Corporate credit risk prediction under stochastic volatility and jumps

Di Bu, Yin Liao*

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

7 Citations (Scopus)
44 Downloads (Pure)


This paper examines the impact of allowing for stochastic volatility and jumps (SVJ) in a structural model on corporate credit risk prediction. The results from a simulation study verify the better performance of the SVJ model compared with the commonly used Merton model, and three sources are provided to explain the superiority. The empirical analysis on two real samples further ascertains the importance of recognizing the stochastic volatility and jumps by showing that the SVJ model decreases bias in spread prediction from the Merton model, and better explains the time variation in actual CDS spreads. The improvements are found particularly apparent in small firms or when the market is turbulent such as the recent financial crisis. (C) 2014 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)263-281
Number of pages19
JournalJournal of Economic Dynamics and Control
Publication statusPublished - Oct 2014
Externally publishedYes


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