Joint calibration of VIX and VXX options: does volatility clustering matter?
研究了波动率聚集对VIX和VXX期权联合校准的影响，发现包含波动率聚集的模型在样本内和样本外表现更优，且VXX期权包含VIX期权未覆盖的信息，联合使用两者数据可提高定价效果。
This paper studies the effects of volatility clustering on the joint calibration of VIX and VXX options. We find that model which incorporates volatility clustering outperforms other models without this feature in joint calibration of VIX and VXX options both in-sample and out-of-sample; the superiority of the model with volatility clustering is statistically significant. Moreover, the information contained in the VXX options is not fully spanned by the VIX options, as a result, one can achieve better joint pricing performance by employing both VIX and VXX derivatives data when calibrating the model, compared to the case when only VIX data are used in calibration.