model in several ways, it allows for all the primary stylized facts of financial asset returns, including volatility … volatility, but without the estimation problems associated with the latter, and being applicable in the multivariate setting for …

We use machine learning methods to predict stock return volatility. Our out-of-sample prediction of realised volatility … realised volatility of 43.8% with an R2 being as high as double the ones reported in the literature. We further show that … machine learning methods can capture the stylized facts about volatility without relying on any assumption about the …

This paper quantifies the amount of noise and bias in analysts' forecast of corporate earnings at various horizons. We … increasing function of volatility …

We analyze the effects of the outbreak of the Russian-Ukrainian war on the volatility in commodity and financial … markets. The Russian invasion sharply raised the volatility of most assets, however, the scale of reactions was market … accuracy of volatility models and find the superiority of the modified Range GARCH model. Our findings reveal also a specific …

accounting for the long-term price dynamic (i.e. its independent modeling), has demonstrated its efficiency in gaining forecast … requiring any a priori setups, still, do not solve the studied issue. In turn, forecast combining conducted for individual … priori choices, but also has lower forecast error and, thus, performs better than individual models. We also propose a 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 estimate MIDAS regressions with various (bi)power variations to predict future volatility measured via increments in …