Abstract
Estimates of option-implied probability distributions are routinely used in central banks, as well as in other institutions, but their reliability is often difficult to assess. To address this issue, we propose a semi-nonparametric model that allows to compute exact credible intervals around estimated distributions. By analyzing a panel of S&P 500 options, we find that the estimates of the distributions are quite precise. We also provide evidence that the multi-modality often found in option-implied distributions could be an artifact due to over-fitting, and that models with uni-modality constraints have high posterior odds.
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