augmenting a large class of volatility models with implied volatility and Google Trends data improves the quality of the … during periods of high volatility, when parameters estimates became very unstable. Moreover, several models augmented with … markets, T-GARCH models with implied volatility and student's t errors are better choices if robust market risk measures are …

. Still, little is known about how far ahead one can forecast volatility. First, in this paper we introduce the notions of the … and forward forecast accuracy curves. Then, by employing a few popular time-series volatility models, we perform a …Volatility forecasting is crucial for portfolio management, risk management, and pricing of derivative securities …

-frequency data and, at the same time produces a direct forecast of the variance at the desired horizon, without iterating. The MIDAS … 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 …

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

the financial crisis, suggesting that an extreme volatility period requires models that can adapt quickly to turmoil …

assets. Building on this idea, we propose the use of a highly flexible and tractable model to forecast the volatility of an …

The GARCH(1,1) model and its extensions have become a standard econometric tool for modeling volatility dynamics of … on the basis of their one-step ahead forecasting performance. With regard to forecast unbiasedness and precision …

The GARCH(1,1) model and its extensions have become a standard econometric tool for modeling volatility dynamics of … on the basis of their one-step ahead forecasting performance. With regard to forecast unbiasedness and precision …

more than a single regime, have performed substantially better than standard methods in terms of volatility and Value … individual models, we evaluate the use of forecast combinations strategies. In our empirical application, procedures that are …