← Search

Journal of Banking & Finance Vol. 108 2019

Implied volatility surface predictability: The case of commodity markets

Fearghal Kearney1; Han Lin Shang2; Lisa Sheenan1

1 Queen's University Belfast · 2 Australian National University

open access

Abstract

Recent literature seek to forecast implied volatility derived from equity, index, foreign exchange, and interest rate options using latent factor and parametric frameworks. Motivated by increased public attention borne out of the financialization of futures markets in the early 2000s, we investigate if these extant models can uncover predictable patterns in the implied volatility surfaces of the most actively traded commodity options between 2006 and 2016. Adopting a rolling out-of-sample forecasting framework that addresses the common multiple comparisons problem, we establish that, for energy and precious metals options, explicitly modeling the term structure of implied volatility using the Nelson-Siegel factors produces the most accurate forecasts.

DOI
10.1016/j.jbankfin.2019.105657
Volume
108
Pages
105657
Language
en
Sources
bibtex:phds-export.bib openalex crossref

Cite