sample path and jump components, thus enhancing forecasting performance. We generalize the heterogeneous autoregressive (HAR …) model to include implied volatility as an additional regressor, and to the separate forecasting of the realized components … endogeneity of implied volatility in the forecasting equations. We show that implied volatility is a biased and inefficient …

-form volatility modeling and forecasting as well as testing for the presence of jumps. …

. Previous work has found that jumps at an index level are not related to future volatility. Here we examine the links between co-jumps … common, or co-jumps between the stocks are unrelated to the level of volatility or correlation. On the other hand, both … volatility and correlation are lower subsequent to a co-jump. This indicates that co-jumps are a transient event but in contrast …

investment horizons. Results suggest that understanding jumps and co-jumps is important for forecasting the covariance and the … time series econometrics and economic forecasting during the recent decades. Current financial crisis have shown that … into several investment horizons. Our estimator is moreover able to separate individual jumps, co-jumps and true …

the first-order asymptotic validity of this method in the multivariate context with a potential presence of jumps …

This paper examines the impact of intraday periodicity on forecasting realized volatility using a heterogeneous … estimators. This combined effect adversely affects forecasting. To account for this, we propose a periodicity-adjusted model …

The focus of the volatility literature on forecasting and the predominance of the conceptually simpler HAR model over …