Publications-NSC Projects

Article View/Open

Publication Export

Google ScholarTM

NCCU Library

Citation Infomation

Related Publications in TAIR

題名 保險公司因應長壽風險衝擊所應採取之風險管理
其他題名 Risk Management of Longevity Risk for Insurance Companies
作者 黃泓智
貢獻者 國立政治大學風險管理與保險學系
行政院國家科學委員會
關鍵詞 保險公司;長壽風險風險管理
日期 2011
上傳時間 22-Oct-2012 15:45:02 (UTC+8)
摘要 本計畫在未來四年的計畫中將主要針對長壽風險對保險公司的影響進行探 討,並進一步提出有效的風險管理策略,任何成功風險管理策略的前題就是要能 精準預測風險,因此建構正確的風險預測模型是風險管理最重要的步驟,本計劃 前兩年將針對保險公司的兩個主要風險"死亡率" 和"投資報酬" ,建構其正 確的風險預測模型。本研究將於第一年建構新的死亡率模型,採用Levy 模型把 跳躍特性納入死亡改善率模型建構之考量,於計劃中第二年進行投資模型建構, 改善過去資產模型架構中經濟過程的變化量以高斯函數模擬產生結果的缺點,採 用近幾年較新觀點之MAGH 分配來建立多資產投資報酬率模型架構,達到捕捉財 務金融資產常具備的厚尾(heavy-tailness)、偏態(skewness)、峰態(kurtosis) 特性之目的,有了前兩年風險因子預測模型的基礎研究之後,在計畫的後兩年將 探討因應長壽風險衝擊之下保險公司所應採取之實質的風險管理策略。計劃的第 三年首先探討保險公司的自然避險策略(natural hedging),透過公司內部保單 組合來規避未來死亡改善率脫離預期死亡率所造成的損失,並將自然避險策略推 廣至整體保單組合的配置策略。此計畫之第四年將探討各種給付型態的商品在未 來各個保單年度的現金流量分佈情形,然後根據現金流量分配探討保險公司在因 應死亡率逐年改善的情況下之風險管理策略,並建構正確的死差分紅公式,進而 探討保險公司的風險管理策略。
This research aims to investigate the impact of longevity risk for insurance companies and further provide an efficient risk management strategy to hedge longevity risk. An accurate risk predicting model is a key factor of any successful risk management. The purpose of this research in the first two years is to create a mortality improvement model and a multi‐asset model. In the first year, we will adopt the concept of Levy process into the mortality model in order to catch the characteristics of jump in the mortality data. In the second year, we will apply MAGH process to create a multi‐asset investment model in order to catch the characteristics of heavy‐tailness, skewness and kurtosis in the financial data. With the basic researches of forecasting model in the first two years, we will investigate the risk management strategy to hedge longevity risk in the rest two years of this research. In the third year, we will use natural hedging strategy to reduce the loss due to longevity risk. In the last year, we will fit the mortality model by experienced mortality data and check how serious of mispricing for various insurance products. By the method of cash‐flow testing, we will investigate the risk management strategy to reduce the risk of mispricing due to mortality improvement. This research will finally discuss the feasibility of current mortality‐bonus formula and provide a suitable mortality‐bonus formula to solve the problem of unfairness in the insurance market and further discuss its risk management strategy.
關聯 基礎研究
學術補助
研究期間:10008~ 10107
研究經費:920仟元
資料類型 report
dc.contributor 國立政治大學風險管理與保險學系en_US
dc.contributor 行政院國家科學委員會en_US
dc.creator (作者) 黃泓智zh_TW
dc.date (日期) 2011en_US
dc.date.accessioned 22-Oct-2012 15:45:02 (UTC+8)-
dc.date.available 22-Oct-2012 15:45:02 (UTC+8)-
dc.date.issued (上傳時間) 22-Oct-2012 15:45:02 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/53909-
dc.description.abstract (摘要) 本計畫在未來四年的計畫中將主要針對長壽風險對保險公司的影響進行探 討,並進一步提出有效的風險管理策略,任何成功風險管理策略的前題就是要能 精準預測風險,因此建構正確的風險預測模型是風險管理最重要的步驟,本計劃 前兩年將針對保險公司的兩個主要風險"死亡率" 和"投資報酬" ,建構其正 確的風險預測模型。本研究將於第一年建構新的死亡率模型,採用Levy 模型把 跳躍特性納入死亡改善率模型建構之考量,於計劃中第二年進行投資模型建構, 改善過去資產模型架構中經濟過程的變化量以高斯函數模擬產生結果的缺點,採 用近幾年較新觀點之MAGH 分配來建立多資產投資報酬率模型架構,達到捕捉財 務金融資產常具備的厚尾(heavy-tailness)、偏態(skewness)、峰態(kurtosis) 特性之目的,有了前兩年風險因子預測模型的基礎研究之後,在計畫的後兩年將 探討因應長壽風險衝擊之下保險公司所應採取之實質的風險管理策略。計劃的第 三年首先探討保險公司的自然避險策略(natural hedging),透過公司內部保單 組合來規避未來死亡改善率脫離預期死亡率所造成的損失,並將自然避險策略推 廣至整體保單組合的配置策略。此計畫之第四年將探討各種給付型態的商品在未 來各個保單年度的現金流量分佈情形,然後根據現金流量分配探討保險公司在因 應死亡率逐年改善的情況下之風險管理策略,並建構正確的死差分紅公式,進而 探討保險公司的風險管理策略。en_US
dc.description.abstract (摘要) This research aims to investigate the impact of longevity risk for insurance companies and further provide an efficient risk management strategy to hedge longevity risk. An accurate risk predicting model is a key factor of any successful risk management. The purpose of this research in the first two years is to create a mortality improvement model and a multi‐asset model. In the first year, we will adopt the concept of Levy process into the mortality model in order to catch the characteristics of jump in the mortality data. In the second year, we will apply MAGH process to create a multi‐asset investment model in order to catch the characteristics of heavy‐tailness, skewness and kurtosis in the financial data. With the basic researches of forecasting model in the first two years, we will investigate the risk management strategy to hedge longevity risk in the rest two years of this research. In the third year, we will use natural hedging strategy to reduce the loss due to longevity risk. In the last year, we will fit the mortality model by experienced mortality data and check how serious of mispricing for various insurance products. By the method of cash‐flow testing, we will investigate the risk management strategy to reduce the risk of mispricing due to mortality improvement. This research will finally discuss the feasibility of current mortality‐bonus formula and provide a suitable mortality‐bonus formula to solve the problem of unfairness in the insurance market and further discuss its risk management strategy.en_US
dc.language.iso en_US-
dc.relation (關聯) 基礎研究en_US
dc.relation (關聯) 學術補助en_US
dc.relation (關聯) 研究期間:10008~ 10107en_US
dc.relation (關聯) 研究經費:920仟元en_US
dc.subject (關鍵詞) 保險公司;長壽風險風險管理en_US
dc.title (題名) 保險公司因應長壽風險衝擊所應採取之風險管理zh_TW
dc.title.alternative (其他題名) Risk Management of Longevity Risk for Insurance Companiesen_US
dc.type (資料類型) reporten