This paper examines an issue overlooked in the finance and economics literature: time variation in announcement volatility or event risk. We combine long spans of high-frequency data with a flexible parametric model of returns, which al- lows to identify announcement returns, capture intraday...

This paper provides an optimal filtering methodology in discretely observed continuous-time jump-diffusion models. Although the filtering problem has received little attention, it is useful for estimating latent states, forecasting volatility and returns, computing model diagnostics such as...

This paper provides a methodology for estimating FOMC event risk from options and studies how index option markets price FOMC event risk. Using high-quality intraday option data for short maturities we are able to cleanly estimate ex-ante FOMC event risk, avoiding the use of noisy proxies like...