Expected utility maximization and conditional value-at-risk deviation-based Sharpe ratio in dynamic stochastic portfolio optimization

Title:

Expected utility maximization and conditional value-at-risk deviation-based Sharpe ratio in dynamic stochastic portfolio optimization

Creator:

Kilianová, Soňa and Ševčovič, Daniel

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:50fe5530-e67c-4e25-9071-64908d7d914b
uuid:50fe5530-e67c-4e25-9071-64908d7d914b
doi:10.14736/kyb-2018-6-1167

Subject:

dynamic stochastic portfolio optimization, Hamilton-Jacobi-Bellman equation, Conditional value-at-risk, CVaRD-based Sharpe ratio, and CVaRD-based Sharpe ratio

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

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.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Kybernetika | 2018 Volume:54 | Number:6

Harvested from:

CDK

Metadata only:

false