Generating options-implied probability densities to understand oil market events

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. •Semiparametric method to calculate options-implied PDFs for oil future prices•Explore methods for fitting options-implied curves and unobserved tails•Investigate the trade-off between pricing errors and PDF smoothness across methods•Options-implied moments that rely on unobserved tails are less robust.•Explore changes in options-implied PDFs around important market events