Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these … forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the assumptions of jumping …

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the … assumptions of jumps in prices and leverage effects for volatility. Findings suggest that daily-data models are preferred to HF …

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 … threshold bipower variation measures. Incorporating signed finite and infinite jumps generates significantly better real …

their forecasting performance. Our findings reveal significant heterogeneity in ETM volatility patterns, which challenge …

using these models in an out-of-sample forecasting exercise compared with the forecasts obtained based on the usual linear …

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

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 …

volatility information improves the day volatility estimation. The results indicate a forecasting improvement using bivariate …