Nonparametric correlation estimators as the Kendall and Spearman correlation are widely used in the applied sciences. They are often said to be robust, in the sense of being resistant to outlying observations. In this paper we formally study their robustness by means of their influence functions...

Using high-frequency stock market data and (synthetic) variance swap rates, this paper identifies and investigates the temporal variation in the market variance risk-premium. The variance risk is manifest in two salient features of financial returns: stochastic volatility and jumps. The pricing...

We introduce the realized co-range, a novel estimator of the daily covariance between asset returns based on intraday high-low price ranges. In an ideal world, the co-range is five times more efficient than the realized covariance, which uses cross-products of intraday returns, when sampling at...