Implied volatility surface predictability: the case of commodity markets

Fearghal Kearney*, Han Lin Shang, Lisa Sheenan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

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.
Original languageEnglish
Article number105657
Number of pages16
JournalJournal of Banking and Finance
Volume108
DOIs
Publication statusPublished - Nov 2019
Externally publishedYes

Keywords

  • Implied volatility surfaces
  • Options markets
  • Forecasting
  • Commodity finance

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