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 estimates models of high frequency index futures returns using 'around the clock' 5-minute returns that incorporate the following key features: multiple persistent stochastic volatility factors, jumps in prices and volatilities, seasonal components capturing time of the day patterns,...

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...