Several novel large volatility matrix estimation methods have been developed based on the high-frequency financial data …. They often employ the approximate factor model that leads to a low-rank plus sparse structure for the integrated volatility … matrix and facilitates estimation of large volatility matrices. However, for predicting future volatility matrices, these …

In the past decade, the popularity of realized measures and various linear models for volatility forecasting has … the ongoing debate with a comprehensive evaluation of multiple-step-ahead volatility forecasts of energy markets using … commonly used to forecast realized volatility, this paper also contributes to the literature by coupling realized measures with …

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 …

forecasting the volatility of equity prices, using high-frequency data from 2000 to 2016. We consider the SPY and 20 stocks that …, 60 and 300 seconds), forecast horizons (1, 5, 22 and 66 days) and the use of standard and robust-to-noise volatility and …-time forecasts than the HAR-RV model, although no single extended model dominates. In general, standard volatility measures at the …

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 …

forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve …

returns, such as leptokurtosis and asymmetric distribution, volatility clustering, asymmetric relationship between stock … accurate VaR forecasts. Especially for the high confidence levels, a risk manager must employ different volatility techniques …

high-frequency data better and produce more accurate forecasts than competing realized volatility and option …