Portfolio optimization managing value at risk under heavy tail return, using stochastic maximum principle

• Published in: Stochastic analysis and applications Vol. 39; no. 6; pp. 1025 - 1049
• Main Authors: Biswas, Subhojit, Ghosh, Mrinal K., Mukherjee, Diganta
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 02.11.2021; Taylor & Francis Ltd
• Subjects: Distribution functions; Dynamic programming; Empirical equations; Exact solutions; Expected utility; finance; Hamiltonian system; heavy tailed distribution; Maximum principle; Normality; Optimization; portfolio optimization; Quantiles; Risk management; Smoothness; stochastic maximum principle; Strategy

We consider an investor whose portfolio consists of a single risky asset and a risk free asset. The risky asset's return has a heavy tailed distribution and thus does not have higher order moments. Hence, she aims to maximize the expected utility of the portfolio defined in terms of the median...