Rogers-Satchell (RS) measure is an efficient volatility measure. This paper proposes quantile RS (QRS) measure to … on Standard and Poor 500 and Dow Jones Industrial Average indices show that volatility estimates using QRS measures …-of-sample forecast. For return models, the constant mean structure with Student-t errors and QRS volatility estimates provides the best …

This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset … predictive performance relative to the standard volatility models. Furthermore, we construct volatility timing portfolios and …

strongest during bad economic times. In line with this evidence, we document that stock volatility predictability is also state …-series volatility models, in this paper we comprehensively examine how volatility forecastability varies across bull and bear states of … the stock market. We find that the volatility forecast horizon is substantially longer when the market is in a bear state …

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 … international volatility risk proxies. We find that international volatility risks are negatively associated with contemporaneous …

includes several episodes of high volatility in the oil market. Our evidence shows that penalized regressions provided the best …

volatility. Finally, we show that trading volume will be higher when textual sentiment is unusually high or low and when there …

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 …