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

is highly integrated. Introducing a new World Fear index, we find that local and global aggregate market returns are … mainly driven by global tail risk rather than local tail risk. World fear is also priced in the crosssection of stock returns …. Buying stocks with high sensitivities to World Fear while selling stocks with low sensitivities generates excess returns of …

relationship between the S&P500 Composite Index and the Volatility Index (VIX), but few empirical studies have focused on the … affect ETF returns. The ARCH-LM test shows conditional heteroskedasticity in the estimation of ETF returns, so that the …

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

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 …

using recently developed volatility models, including HEAVY, Realized GARCH and GAS models, applied to daily returns on the …

We investigate the pricing of volatility risks in currency markets. First, we show that pricing ability of volatility … risk is concentrated in some of its components. Diffusive volatility dominates jump volatility in pricing carry trade … returns, while jump volatility is important in jointly explaining carry trade and momentum returns. Both short-run and long …

For forecasting volatility of futures returns, the paper proposes an indirect method based on the relationship between … futures and the underlying asset for the returns and time-varying volatility. For volatility forecasting, the paper considers … that the new method based on stochastic volatility models with the asymmetry and long memory outperforms the forecasting …