Generating options-implied probability densities to understand oil market events

A-Tier
Journal: Energy Economics
Year: 2017
Volume: 64
Issue: C
Pages: 440-457

Authors (3)

Datta, Deepa Dhume (not in RePEc) Londono, Juan M. (Federal Reserve Board (Board o...) Ross, Landon J. (not in RePEc)

Score contribution per author:

1.341 = (α=2.01 / 3 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

We investigate the informational content of options-implied probability density functions (PDFs) for the future price of oil. Using a semiparametric variant of the methodology in Breeden and Litzenberger (1978), we investigate the fit and smoothness of distributions derived from alternative PDF estimation methods, and develop a set of robust summary statistics. Using PDFs estimated around episodes of high geopolitical tensions, oil supply disruptions, macroeconomic data releases, and shifts in OPEC production strategy, we explore the extent to which oil price movements are expected or unexpected, and whether agents believe these movements to be persistent or temporary.

Technical Details

RePEc Handle
repec:eee:eneeco:v:64:y:2017:i:c:p:440-457
Journal Field
Energy
Author Count
3
Added to Database
2026-01-25