{"title":"与行为金融学相关的负债驱动投资","authors":"L. Brummer, Markus Wahl, R. Zagst","doi":"10.1142/9789813272569_0011","DOIUrl":null,"url":null,"abstract":"Liability driven investment (LDI) strategies that take stochastic liabilities into account have become increasingly important for insurance companies and pension funds due to market developments such as low interest rates, high volatility and changes in regulatory requirements. We consider stochastic liabilities in a portfolio optimization framework and include aspects from behavioral finance, in particular cumulative prospect theory (CPT). We study LDI strategies with extended preference structures and probability distortion and derive analytical solutions for a CPT portfolio optimization problem in an LDI context. Within a case study, we compare the optimal investment strategies to existing LDI approaches within traditional frameworks such as the partial surplus optimization presented in [1] and the funding ratio optimization in an expected utility framework as introduced in [2].","PeriodicalId":128926,"journal":{"name":"Innovations in Insurance, Risk- and Asset Management","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Liability Driven Investments with a Link to Behavioral Finance\",\"authors\":\"L. Brummer, Markus Wahl, R. Zagst\",\"doi\":\"10.1142/9789813272569_0011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Liability driven investment (LDI) strategies that take stochastic liabilities into account have become increasingly important for insurance companies and pension funds due to market developments such as low interest rates, high volatility and changes in regulatory requirements. We consider stochastic liabilities in a portfolio optimization framework and include aspects from behavioral finance, in particular cumulative prospect theory (CPT). We study LDI strategies with extended preference structures and probability distortion and derive analytical solutions for a CPT portfolio optimization problem in an LDI context. Within a case study, we compare the optimal investment strategies to existing LDI approaches within traditional frameworks such as the partial surplus optimization presented in [1] and the funding ratio optimization in an expected utility framework as introduced in [2].\",\"PeriodicalId\":128926,\"journal\":{\"name\":\"Innovations in Insurance, Risk- and Asset Management\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Innovations in Insurance, Risk- and Asset Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/9789813272569_0011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Innovations in Insurance, Risk- and Asset Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/9789813272569_0011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Liability Driven Investments with a Link to Behavioral Finance
Liability driven investment (LDI) strategies that take stochastic liabilities into account have become increasingly important for insurance companies and pension funds due to market developments such as low interest rates, high volatility and changes in regulatory requirements. We consider stochastic liabilities in a portfolio optimization framework and include aspects from behavioral finance, in particular cumulative prospect theory (CPT). We study LDI strategies with extended preference structures and probability distortion and derive analytical solutions for a CPT portfolio optimization problem in an LDI context. Within a case study, we compare the optimal investment strategies to existing LDI approaches within traditional frameworks such as the partial surplus optimization presented in [1] and the funding ratio optimization in an expected utility framework as introduced in [2].