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 …

Option-implied moments, like implied volatility, contain useful information about an underlying asset's return …

Chinese daily overnight stock returns, while positively forecast next-day Chinese daytime stock returns. The US volatility …This paper investigates the predictive ability of international volatility risk for the daily aggregate Chinese stock … market returns. We employ the innovations in implied volatility indices of seven major international markets as our …

volatility model are included in this paper to forecast VaR. In a series of extensive back tests, this paper finds that the … volatility models can improve the accuracy of 1-day ahead VaR forecasting beyond the performance of frequently used models. As … such, this paper constructs 60 conditional volatility forecasting models. Several extensions of the GARCH model are …

Standard realized volatility (RV) measures estimate the latent volatility of an asset price using high frequency data … estimate of volatility to the application in which it will be used. For example, if the volatility measure will be used in a … volatility. We use methods from machine learning to estimate optimal “bespoke” RVs for heterogeneous autoregressive (HAR) and …

significantly higher utility for volatility managed portfolios. Superior forecast performance is especially pronounced for firms … forest. In contrast to conventional random forests that approximate the volatility nonparametrically using local averaging … forecasting performance of the HAR forest across multiple forecast horizons and across 186 S&P 500 constituents. This leads to …