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On the applicability of stochastic volatility models

机译:随机波动率模型的适用性

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The applicability of the stochastic volatility (SV) model and the SV model with jumps for US. Treasury Bill yields data is investigated. The transformation of the continuous time models into regression models is considered and their error terms are examined. The applicability of the continuous time models to the real data is assessed by comparing some atypical properties of such error terms with an application to the real data and the generated data from the models. The empirical results indicate that the SV model and the SV model with jumps are not applicable to modeling the daily/weekly released US T-Bill secondary market yields data. Some trends and correlation structure are detected to exist in the error terms of the transformed regression models for the daily/weekly released US T-Bill yields data, while the error terms of the continuous time models are supposed to be uncorrelated. These results suggest that alternative models are needed to model such T-Bill yields data.
机译:随机波动率(SV)模型和带跳跃的SV模型在美国的适用性。研究国库券收益率数据。考虑将连续时间模型转换为回归模型,并检查其误差项。通过将此类误差项的某些非典型性质与应用程序应用于实际数据和从模型生成的数据进行比较,可以评估连续时间模型对实际数据的适用性。实证结果表明,SV模型和带跳跃的SV模型不适用于建模每日/每周发布的美国国库券二级市场收益数据。对于每日/每周发布的美国国库券收益率数据,在转换回归模型的误差项中检测到某些趋势和相关结构,而连续时间模型的误差项被认为是不相关的。这些结果表明,需要替代模型来对此类国库券收益数据进行建模。

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