Year: 2025
Type: article
Abstract: This paper proposes a method for minimizing a Gerber–Shiu-like penalty function using a mini-batch stochastic projected gradient method (MBSPG) to determine optimal investment and reinsurance strategies. The Gerber–Shiu-like penalty function considers both the probability of ruin and the magnitude of loss when ruin occurs. To apply the MBSPG, we derive an unbiased estimator of the gradient via Malliavin calculus and establish Hölder continuity of the gradient. Numerical experiments demonstrate the effectiveness of our proposed method.
Source: JSIAM Letters
Authors: Yuta Otsuki, Shotaro Yagishita
Institution: The Institute of Statistical Mathematics
Language: English
Topic: Probability and Risk Models
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4412368899