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

Kerem UğurluTomasz Brzeczek
Published in: Central European journal of operations research (2022)
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.
Keyphrases
  • public health
  • healthcare
  • machine learning
  • mental health
  • deep learning