Abstract
This chapter 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.
| Original language | English |
|---|---|
| Title of host publication | Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning (In 4 Volumes) |
| Pages | 1533-1559 |
| Number of pages | 27 |
| ISBN (Electronic) | 9789811202391 |
| DOIs | |
| State | Published - 1 Jan 2020 |
Keywords
- Ex ante moments
- Implied volatility
- VIX
Fingerprint
Dive into the research topics of 'Does VIX truly measure return volatility?'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver