Recent work in asset pricing has focused on market-wide variance as a systematic factor and on firm-specific variance as idiosyncratic risk. We study an alternative channel through which the variability of financial market returns may help our understanding of cross-sectional price formation in...

We introduce a new stylized fact: the hump-shaped behavior of slopes and coefficients of determination as a function of the aggregation horizon when running (forward/backward) predictive regressions of future excess market returns onto past economic uncertainty (as proxied by market variance,...

We argue that the persistence properties of financial market volatility need to be taken into account when carrying out inference about volatility measures, for example when assessing the relation between realized and implied volatility series. If these volatility measures display long memory,...

We argue that the predictive regression between implied volatility (regressor) and realized volatility over the remaining life of a European option (regressand) is likely to be a fractional cointegrating relation. Because cointegration is associated with long-run comovements, this classical...

We argue that the predictive regression between implied volatility (regressor) and realized volatility over the remaining life of a European option (regressand) is likely to be a fractional cointegrating relation. Because cointegration is associated with long-run comovements, this classical...

Recent work in asset pricing has focused on market-wide variance as a systematic factor and on firm-specific variance as idiosyncratic risk. We study an alternative channel through which the variability of financial market returns may help our understanding of cross-sectional price formation in...

Cross-validation is the most common data-driven procedure for choosing smoothing parameters in nonparametric regression. For the case of kernel estimators with iid or strong mixing data, it is well-known that the bandwidth chosen by crossvalidation is optimal with respect to the average squared...