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題名 Modeling Multicountry Longevity Risk with Mortality Dependence: A Levy Subordinated Hierarchical Archimedean Copulas Approach
作者 王昭文
Zhu, Wenjun
Tan, Ken Seng
Wang, Chou-Wen
貢獻者 風管系
關鍵詞 Forecast; Modeling; Mortality
日期 2017-04
上傳時間 30-Aug-2017 15:28:01 (UTC+8)
摘要 This article proposes a new copula model known as the Levy subordinated hierarchical Archimedean copulas (LSHAC) for multicountry mortality dependence modeling. To the best of our knowledge, this is the first article to apply the LSHAC model to mortality studies. Through an extensive empirical analysis on modeling mortality experiences of 13 countries, we demonstrate that the LSHAC model, which has the advantage of capturing the geographical structure of mortality data, yields better fit, compared to the elliptical copulas. In addition, the proposed LSHAC model generates out-of-sample forecasts with smaller standard deviations, when compared to other benchmark copula models. The LSHAC model also confirms that there is an association between geographical locations and dependence of the overall mortality improvement. These results yield new insights into future longevity risk management. Finally, the model is used to price a hypothetical survival index swap written on a weighted mortality index. The results highlight the importance of dependence modeling in managing longevity risk and reducing population basis risk.
關聯 Journal of Risk and Insurance, Special Edition, Vol. 84, 477-493
資料類型 article
DOI http://dx.doi.org/10.1111/jori.12198
dc.contributor 風管系zh_TW
dc.creator (作者) 王昭文zh_TW
dc.creator (作者) Zhu, Wenjunen_US
dc.creator (作者) Tan, Ken Sengen_US
dc.creator (作者) Wang, Chou-Wenen_US
dc.date (日期) 2017-04
dc.date.accessioned 30-Aug-2017 15:28:01 (UTC+8)-
dc.date.available 30-Aug-2017 15:28:01 (UTC+8)-
dc.date.issued (上傳時間) 30-Aug-2017 15:28:01 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/112301-
dc.description.abstract (摘要) This article proposes a new copula model known as the Levy subordinated hierarchical Archimedean copulas (LSHAC) for multicountry mortality dependence modeling. To the best of our knowledge, this is the first article to apply the LSHAC model to mortality studies. Through an extensive empirical analysis on modeling mortality experiences of 13 countries, we demonstrate that the LSHAC model, which has the advantage of capturing the geographical structure of mortality data, yields better fit, compared to the elliptical copulas. In addition, the proposed LSHAC model generates out-of-sample forecasts with smaller standard deviations, when compared to other benchmark copula models. The LSHAC model also confirms that there is an association between geographical locations and dependence of the overall mortality improvement. These results yield new insights into future longevity risk management. Finally, the model is used to price a hypothetical survival index swap written on a weighted mortality index. The results highlight the importance of dependence modeling in managing longevity risk and reducing population basis risk.en_US
dc.format.extent 507090 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Journal of Risk and Insurance, Special Edition, Vol. 84, 477-493en_US
dc.subject (關鍵詞) Forecast; Modeling; Mortalityen_US
dc.title (題名) Modeling Multicountry Longevity Risk with Mortality Dependence: A Levy Subordinated Hierarchical Archimedean Copulas Approachen_US
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1111/jori.12198
dc.doi.uri (DOI) http://dx.doi.org/10.1111/jori.12198