on Information Science and Communications Technologies, ICISCT 2017
Volume2017-December

Other

Other2017 International Conference on Information Science and Communications Technologies, ICISCT 2017
CountryUzbekistan
CityTashkent
Period11/2/1711/4/17

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Software
  • Artificial Intelligence

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