Implied volatility surface predictability: the case of commodity markets¶
Bibliographic record. Follow the original-source link for the publication.
| Field | Value |
|---|---|
| Primary domain | Volatility |
| Other domains | — |
| Methods | Research Methods |
| Facets | — |
| Authors | Fearghal Kearney, Han Lin Shang, Lisa Sheenan |
| Published | 2019-09-21 |
| Source | arXiv Quantitative Finance History |
| Identifiers | arxiv:1909.11009 |
| URL | Open original source |
Editorial synthesis¶
Why it matters¶
The paper compares commodity IV-surface models under rolling out-of-sample evaluation and multiple-comparison control, directly addressing whether a model-search winner retains predictive advantage. (abstract:S1, abstract:S2, abstract:S3)
Main author claims¶
- The authors study the most actively traded commodity options from 2006–2016 and compare existing latent-factor and parametric IV-surface frameworks. (
abstract:S1,abstract:S2) - The authors report that, under their rolling out-of-sample and multiple-comparison procedure, Nelson–Siegel term-structure methods are most accurate for energy and precious-metals options. (
abstract:S3)
Data, method, or discussion scope¶
The abstract gives the period, active-commodity scope, evaluation design, and ranking, but not contract definitions, the candidate set, loss function, correction method, or numerical gaps. (abstract:S1, abstract:S2, abstract:S3)
Main limitations¶
“Most accurate” lacks a quantified gap; it is unclear whether multiple-comparison control spans the full search space or whether the result transfers to other commodities and periods. (abstract:S2, abstract:S3)
Relationships¶
- None recorded.