Generating options-implied probability densities to understand oil market events

Deepa Datta, Juan M. Londono and Landon J. Ross

Energy Economics, 2017, vol. 64, issue C, 440-457

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.

Keywords: Options-implied PDFs; Futures; Options; Oil (search for similar items in EconPapers)
JEL-codes: C13 G13 G14 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)

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Related works:
Working Paper: Generating Options-Implied Probability Densities to Understand Oil Market Events (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:64:y:2017:i:c:p:440-457

DOI: 10.1016/j.eneco.2016.01.006

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