随机波动模型中的违约风险

H. Gersbach, N. Surulescu
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引用次数: 2

摘要

我们考虑一个均值回归型的随机波动模型来描述企业价值的演变,而不是经典的默顿方法与几何布朗运动。我们提出了违约概率的解析表达式。我们的模拟结果表明,如果企业的信用质量不是太低,随机波动率模型往往比相应的默顿模型预测更高的违约概率。否则,随机波动率模型预测的违约概率较低。研究结果可能会对各种金融应用产生影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Default Risk in Stochastic Volatility Models
We consider a stochastic volatility model of the mean-reverting type to describe the evolution of a firm’s values instead of the classical approach by Merton with geometric Brownian motions. We develop an analytical expression for the default probability. Our simulation results indicate that the stochastic volatility model tends to predict higher default probabilities than the corresponding Merton model if a firm’s credit quality is not too low. Otherwise the stochastic volatility model predicts lower probabilities of default. The results may have implications for various financial applications.
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