Kilianová, Soňa; Ševčovič, Daniel Expected utility maximization and conditional value-at-risk deviation-based Sharpe ratio in dynamic stochastic portfolio optimization. (English) Zbl 1463.91128 Kybernetika 54, No. 6, 1167-1183 (2018). Summary: In this paper we investigate the expected terminal utility maximization approach for a dynamic stochastic portfolio optimization problem. We solve it numerically by solving an evolutionary Hamilton-Jacobi-Bellman equation which is transformed by means of the Riccati transformation. We examine the dependence of the results on the shape of a chosen utility function in regard to the associated risk aversion level. We define the conditional value-at-risk deviation (CVaRD) based Sharpe ratio for measuring risk-adjusted performance of a dynamic portfolio. We compute optimal strategies for a portfolio investment problem motivated by the German DAX 30 Index and we evaluate and analyze the dependence of the CVaRD-based Sharpe ratio on the utility function and the associated risk aversion level. Cited in 2 Documents MSC: 91G10 Portfolio theory 93E20 Optimal stochastic control Keywords:dynamic stochastic portfolio optimization; Hamilton-Jacobi-Bellman equation; conditional value-at-risk; CVaRD-based Sharpe ratio PDFBibTeX XMLCite \textit{S. Kilianová} and \textit{D. Ševčovič}, Kybernetika 54, No. 6, 1167--1183 (2018; Zbl 1463.91128) Full Text: DOI arXiv