不對稱跳躍與不完全資訊對於信用風險模型之影響

Abstract

此篇論文的主旨為在資訊不完全的市場下，建立一個以雙邊指數型跳躍過程為基礎的信用風險模型、推導此模型下之破產機率，並探討不對稱跳躍與不完全資訊對於破產機率、破產強度、以及信用利差之衝擊。研究結果顯示，相較於未考慮跳躍過程之模型，在此含有跳躍過程之一般化模型的假設下，所求得之信用利差的時間結構更為豐富且多元。亦即，此篇論文建構之模型將對於真實市場有較佳之解釋能力。

The pure diffusion approach for credit risk model with noisy information is generalized in this paper by including jumps in the firm-value processes. The explicit solution of the default probability for this credit risk model is derived, and the impacts of asymmetric jumps and noisy information on the credit risk are illustrated with numerical results on the default probability, the default intensity, and the credit spread. With the term structure of credit spreads being enriched, our approach is potential to interpret empirical data in real world.