{"title":"生命关怀年金:增强产品功能,完善定价方法","authors":"G. Apicella, A. Molent, M. Gaudenzi","doi":"arxiv-2404.02858","DOIUrl":null,"url":null,"abstract":"In this paper we provide more general features for the variable annuity\ncontract with LTC payouts and GLWB proposed by the state-of-the-art and we\nrefine its pricing methods. In particular, as to product features, we allow\ndynamic withdrawal strategies, including the surrender option. Furthermore, we\nconsider stochastic interest rate, described by a Cox-Ingersoll-Ross (CIR)\nprocess. As to the numerical methods, we solve the stochastic control problem\ninvolved by the selection of the optimal withdrawal strategy by means of a\nrobust tree method. We use such a method to estimate the fair price of the\nproduct. Furthermore, our numerical results show how the optimal withdrawal\nstrategy varies over time with the health status of the policyholder. Our\nproposed tree method, we name Tree-LTC, proves to be efficient and reliable,\nwhen tested against the Monte Carlo approach.","PeriodicalId":501294,"journal":{"name":"arXiv - QuantFin - Computational Finance","volume":"26 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Life Care Annuity: enhancing product features and refining pricing methods\",\"authors\":\"G. Apicella, A. Molent, M. Gaudenzi\",\"doi\":\"arxiv-2404.02858\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we provide more general features for the variable annuity\\ncontract with LTC payouts and GLWB proposed by the state-of-the-art and we\\nrefine its pricing methods. In particular, as to product features, we allow\\ndynamic withdrawal strategies, including the surrender option. Furthermore, we\\nconsider stochastic interest rate, described by a Cox-Ingersoll-Ross (CIR)\\nprocess. As to the numerical methods, we solve the stochastic control problem\\ninvolved by the selection of the optimal withdrawal strategy by means of a\\nrobust tree method. We use such a method to estimate the fair price of the\\nproduct. Furthermore, our numerical results show how the optimal withdrawal\\nstrategy varies over time with the health status of the policyholder. Our\\nproposed tree method, we name Tree-LTC, proves to be efficient and reliable,\\nwhen tested against the Monte Carlo approach.\",\"PeriodicalId\":501294,\"journal\":{\"name\":\"arXiv - QuantFin - Computational Finance\",\"volume\":\"26 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuantFin - Computational Finance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2404.02858\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Computational Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2404.02858","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Life Care Annuity: enhancing product features and refining pricing methods
In this paper we provide more general features for the variable annuity
contract with LTC payouts and GLWB proposed by the state-of-the-art and we
refine its pricing methods. In particular, as to product features, we allow
dynamic withdrawal strategies, including the surrender option. Furthermore, we
consider stochastic interest rate, described by a Cox-Ingersoll-Ross (CIR)
process. As to the numerical methods, we solve the stochastic control problem
involved by the selection of the optimal withdrawal strategy by means of a
robust tree method. We use such a method to estimate the fair price of the
product. Furthermore, our numerical results show how the optimal withdrawal
strategy varies over time with the health status of the policyholder. Our
proposed tree method, we name Tree-LTC, proves to be efficient and reliable,
when tested against the Monte Carlo approach.