Risk-Sensitive Dividend Problems

TL;DR

This paper addresses a risk-averse optimal dividend payout problem in discrete time, providing solutions for exponential and power utility functions and characterizing optimal policies with unbounded rewards.

Contribution

It offers a complete solution to the risk-sensitive dividend problem in discrete time for specific utility functions, extending previous continuous-time analyses.

Findings

Derived optimal dividend policies with unbounded rewards

Extended Markov decision process methods to risk-sensitive utility functions

Provided structural insights into history-dependent dividend strategies

Abstract

We consider a discrete-time version of the popular optimal dividend pay-out problem in risk theory. The novel aspect of our approach is that we allow for a risk averse insurer, i.e., instead of maximising the expected discounted dividends until ruin we maximise the expected utility of discounted dividends until ruin. This task has been proposed as an open problem in H. Gerber and E. Shiu (2004). The model in a continuous-time Brownian motion setting with the exponential utility function has been analysed in P. Grandits, F. Hubalek, W. Schachermayer and M. Zigo (2007). Nevertheless, a complete solution has not been provided. In this work, instead we solve the problem in discrete-time setup for the exponential and the power utility functions and give the structure of optimal history-dependent dividend policies. We make use of certain ideas studied earlier in N. B\"auerle and U. Rieder (2013), where Markov decision processes with general utility functions were treated. Our analysis, however, include new aspects, since the reward functions in this case are not bounded.