Distorted probability operator for dynamic portfolio optimization in times of socio-economic crisis

Kerem Uğurlu, Tomasz Brzeczek

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

A robust optimal control of discrete time Markov chains with finite terminal T and bounded costs or wealth using probability distortion is studied. The time inconsistency of these distortion operators and hence its lack of dynamic programming are discussed. Due to that, dynamic versions of these operators are introduced, and its availability for dynamic programming is demonstrated. Based on dynamic programming algorithm, existence of the optimal policy is justified and an application of the theory to portfolio optimization along with a numerical study is also presented.

Original languageEnglish
JournalCentral European Journal of Operations Research
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Dynamic programming
  • Markov decision processes
  • Mathematical finance
  • Probability distortion
  • Risk management

ASJC Scopus subject areas

  • Management Science and Operations Research

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