In this paper, we estimate, model and forecast Realized Range Volatility, a new realized measure and estimator of the …-known stylized effects present in financial data. We consider an HAR model with asymmetric effects with respect to the volatility and …

The volatility of equity and foreign exchange market is an important input to portfolio selection and to asset pricing … models. Many investment decisions and valuation of derivatives frequently rely on predictions of volatility. In this paper we … review the existing empirical literature in forecasting volatility of financial time series. Particularly, we decompose the …

In this paper, we estimate, model and forecast Realized Range Volatility, a realized measure and estimator of the … forecasting daily stocks volatility. We consider an HAR model with asymmetric effects with respect to the volatility and the … volatility series and they have a highly in-sample explanatory power. The analysis of the forecast performance in 16 NYSE stocks …

In this paper, we study the methods of combining different volatility forecasts using various GARCH models. Given that … the major risk exposure for many investors in energy is the volatility of the electricity price, our motivation stems from … the fact that there is no single best model for forecasting such volatility. Ample evidence suggests that most of the …

In this paper, we use factor-augmented HAR-type models to predict the daily integrated volatility of asset returns. Our … approach is based on a proposed two-step dimension reduction procedure designed to extract latent common volatility factors …, we apply either LASSO or elastic net shrinkage on estimates of integrated volatility of all constituents in the dataset …

broadly, our study dispels the notion that volatility is not forecastable at long horizons and offers an approach that …

This paper introduces a parsimonious and yet flexible semiparametric model to forecast financial volatility. The new …

forecasts of daily integrated volatility. Our approach is based on a two-step shrinkage procedure designed to extract latent … common volatility factors from a large dimensional and high-frequency asset returns dataset. In the first step, we apply …, in order to estimate a latent return factor. This new factor is in turn utilized to construct a latent volatility factor …

volatility (RV) of ten global stock market indices in the period from January 2000 to December 2021. We train models using a …

This paper provides empirical evidence that combinations of option implied and time series volatility forecasts that … application is for volatility forecasts of the Mexican Peso–US Dollar exchange rate, where realized volatility calculated using … intra-day data is used as a proxy for the (latent) daily volatility. -- Composite Forecasts ; Forecast Evaluation ; GARCH …