Estimating volatility-of-volatility: A comparative analysis

This paper compares four volatility-of-volatility estimates with the CBOE’s VVIX index for prediction accuracy. Hybrid estimates, combining historical and model-based components, show closer alignment with VVIX. Practical limitations are briefly noted. • Compares four volatility-of-volatility (VV) estimates with CBOE’s VVIX. • Uses MAE and copula to compare VV estimates accuracy. • Moving average (MIVV) of Baltussen et al. (2018) shows the strongest alignment with VVIX. • Discusses VV estimates applied to stocks with sparse strikes.

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Publication Details

Journal
Economics Letters
Published
2025-03-29
DOI
https://doi.org/10.1016/j.econlet.2025.112298
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Estimating volatility-of-volatility: A comparative analysis

Dehong Liu, Carl R. Chen, Jianglei Yuan, Mingye Ma
Economics Letters
Stochastic processes and financial applications
article

Estimating volatility-of-volatility: A comparative analysis

Dehong Liu, Carl R. Chen, Jianglei Yuan, Mingye Ma
article en

Abstract

This paper compares four volatility-of-volatility estimates with the CBOE’s VVIX index for prediction accuracy. Hybrid estimates, combining historical and model-based components, show closer alignment with VVIX. Practical limitations are briefly noted. • Compares four volatility-of-volatility (VV) estimates with CBOE’s VVIX. • Uses MAE and copula to compare VV estimates accuracy. • Moving average (MIVV) of Baltussen et al. (2018) shows the strongest alignment with VVIX. • Discusses VV estimates applied to stocks with sparse strikes.

Economics LettersVol. 250
University of Dayton (US), Beijing Jiaotong University (CN), University of Southampton (GB)
Openalex Percentile: Top 92%
Stochastic processes and financial applications
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