forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve …

We study the relationship between conditional quantiles of returns and the long-, medium- and short-term volatility in … the volatility time series provides us with new insights into the pricing of risk and increases the accuracy of our …

This paper investigates the role of volatility risk on stock return predictability specified on two global financial … volatility forecasting measures on future stock returns in four different periods (bear and bull markets). First we find clear … and robust empirical evidence that the implied idiosyncratic volatility is the best stock return predictor for every sub …

degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which … forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation … distribution of returns. Carefully modeling this volatility risk is fundamental. We propose a dually asymmetric realized volatility …

price volatility. To address this issue, we find a phenomenon, "momentum of jumps" (MoJ), that the predictive ability of the … jump component is persistent when forecasting the oil futures market volatility. Specifically, we propose a strategy that … according to their recent past forecasting performance. The volatility data are based on the intraday prices of West Texas …

paper investigates the impact of EPU on the crude oil return volatility and which EPU index has the most forecasting power … the crude oil return volatility, but the effect is short-lived and the decay period is about one year. Particularly, our … results show that the US EPU index has the best forecasting power for crude oil return volatility over the long-term, whereas …