ASTIN BulletinPub Date : 2023-07-14DOI: 10.1017/asb.2023.25
Donatien Hainaut, Adnane Akbaraly
{"title":"Risk management with local least squares Monte Carlo","authors":"Donatien Hainaut, Adnane Akbaraly","doi":"10.1017/asb.2023.25","DOIUrl":"https://doi.org/10.1017/asb.2023.25","url":null,"abstract":"Abstract The least squares Monte Carlo method has become a standard approach in the insurance and financial industries for evaluating a company’s exposure to market risk. However, the non-linear regression of simulated responses on risk factors poses a challenge in this procedure. This article presents a novel approach to address this issue by employing an a-priori segmentation of responses. Using a K-means algorithm, we identify clusters of responses that are then locally regressed on their corresponding risk factors. The global regression function is obtained by combining the local models with logistic regression. We demonstrate the effectiveness of the proposed local least squares Monte Carlo method through two case studies. The first case study investigates butterfly and bull trap options within a Heston stochastic volatility model, while the second case study examines the exposure to risks in a participating life insurance scenario.","PeriodicalId":8617,"journal":{"name":"ASTIN Bulletin","volume":"39 1","pages":"489 - 514"},"PeriodicalIF":1.9,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87303405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ASTIN BulletinPub Date : 2023-07-11DOI: 10.1017/asb.2023.24
Jingyi Cao, Dongchen Li, V. Young, B. Zou
{"title":"Reinsurance games with \u0000$boldsymbol{{n}}$\u0000 variance-premium reinsurers: from tree to chain","authors":"Jingyi Cao, Dongchen Li, V. Young, B. Zou","doi":"10.1017/asb.2023.24","DOIUrl":"https://doi.org/10.1017/asb.2023.24","url":null,"abstract":"Abstract This paper studies dynamic reinsurance contracting and competition problems under model ambiguity in a reinsurance market with one primary insurer and n reinsurers, who apply the variance premium principle and who are distinguished by their levels of ambiguity aversion. The insurer negotiates reinsurance policies with all reinsurers simultaneously, which leads to a reinsurance tree structure with full competition among the reinsurers. We model the reinsurance contracting problems between the insurer and reinsurers by Stackelberg differential games and the competition among the reinsurers by a non-cooperative Nash game. We derive equilibrium strategies in semi-closed form for all the companies, whose objective is to maximize their expected surpluses penalized by a squared-error divergence term that measures their ambiguity. We find that, in equilibrium, the insurer purchases a positive amount of proportional reinsurance from each reinsurer. We further show that the insurer always prefers the tree structure to the chain structure, in which the risk of the insurer is shared sequentially among all reinsurers.","PeriodicalId":8617,"journal":{"name":"ASTIN Bulletin","volume":"16 1","pages":"706 - 728"},"PeriodicalIF":1.9,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81940006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}