Pricing VIX Futures and Options With Good and Bad Volatility of Volatility¶
Bibliographic record. Follow the original-source link for the publication.
| Field | Value |
|---|---|
| Primary domain | Volatility |
| Other domains | — |
| Methods | Research Methods |
| Facets | Instrument Vix Options |
| Authors | Zhiyu Guo, Zhuo Huang, Chen Tong |
| Published | 2024-08-19 |
| Source | Journal of Futures Markets |
| Identifiers | doi:10.1002/fut.22545 |
| URL | Open original source |
Editorial synthesis¶
Why it matters¶
For VIX futures and options, if the model genuinely improves pricing accuracy, it affects model risk and hedging confidence. The claim concerns volatility-factor specification and the practical credibility of pricing for volatility derivatives. (abstract:S1, abstract:S2, abstract:S3, abstract:S4)
Main author claims¶
- The authors claim to model VIX dynamics from realized semivariances and derive closed-form pricing formulas for both VIX futures and options. (
abstract:S1,abstract:S2) - They claim superior pricing performance versus conventional unsigned realized variance and Heston-Nandi GARCH models in and out of sample, with upside/downside decomposition improving results. (
abstract:S3,abstract:S4)
Data, method, or discussion scope¶
The evidence is limited to directional abstract-level statements and does not provide instrument set, windows, error metrics, or microstructure/cost treatment details. (abstract:S1, abstract:S2, abstract:S3, abstract:S4)
Main limitations¶
Relative superiority is asserted without explicit significance criteria, out-of-sample protocol, or benchmark calibration details, so overfitting and sample-selection concerns cannot be excluded. (abstract:S3, abstract:S4)
Relationships¶
- None recorded.