此研究主要研究壽險業的系統性風險與違約風險之評價，基於投資組合的波動度去建立隨機過程模型。特別是那些隱含無法被多角化的財務風險、系統性風險，透過研究，使用Heston(1993)模型去描述標的資產的隨機波動程度比以往使用Black-Scholes(1973)模型描述股價的波動變化更能反映實際的風險狀況，並透過CIR過程來表示瞬間的波動程度。在這個模型之中，把過去以平賭測度決定違約選擇權的方法延伸。此外透過探討違約價值之敏感度，根據不同的情境測試對於壽險公司負債的影響。最後透過數值的結果與敏感度分析隨機波動模型與確定性的模型之差異。 當資本準備增加時，資產與負債比提高，因負債仍固定承諾予保戶之利率增長，而資產因應系統性風險的發生而減損仍能支付負債，致使違約風險降低，進而使得評價時點的違約金額降低。當系統風險發生時，風險值上升，違約價值為右偏分布，代表在極端條件下有可能有極大的損失；反之，當整個金融體系經濟情勢良好，公司擁有足夠的經濟資本時，風險值下降，滿足VaR75與CTE65的法規限制，此時公司的清償能力足以反映系統性風險。 / This paper considers the problem of valuating the default option of the life insurers that are subject to systematic financial risk in the sense that the volatility of the investment portfolio is modeled through stochastic processes. In particular, this implies that the financial risk cannot be eliminated through diversifying the asset portfolio. In our work, Heston (1993) model is employed in describing the evolution of the volatility of an underlying asset, while the instantaneous variance is a CIR process. Within this model, we study a general set of equivalent martingale measures, and determine the default option by applying these measures. In addition, we investigate the sensitivity of the default values given regulatory forbearance for the life insurance liabilities considered. Numerical examples are included, and the use of the stochastic volatility model is compared with deterministic models. As reserve of capital is increasing, asset-liability ratio is also increasing. The liability grew up with promised interest rate, and it could be covered by the asset when the systematic risk events happened. Therefore, the default risk was decreasing, that caused the default value decreasing. When the systematic risk events happened, the value of risk was increasing, and the default value was positive skew distribution. That means the maximum loss will be coming in the extreme case. On the other hand, when prosperity economy occurred, the value of risk was decreasing, which in compliance with the law of VaR75&CTE65 rules, and the insurance company had enough capital to face the systematic risk events.

以往投資人認為透過『附加保護層』的保護機制，損失不易流通至主擔保債權憑證，潛在損失較低；又因包含龐大之標的債權，投資人也認為該投資風險分散程度較高，風險暴露程度較低。然而，2007年7月發生次級房貸風暴，導致複合型保護層信用擔保債權憑證各分券投資人產生鉅額損失，方了解於保護層的面紗之下，隱含了不為人知的風險。 　　因此，本研究目的發展合成型複合型保護層信用擔保債權憑證之評價模型，以雙層信用擔保債權為例，『由下而上』依序建構標的債權群組，至主擔保債權憑證之總損失機率分配；並透過直觀的考慮所有損失的可能組合，使估計之合理信用價差更為精確，不僅解決以往評價雙層擔保債權憑證的維度限制，計算子分券數目為二以上的情形，更能將此模型推廣至所有複合型保護層信用擔保債權憑證之評價，適合實務應用。 　　除此之外，本研究亦希望透過實務界常用之風險衡量指標，揭開保護層之厚重面紗，探討複合型保護層信用擔保債權憑證所隱含之風險，提供投資人參考。透過與一般信用擔保債權憑證之風險特性，探討『附加保護層』機制是否真能提升風險分散程度，抑或反而有損失累積的效果。最後，本研究也藉由風險衡量指標，分析資產重疊程度由低至高時，對對雙層信用擔保債權憑證風險的影響，了解風險是否會隨其資產重疊度增加而增加。