Modeling credit spreads under multifactor stochastic volatility

Jacinto Marabel Romo
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引用次数: 4

Abstract

The empirical tests of traditional structural models of credit risk tend to indicate that such models have been unsuccessful in the modeling of credit spreads. To address these negative findings some authors introduce single-factor stochastic volatility specifications and/or jumps.

In the yield curve literature it is widely accepted that one-factor is not sufficient to capture the time variation and cross-sectional variation in the term structure. This article introduces a two-factor stochastic volatility specification within the structural model of credit risk. One of the factors determines the correlation between short-term firms’ assets returns and variance, whereas the other factor determines the correlation between long-term returns and variance. The numerical tests reveal how the introduction of two volatility factors can generate a wide range of combinations associated with short-term and long-term patters corresponding to credit spreads. In this sense, multi-factor stochastic volatility specifications provide more flexibility than single-factor models to capture a wide range of shapes associated with the term structure of credit spreads consistent with the empirical evidence.

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多因素随机波动下的信用利差建模
传统的信用风险结构模型的实证检验往往表明,这些模型在信用利差建模方面是不成功的。为了解决这些负面的发现,一些作者引入了单因素随机波动率规范和/或跳跃。在收益率曲线文献中,人们普遍认为单因素不足以反映期限结构的时间变化和横截面变化。本文在信用风险结构模型中引入了一种双因素随机波动率规范。其中一个因素决定了短期公司资产收益与方差之间的相关性,而另一个因素决定了长期收益与方差之间的相关性。数值测试揭示了引入两个波动因子如何产生与信用利差对应的短期和长期模式相关的大范围组合。从这个意义上说,多因素随机波动率规范比单因素模型提供了更大的灵活性,以捕捉与经验证据一致的信用利差期限结构相关的各种形状。
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