Volatility of Volatility and VIX Forecasting: New Evidence Based on Jumps, the Short‐Term and Long‐Term Volatility

ABSTRACT This study explores VIX forecasting by proposing a novel model to characterize the volatility of volatility based on high‐frequency VIX. Specifically, the decomposed jumps, the short‐ and long‐term volatility of VIX realized volatility obtained through wavelet analysis are considered by integrating the HAR‐DJI‐GARCH with GARCH‐MIDAS model. Empirical results show superior performance over competing models, with enhanced predictive accuracy under four non‐parametric jumps. The model's effectiveness is further validated by adjusting prediction windows, wavelet levels, examining VIX term structure, varying the significance level of jump test, and through the assessment of its economic significance.

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Publication Details

Journal
Journal of Futures Markets
Published
2024-09-30
DOI
https://doi.org/10.1002/fut.22553
Citations
5
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
2.70

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article

Volatility of Volatility and VIX Forecasting: New Evidence Based on Jumps, the Short‐Term and Long‐Term Volatility

Chao Liang, Gaoxiu Qiao, Yijie Zhou, Wanmei Cui
5 citations
Journal of Futures Markets
Stochastic processes and financial applications
2.70
article

Volatility of Volatility and VIX Forecasting: New Evidence Based on Jumps, the Short‐Term and Long‐Term Volatility

Chao Liang, Gaoxiu Qiao, Yijie Zhou, Wanmei Cui
article en
5 citations

Abstract

ABSTRACT This study explores VIX forecasting by proposing a novel model to characterize the volatility of volatility based on high‐frequency VIX. Specifically, the decomposed jumps, the short‐ and long‐term volatility of VIX realized volatility obtained through wavelet analysis are considered by integrating the HAR‐DJI‐GARCH with GARCH‐MIDAS model. Empirical results show superior performance over competing models, with enhanced predictive accuracy under four non‐parametric jumps. The model's effectiveness is further validated by adjusting prediction windows, wavelet levels, examining VIX term structure, varying the significance level of jump test, and through the assessment of its economic significance.

Journal of Futures MarketsVol. 45(1)
Southwest Jiaotong University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Sichuan Province
Openalex Percentile: Top 9%
Stochastic processes and financial applications
2.70
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