This work aims to investigate the (inter)relations of information arrival, news sentiment, volatility and jump dynamics … volatility modelling is justified in our specific calibration samples (2008 and 2013, respectively). However, our results reject …

. Applying our model to high-frequency transaction data, we detect two distinct regimes in the intraday volatility process: a … dominant volatility regime that is observable throughout the trading day representing the risk-transferring trading activity of … investors, and a minor volatility regime that concentrates around market liquidity shocks which mainly capture impacts of firm …

This paper introduces novel volatility diffusion models to account for the stylized facts of high-frequency financial … data such as volatility clustering, intra-day U-shape, and leverage effect. For example, the daily integrated volatility of … the proposed volatility process has a realized GARCH structure with an asymmetric effect on log-returns. To further …

. They are applicable to the complete class of observation driven models and are valid for a wide range of estimation … that is embedded in the time-varying parameter path. We illustrate our findings in a volatility analysis for monthly …

increases in realized volatility and arrive when differences-in-opinion among market participants are large at times of FOMC … press releases. Unlike intensity jumps, volatility jumps fail to explain the variation in news-induced realized volatility …

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …

There is evidence that volatility forecasting models that use intraday data provide better forecast accuracy as … fills this gap in the literature and extends previous studies on forecasting stock market volatility in several important …, we use forecast horizons ranging from 1 day to 6 months. Third, we evaluate the precision of volatility forecast provided …

Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many … forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the assumptions of jumping …