Merton Investment Problem for the Hawkes-based Risk Model

Abstract

We study the Merton investment problem in insurance where the risk process is based on the general compound Hawkes process. That means the arrival of claims modeled with a Hawkes process and the modeled claim sizes follow a finite number of fixed jump sizes governed by a Markov chain evolution. The Merton investment problem in insurance is an optimal control problem and we use the dynamic programming method to derive the stochastic Hamilton-Jacobi-Bellman (SHJB) equation satisfied by the value function. The stochastic HJB equation yields a means to obtain the optimal control and thus the optimally controlled stochastic differential equation. Finally, using the claim size from the empirical data set, we simulate the optimal investment portfolio and risk process.