English
Related papers

Related papers: Robust Optimal Investment and Reinsurance Problems…

200 papers

This paper studies the optimal dividend problem with a bounded payout rate in a partially observed regime-switching diffusion model, where, in practice, the market regime is unobserved and key model parameters are unknown. To address this…

Optimization and Control · Mathematics 2026-01-29 Zhongqin Gao , Yan Lv , Jingmin He

This paper considers nonlinear regular-singular stochastic optimal control of large insurance company. The company controls the reinsurance rate and dividend payout process to maximize the expected present value of the dividend pay-outs…

Risk Management · Quantitative Finance 2010-08-31 Zongxia Liang , Jicheng Yao

In this paper, an optimization problem for the monotone mean-variance(MMV) criterion is considered in the perspective of the insurance company. The MMV criterion is an amended version of the classical mean-variance(MV) criterion which…

Optimization and Control · Mathematics 2022-12-05 Bohan Li , Junyi Guo , Linlin Tian

We study optimal investment problem for a diffusion market consisting of a finite number of risky assets (for example, bonds, stocks and options). Risky assets evolution is described by Ito's equation, and the number of risky assets can be…

Probability · Mathematics 2008-12-02 Nikolai Dokuchaev

This paper considers an insurance company that faces two key constraints: a ratcheting dividend constraint and an irreversible reinsurance constraint. The company allocates part of its reserve to pay dividends to its shareholders while…

Optimization and Control · Mathematics 2025-12-22 Tim J. Boonen , Engel John C. Dela Vega

Managing insurance and financial risk when data is limited is a key task in the insurance industry. In this paper, we focus on cases where the risk distribution is modeled as a mixture with some components estimable to high precision or…

Optimization and Control · Mathematics 2026-03-03 N. D. Shyamalkumar , Tianrun Wang

We study a reinsurer who faces multiple sources of model uncertainty. The reinsurer offers contracts to $n$ insurers whose claims follow compound Poisson processes representing both idiosyncratic and systemic sources of loss. As the…

Risk Management · Quantitative Finance 2024-10-03 Emma Kroell , Sebastian Jaimungal , Silvana M. Pesenti

In this work we investigate the optimal proportional reinsurance-investment strategy of an insurance company which wishes to maximize the expected exponential utility of its terminal wealth in a finite time horizon. Our goal is to extend…

Risk Management · Quantitative Finance 2019-04-04 Matteo Brachetta , Claudia Ceci

In this paper, we study the optimal stopping problem in the so-called exploratory framework, in which the agent takes actions randomly conditioning on current state and an entropy-regularized term is added to the reward functional. Such a…

Optimization and Control · Mathematics 2023-09-04 Yuchao Dong

We study the optimal investment-consumption problem for a member of defined contribution plan during the decumulation phase. For a fixed annuitization time, to achieve higher final annuity, we consider a variable consumption rate. Moreover,…

Portfolio Management · Quantitative Finance 2020-08-18 Hassan Dadashi

This paper explores the optimal investment problem of a renewal risk model with generalized Erlang distributed interarrival times. The phases of the Erlang interarrival time is assumed to be observable. The price of the risky asset is…

Optimization and Control · Mathematics 2025-06-04 Linlin Tian , Yixuan Tian , Bohan Li , Guoqing Li

This paper considers an insurer with two collaborating business lines that must make three critical decisions: (1) dividend payout, (2) a combination of proportional and excess-of-loss reinsurance coverage, and (3) capital injection between…

Optimization and Control · Mathematics 2025-11-17 Tim J. Boonen , Engel John C. Dela Vega

This paper studies optimal investment from the point of view of an investor with longevity-linked liabilities. The relevant optimization problems rarely are analytically tractable, but we are able to show numerically that liability driven…

Risk Management · Quantitative Finance 2013-08-01 Helena Aro , Teemu Pennanen

In this work, we address the problem of determining reliable policies in reinforcement learning (RL), with a focus on optimization under uncertainty and the need for performance guarantees. While classical RL algorithms aim at maximizing…

Machine Learning · Computer Science 2025-10-22 Nadir Farhi

We consider an optimal dividend payout problem for an insurance company whose surplus follows the classical Cram\'er-Lundberg model. The dividend rate is subject to a ratcheting constraint (i.e., it must be nondecreasing over time), and the…

Optimization and Control · Mathematics 2026-04-07 Chonghu Guan , Zuo Quan Xu

Safe reinforcement learning (RL) aims to learn policies that satisfy certain constraints before deploying them to safety-critical applications. Previous primal-dual style approaches suffer from instability issues and lack optimality…

Machine Learning · Computer Science 2022-06-20 Zuxin Liu , Zhepeng Cen , Vladislav Isenbaev , Wei Liu , Zhiwei Steven Wu , Bo Li , Ding Zhao

In this paper we continue investigating the optimal dividend and investment problems under the Sparre Andersen model. More precisely, we assume that the claim frequency is a renewal process instead of a standard compound Poisson process,…

Probability · Mathematics 2019-09-02 Lihua Bai , Jin Ma

In this paper, we assume an insure is allowed to purchase proportional reinsurance and can invest his or her wealth into the financial market where a savings account, stocks and bonds are available. Different from classical optimal…

Mathematical Finance · Quantitative Finance 2014-07-01 Xiaoxiao Zheng , Xin Zhang

We consider the challenge of finding a deterministic policy for a Markov decision process that uniformly (in all states) maximizes one reward subject to a probabilistic constraint over a different reward. Existing solutions do not fully…

Machine Learning · Computer Science 2022-01-21 Jaeyoung Lee , Sean Sedwards , Krzysztof Czarnecki

We consider a general statistical learning problem where an unknown fraction of the training data is corrupted. We develop a robust learning method that only requires specifying an upper bound on the corrupted data fraction. The method…

Machine Learning · Statistics 2020-02-10 Muhammad Osama , Dave Zachariah , Peter Stoica