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 …

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 …

We provide empirical evidence of volatility forecasting in relation to asymmetries present in the dynamics of both … return and volatility processes. Using recently-developed methodologies to detect jumps from high frequency price data, we … estimate the size of positive and negative jumps and propose a methodology to estimate the size of jumps in the quadratic …

forecasting performances across most of the forecasting horizons. Moreover, we found that models using the VRP as an additional … forecasting performances were not statistically different for most models, and only the Principal Component Regression (PCR) and … the Partial least squares (PLS) regression were consistently excluded from the set of best forecasting models. These …

We survey the literature on stock return forecasting, highlighting the challenges faced by forecasters as well as …-of-sample tests. Recent studies, however, provide improved forecasting strategies that deliver statistically and economically … model restrictions, forecast combination, diffusion indices, and regime shifts—improve forecasting performance by addressing …