dc.contributor | 風險管理與保險學系 | |
dc.creator (作者) | 謝明華 | zh_TW |
dc.creator (作者) | Hsieh, Ming-hua | en_US |
dc.creator (作者) | Wang, Jennifer L. | en_US |
dc.creator (作者) | Chiu, Yu-Fen | en_US |
dc.creator (作者) | Chen, Yen-Chih | en_US |
dc.date (日期) | 2017 | |
dc.date.accessioned | 29-Jan-2018 12:29:18 (UTC+8) | - |
dc.date.available | 29-Jan-2018 12:29:18 (UTC+8) | - |
dc.date.issued (上傳時間) | 29-Jan-2018 12:29:18 (UTC+8) | - |
dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/115637 | - |
dc.description.abstract (摘要) | This paper proposes a new product, the Variable Life Care Annuity with Guaranteed Lifetime Withdrawal Benefits (LCA-GLWB), and designs an efficient valuation algorithm. This innovative product provides a comprehensive retirement solution for both longevity risk and long-term care protection. It includes the benefits of guaranteed income streams with downside risk protection and long-term care expenses for retirees. However, the valuation of this type of product is both complex and time-consuming. In this paper, we propose a Monte Carlo valuation algorithm that uses the variance reduction technique. The numerical results indicate that the proposed valuation algorithm is very efficient under a broad range of asset return models. The proposed algorithm provides a general approach for the rapid valuation of similar products and can help provide life insurance companies offering innovative products with an appropriate valuation tool. | en_US |
dc.format.extent | 503322 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.relation (關聯) | Insurance: Mathematics and Economics | |
dc.subject (關鍵詞) | Variable annuity; Long-term care; Life Care Annuity; Guaranteed Lifetime Withdrawal Benefit; Variance reduction | en_US |
dc.title (題名) | Valuation of variable long-term care Annuities with Guaranteed Lifetime Withdrawal Benefits: A variance reduction approach | en_US |
dc.type (資料類型) | article | |
dc.identifier.doi (DOI) | 10.1016/j.insmatheco.2017.09.017 | |
dc.doi.uri (DOI) | https://doi.org/10.1016/j.insmatheco.2017.09.017 | |