Yakun Liu, Jingchao Li, Jieming Zhou, Yingchun Deng
{"title":"优化投资和再保险,最大限度地提高提取前的提取概率","authors":"Yakun Liu, Jingchao Li, Jieming Zhou, Yingchun Deng","doi":"10.1007/s11009-024-10096-9","DOIUrl":null,"url":null,"abstract":"<p>In this paper, we study the optimal investment and proportional reinsurance problem for an insurer with short-selling and borrowing constraints under the expected value premium principle. The claim process follows a Brownian risk model with a drift. The insurer’s surplus is allowed to invest in one risk-free asset and one risky asset. By using the dynamic programming approach and solving the corresponding boundary-value problems, the optimization objective of maximizing the probability of drawup before drowdown is considered initially. The optimal strategy and the corresponding value function are derived through solving the Hamilton-Jacobi-Bellman (HJB) equation. Moreover, numerical examples are performed to illustrate the effects of model parameters on the optimal strategy. In addition, we verify the optimality of the strategies obtained from the dynamic programming principle by Euler method.</p>","PeriodicalId":18442,"journal":{"name":"Methodology and Computing in Applied Probability","volume":"24 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal Investment and Reinsurance to Maximize the Probability of Drawup Before Drawdown\",\"authors\":\"Yakun Liu, Jingchao Li, Jieming Zhou, Yingchun Deng\",\"doi\":\"10.1007/s11009-024-10096-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In this paper, we study the optimal investment and proportional reinsurance problem for an insurer with short-selling and borrowing constraints under the expected value premium principle. The claim process follows a Brownian risk model with a drift. The insurer’s surplus is allowed to invest in one risk-free asset and one risky asset. By using the dynamic programming approach and solving the corresponding boundary-value problems, the optimization objective of maximizing the probability of drawup before drowdown is considered initially. The optimal strategy and the corresponding value function are derived through solving the Hamilton-Jacobi-Bellman (HJB) equation. Moreover, numerical examples are performed to illustrate the effects of model parameters on the optimal strategy. In addition, we verify the optimality of the strategies obtained from the dynamic programming principle by Euler method.</p>\",\"PeriodicalId\":18442,\"journal\":{\"name\":\"Methodology and Computing in Applied Probability\",\"volume\":\"24 1\",\"pages\":\"\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2024-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Methodology and Computing in Applied Probability\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1007/s11009-024-10096-9\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Methodology and Computing in Applied Probability","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s11009-024-10096-9","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Optimal Investment and Reinsurance to Maximize the Probability of Drawup Before Drawdown
In this paper, we study the optimal investment and proportional reinsurance problem for an insurer with short-selling and borrowing constraints under the expected value premium principle. The claim process follows a Brownian risk model with a drift. The insurer’s surplus is allowed to invest in one risk-free asset and one risky asset. By using the dynamic programming approach and solving the corresponding boundary-value problems, the optimization objective of maximizing the probability of drawup before drowdown is considered initially. The optimal strategy and the corresponding value function are derived through solving the Hamilton-Jacobi-Bellman (HJB) equation. Moreover, numerical examples are performed to illustrate the effects of model parameters on the optimal strategy. In addition, we verify the optimality of the strategies obtained from the dynamic programming principle by Euler method.
期刊介绍:
Methodology and Computing in Applied Probability will publish high quality research and review articles in the areas of applied probability that emphasize methodology and computing. Of special interest are articles in important areas of applications that include detailed case studies. Applied probability is a broad research area that is of interest to many scientists in diverse disciplines including: anthropology, biology, communication theory, economics, epidemiology, finance, linguistics, meteorology, operations research, psychology, quality control, reliability theory, sociology and statistics.
The following alphabetical listing of topics of interest to the journal is not intended to be exclusive but to demonstrate the editorial policy of attracting papers which represent a broad range of interests:
-Algorithms-
Approximations-
Asymptotic Approximations & Expansions-
Combinatorial & Geometric Probability-
Communication Networks-
Extreme Value Theory-
Finance-
Image Analysis-
Inequalities-
Information Theory-
Mathematical Physics-
Molecular Biology-
Monte Carlo Methods-
Order Statistics-
Queuing Theory-
Reliability Theory-
Stochastic Processes