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Corporate credit risk prediction under stochastic volatility and jumps

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  • Bu, Di
  • Liao, Yin

Abstract

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.

Suggested Citation

  • Bu, Di & Liao, Yin, 2014. "Corporate credit risk prediction under stochastic volatility and jumps," Journal of Economic Dynamics and Control, Elsevier, vol. 47(C), pages 263-281.
  • Handle: RePEc:eee:dyncon:v:47:y:2014:i:c:p:263-281
    DOI: 10.1016/j.jedc.2014.08.006
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Pascal Damel & Hoai An Le Thi & Nadège Peltre, 2016. "The challenge in managing new financial risks: adopting an heuristic or theoretical approach," Annals of Operations Research, Springer, vol. 247(2), pages 581-598, December.
    2. Xiao, Weilin & Zhang, Xili, 2016. "Pricing equity warrants with a promised lowest price in Merton’s jump–diffusion model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 219-238.
    3. Haixiang Yao & Xun Li & Zhifeng Hao & Yong Li, 2016. "Dynamic asset–liability management in a Markov market with stochastic cash flows," Quantitative Finance, Taylor & Francis Journals, vol. 16(10), pages 1575-1597, October.

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    More about this item

    Keywords

    Credit risk; CDS spread; Merton model; Stochastic volatility; Jumps;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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