複雜衍生性商品信用價值調整 (CVA) 高效演算法研究

Abstract

信用價值調整（CVA）自2008年的金融危機以來已經成為金融業的銀行監管和會計準則的通用標準。因此，從業者和學者都非常關注CVA的相關問題。巴塞爾協議III要求銀行針對交易對手信用風險 （CCR）計提資本要求。 CCR包括交易對手違約和CVA價值的變化。 CVA衡量CCR的評價部分，即 CVA根據交易對手信用狀態調整相互間的衍生性商品契約的價值。 CVA的計算是一個複雜的任務，因為它涉及複雜的衍生工具的違約選擇權的評價。對複雜衍生性商品契約而言，情況更加困難。因為它們的定價, 蒙特卡羅模擬是唯一可行的計算工具。因此，設計高效的演算法, 對於這些複雜的衍生性商品契約的CVA計算就變得非常重要。針對此一議題，本計畫將一個重要的複雜的衍生性商品契約：一籃子信用違約交換合約，這是流行的對沖信貸組合 Credit Valuation Adjustments (CVA) has become a common standard in bank regulation and accounting rules since the 2008 crisis in the financial industry. Therefore, practitioners and academics draw a lot of attentions to CVA related problems. Basel III requires banks to set a part of their capital requirement for counterparty credit risk (CCR). CCR includes counterparty default and CVA changes. CVA measures the valuation component of this risk, i.e. the adjustment to the price of a product due to this risk. The computation of CVA is a complex task, because it involves valuation of the default option on complex derivatives. The situation is even worse for complex derivatives, because Monte Carlo simulation is the only viable computation tool for their pricing. Therefore, designing effective algorithms for the CVA computation of these complex derivatives becomes very important. We develop fast valuation algorithm for basket credit default swaps, which are popular for hedging credit portfolio.