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. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized …

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. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized …

foreign exchange markets. -- Random Lognormal cascades ; GMM estimation ; best linear forecasting ; volatility of financial … Generalized Method of Moments (GMM) estimation procedure to cope with the documented difficulties of previous methodologies. We … by estimating the intermittency parameter and forecasting of volatility for a sample of financial data from stock and …

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 …

This paper studies the intertemporal relation between U.S. volatility risk and international equity risk premia. We … show that a common volatility risk factor constructed from the option-implied U.S. forward variances positively and … robust to the inclusion of existing domestic and U.S. predictors and alternative U.S. volatility risk proxies. The …