This article presents a comprehensive analysis of the relative ability of three information sets --- daily trading volume, intraday returns and overnight returns --- to predict equity volatility. We investigate the extent to which statistical accuracy of one-day-ahead forecasts translates into...

We document the forecasting gains achieved by incorporating measures of signed, finite and infinite jumps in forecasting the volatility of equity prices, using high-frequency data from 2000 to 2016. We consider the SPY and 20 stocks that vary by sector, volume and degree of jump activity. We use...

This paper examines the finite sample properties of novel theoretical tests that evaluate the presence of: a) Brownian motion, b) jumps; c) finite vs. infinite activity jumps. In allowing for Gaussian, t-distributed, and Gaussian-T mixture noise, our Monte Carlo experiment guides a search for...

This paper examines the impact of intraday periodicity on forecasting realized volatility using a heterogeneous autoregressive model (HAR) framework. We show that periodicity inflates the variance of the realized volatility and biases jump estimators. This combined effect adversely affects...

We document the forecasting gains achieved by incorporating measures of signed, finite and infinite jumps in forecasting the volatility of equity prices, using high-frequency data from 2000 to 2016. We consider the SPY and 20 stocks that vary by sector, volume and degree of jump activity. We use...