Does VIX Truly Measure Return Volatility?

Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning, Forthcoming

35 Pages Posted: 31 Aug 2014 Last revised: 7 Jul 2020

See all articles by Victor Chow

Victor Chow

West Virginia University - Department of Finance

Wanjun Jiang

Guang Hua School of Management, Peking University

Jingrui (Victoria) Li

Tulane University - A.B. Freeman School of Business

Date Written: January 22, 2018

Abstract

This article demonstrates theoretically that without imposing any structure on the underlying forcing process, the model-free CBOE volatility index (VIX) does not measure market expectation of volatility but that of a linear moment-combination. Particularly, VIX undervalues (overvalues) volatility when market return is expected to be negatively (positively) skewed. Alternatively, we develop a model-free generalized volatility index (GVIX). With no diffusion assumption, GVIX is formulated directly from the definition of log-return variance, and VIX is a special case of the GVIX. Empirically, VIX generally understates the true volatility, and the estimation errors considerably enlarge during volatile markets. The spread between GVIX and VIX follows a mean-reverting process.

Keywords: Implied Volatility, VIX, Ex-ante Moments

JEL Classification: G10

Suggested Citation

Chow, Victor and Jiang, Wanjun and Li, Jingrui, Does VIX Truly Measure Return Volatility? (January 22, 2018). Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning, Forthcoming, Available at SSRN: https://ssrn.com/abstract=2489345 or http://dx.doi.org/10.2139/ssrn.2489345

Victor Chow (Contact Author)

West Virginia University - Department of Finance ( email )

P. O. Box 6025
Morgantown, WV 26506
United States

Wanjun Jiang

Guang Hua School of Management, Peking University ( email )

Beijing
China

Jingrui Li

Tulane University - A.B. Freeman School of Business ( email )

7 McAlister Drive
New Orleans, LA 70118
United States

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