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Expected Utility Maximization and Conditional Value-at-Risk\n Deviation-based Sharpe Ratio in Dynamic Stochastic Portfolio Optimization

2018/10/27 by Soňa Kilianová, Kilianova, Sona, Daniel Ševčovič +1
Decision Sciences · Economics, Econometrics and Finance · #34E05 #35K55 #70H20 #90C15 #91B16 #91B70 #FOS: Economics and business #Financial Markets and Investment Strategies #Portfolio Management (q-fin.PM) #Risk and Portfolio Optimization #Stochastic processes and financial applications

paper · pdf · doi:10.48550/arxiv.1810.11619

openalex publication_date 2018/10/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper we investigate the expected terminal utility maximization\napproach for a dynamic stochastic portfolio optimization problem. We solve it\nnumerically by solving an evolutionary Hamilton-Jacobi-Bellman equation which\nis transformed by means of the Riccati transformation. We examine the\ndependence of the results on the shape of a chosen utility function in regard\nto the associated risk aversion level. We define the\n Conditional value-at-risk deviation (CVaRD) based Sharpe ratio for\nmeasuring risk-adjusted performance of a dynamic portfolio. We compute optimal\nstrategies for a portfolio investment problem motivated by the German DAX 30\nIndex and we evaluate and analyze the dependence of the CVaRD-based Sharpe\nratio on the utility function and the associated risk aversion level.\n

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