. 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 …

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 …

We examine whether the dynamics of the implied volatility surface of individual equity options contains exploitable …. In particular, we explore the possibility that the dynamics of the implied volatility surface of individual equity … options may be associated with movements in the volatility surface of S&P 500 index options. We present evidence of strong …

commonly used to forecast realized volatility, this paper also contributes to the literature by coupling realized measures with …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 …

In this paper, we apply machine learning to forecast the conditional variance of long-term stock returns measured in … of covariates as well as the smoothing parameters via cross-validation. We find that volatility forecastability is much …