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題名 精算與財務方法在壽險保單定價、準備金估計、以及風險管理之運用 其他題名 The Uses of Actuarial and Financial Approaches in Pricing, Reserving, and Risk Managment of Life Insurance 作者 蔡政憲 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 精算;財務方法;壽險保單定價;準備金;風險管理
Surrender;Reverves;Stochastic Simulation;Dynamic Hedging日期 2012 上傳時間 22-Oct-2012 15:45:42 (UTC+8) 摘要 許多壽險商品都有選擇權式的條款，例如最低獲利保證、分紅、以及可提前解約。如果沒能正確地估計這些條款的價值，保險公司的清償能力將受到影響。目前有兩類方法來處理這個議題。 英美系國家的精算學會採用的是隨機模擬法（或稱精算法）。這類方法是在實際測度下運用隨機模型模擬出內含保證或選擇權的收益機率分佈，保險公司再根據這個機率分佈來計算相關的的成本並提列準備金。保證或選擇權也可以用財務理論中選擇權定價方法來評估。此方法是在一些假設（例如完全與無套利）以及風險中立的測度下進行的。在文獻中被稱為選擇權定價法或財務法，佔有顯著的地位。 本計畫將在三方面延伸比較或整合上述兩種方法的文獻。第一年的計畫將延伸Boyle and Hardy (1997)。他們在比較精算與財務方法的時候採用了不一致的模型，我們將改採同等的模型來進行比較。第二、我們將額外分析多期的保證，因為這類保證存在於許多國家的主流商品中。第三、我們的比較將考量解約選擇權。 第二年的計畫將延伸Barbarin and Devolder (2005) and Gatzert and Kling (2007)。我們將提出一個新模式來整合精算與財務方法，這個模式和 Barbarin and Devolder (2005) 剛好相反。我們建議保險公司先進行風險中立評價以計算保費，然後再用隨機模擬來估計經濟資本。我們將以Bacinello (2001) and Lee (2003)中所分析的保單來闡釋我們的模式，然後再進一步說明這個模式可以如何幫助壽險公司找到最適的保證獲利率以及分紅率。 第三年的計畫將延伸Kling et al. (2007), Gatzert and Kling (2007), Gatzert (2008), and Graf, Kling, and Russ (2009)。第一方面的延伸是分析幾種常見的投資策略（例如CPPI與TIPP）會如何影響保單的評價與保險公司的清償能力。第二則是在一個完整的架構下、運用演算法來求解最適的投資策略、分紅機制、契約參數、以及資本結構。
Many popular life insurance products come with option-like covenants: minimum return guarantees, participating clauses, and/or surrender options. Improper pricing, reserving, and/or hedging of the provided guarantees and options would impair the solvency of an insurer. There are two very different paradigms to handle the issues. Actuarial associations in UK, US, and Canada adopted stochastic methods in the analysis of embedded guarantees and options. The literature labeled this method the stochastic simulation method or the actuarial approach. The idea is to simulate the payoff distribution of an embedded guarantee/option using stochastic models in the real-world probability measure. Insurers then estimate the expected cost of the guarantee/option and the associated reserves based on the simulated distribution. Embedded guarantees and options can also be valuated using the machinery of option pricing. In this context, computations take place under a risk-neutral probability measure with certain assumptions on the market (e.g., completeness and no arbitrage). This approach was labeled the option pricing approach or the financial approach. It occupied a significant position in the literature. This proposal will extend the literature in three aspects of comparing and integrating these two approaches. The first-year project will extend Boyle and Hardy (1997). Firstly, we will compare the merits of the actuarial and financial approaches in a valid/correct way. The models Boyle and Hardy (1997) used for the two approaches are different, which weaken the validity of their comparisons. We propose to use “equivalent” models in both approaches. Secondly, we will analyze the cliquet-style type of periodic guarantee in addition to the point-to-point type of maturity guarantee. The cliquet-style guarantees are the predominant kinds of guarantees in German, Japan, Taiwan, and several other Asian markets. Our third extension is to incorporate surrender options that are embedded in almost all life insurance products into the comparisons. In the second-year project, we plan to extend Barbarin and Devolder (2005) and Gatzert and Kling (2007) by proposing another way to integrate the stochastic simulation method and the option pricing approach. Our proposal basically turns the procedure proposed by Barbarin and Devolder (2005) the other way around. We suggest insurers performing risk-neutral valuation first for policy premiums and then conducting stochastic simulation to calculate the associated economic capital. We plan to illustrate this integration using the product analyses done in Bacinello (2001) and Lee (2003). We will further illustrate how this integration can help insurers to find optimal contract parameters. In the third year, we are going to extend Kling et al. (2007), Gatzert and Kling (2007), Gatzert (2008), and Graf, Kling, and Russ (2009). Our first extension will be explicitly analyzing how investment strategies affect the valuation of insurance policies and the solvency of insurance companies with four popular strategies: buy and hold, constant mix, constant proportion portfolio insurance (CPPI), and time-invariant portfolio protection (TIPP). Our second extension will be employing a heuristic search algorithm to solve for the optimal combination of investment strategies, surplus distribution schemes, contract parameters, and capital structure in a more comprehensive framework.關聯 應用研究
學術補助
研究期間:10108~ 10207
研究經費:691仟元資料類型 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) 蔡政憲 zh_TW dc.date (日期) 2012 en_US dc.date.accessioned 22-Oct-2012 15:45:42 (UTC+8) - dc.date.available 22-Oct-2012 15:45:42 (UTC+8) - dc.date.issued (上傳時間) 22-Oct-2012 15:45:42 (UTC+8) - dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/53934 - dc.description.abstract (摘要) 許多壽險商品都有選擇權式的條款，例如最低獲利保證、分紅、以及可提前解約。如果沒能正確地估計這些條款的價值，保險公司的清償能力將受到影響。目前有兩類方法來處理這個議題。 英美系國家的精算學會採用的是隨機模擬法（或稱精算法）。這類方法是在實際測度下運用隨機模型模擬出內含保證或選擇權的收益機率分佈，保險公司再根據這個機率分佈來計算相關的的成本並提列準備金。保證或選擇權也可以用財務理論中選擇權定價方法來評估。此方法是在一些假設（例如完全與無套利）以及風險中立的測度下進行的。在文獻中被稱為選擇權定價法或財務法，佔有顯著的地位。 本計畫將在三方面延伸比較或整合上述兩種方法的文獻。第一年的計畫將延伸Boyle and Hardy (1997)。他們在比較精算與財務方法的時候採用了不一致的模型，我們將改採同等的模型來進行比較。第二、我們將額外分析多期的保證，因為這類保證存在於許多國家的主流商品中。第三、我們的比較將考量解約選擇權。 第二年的計畫將延伸Barbarin and Devolder (2005) and Gatzert and Kling (2007)。我們將提出一個新模式來整合精算與財務方法，這個模式和 Barbarin and Devolder (2005) 剛好相反。我們建議保險公司先進行風險中立評價以計算保費，然後再用隨機模擬來估計經濟資本。我們將以Bacinello (2001) and Lee (2003)中所分析的保單來闡釋我們的模式，然後再進一步說明這個模式可以如何幫助壽險公司找到最適的保證獲利率以及分紅率。 第三年的計畫將延伸Kling et al. (2007), Gatzert and Kling (2007), Gatzert (2008), and Graf, Kling, and Russ (2009)。第一方面的延伸是分析幾種常見的投資策略（例如CPPI與TIPP）會如何影響保單的評價與保險公司的清償能力。第二則是在一個完整的架構下、運用演算法來求解最適的投資策略、分紅機制、契約參數、以及資本結構。 en_US dc.description.abstract (摘要) Many popular life insurance products come with option-like covenants: minimum return guarantees, participating clauses, and/or surrender options. Improper pricing, reserving, and/or hedging of the provided guarantees and options would impair the solvency of an insurer. There are two very different paradigms to handle the issues. Actuarial associations in UK, US, and Canada adopted stochastic methods in the analysis of embedded guarantees and options. The literature labeled this method the stochastic simulation method or the actuarial approach. The idea is to simulate the payoff distribution of an embedded guarantee/option using stochastic models in the real-world probability measure. Insurers then estimate the expected cost of the guarantee/option and the associated reserves based on the simulated distribution. Embedded guarantees and options can also be valuated using the machinery of option pricing. In this context, computations take place under a risk-neutral probability measure with certain assumptions on the market (e.g., completeness and no arbitrage). This approach was labeled the option pricing approach or the financial approach. It occupied a significant position in the literature. This proposal will extend the literature in three aspects of comparing and integrating these two approaches. The first-year project will extend Boyle and Hardy (1997). Firstly, we will compare the merits of the actuarial and financial approaches in a valid/correct way. The models Boyle and Hardy (1997) used for the two approaches are different, which weaken the validity of their comparisons. We propose to use “equivalent” models in both approaches. Secondly, we will analyze the cliquet-style type of periodic guarantee in addition to the point-to-point type of maturity guarantee. The cliquet-style guarantees are the predominant kinds of guarantees in German, Japan, Taiwan, and several other Asian markets. Our third extension is to incorporate surrender options that are embedded in almost all life insurance products into the comparisons. In the second-year project, we plan to extend Barbarin and Devolder (2005) and Gatzert and Kling (2007) by proposing another way to integrate the stochastic simulation method and the option pricing approach. Our proposal basically turns the procedure proposed by Barbarin and Devolder (2005) the other way around. We suggest insurers performing risk-neutral valuation first for policy premiums and then conducting stochastic simulation to calculate the associated economic capital. We plan to illustrate this integration using the product analyses done in Bacinello (2001) and Lee (2003). We will further illustrate how this integration can help insurers to find optimal contract parameters. In the third year, we are going to extend Kling et al. (2007), Gatzert and Kling (2007), Gatzert (2008), and Graf, Kling, and Russ (2009). Our first extension will be explicitly analyzing how investment strategies affect the valuation of insurance policies and the solvency of insurance companies with four popular strategies: buy and hold, constant mix, constant proportion portfolio insurance (CPPI), and time-invariant portfolio protection (TIPP). Our second extension will be employing a heuristic search algorithm to solve for the optimal combination of investment strategies, surplus distribution schemes, contract parameters, and capital structure in a more comprehensive framework. en_US dc.language.iso en_US - dc.relation (關聯) 應用研究 en_US dc.relation (關聯) 學術補助 en_US dc.relation (關聯) 研究期間:10108~ 10207 en_US dc.relation (關聯) 研究經費:691仟元 en_US dc.subject (關鍵詞) 精算;財務方法;壽險保單定價;準備金;風險管理 en_US dc.subject (關鍵詞) Surrender;Reverves;Stochastic Simulation;Dynamic Hedging - dc.title (題名) 精算與財務方法在壽險保單定價、準備金估計、以及風險管理之運用 zh_TW dc.title.alternative (其他題名) The Uses of Actuarial and Financial Approaches in Pricing, Reserving, and Risk Managment of Life Insurance en_US dc.type (資料類型) report en
