Classic stochastic volatility models assume volatility is unobservable. We use the VIX for consider it observable, and use the Volatility Index: S\&P 500 VIX. This index was designed to measure volatility of S\&P 500. We apply it to a different segment: Corporate bond markets. We fit time series models for spreads between corporate and 10-year Treasury bonds. Next, we divide residuals by VIX. Our main idea is such division makes residuals closer to the ideal case of a Gaussian white noise. This is remarkable, since these residuals and VIX come from separate market segments. We conclude with the analysis of long-term behavior of these models.

翻译：经典随机波动率模型假设波动率不可观测。我们使用VIX将其视为可观测变量，具体采用标准普尔500波动率指数（S&P 500 VIX）。该指数原为衡量标普500指数波动率而设计，我们将其应用于不同领域：公司债券市场。我们建立了公司债券与10年期国债利差的时间序列模型，随后将模型残差除以VIX值。核心思想在于：该除法运算能使残差更接近理想的高斯白噪声特性。这一发现尤为显著，因为残差与VIX源自相互独立的市场板块。最后，我们分析了这些模型的长期行为特征。