Using two newly available ultrahigh-frequency datasets, we investigate empirically how frequently one can sample certain foreign exchange and U.S. Treasury security returns without contaminating estimates of their integrated volatility with market micro-structure noise. We find that one can...

Using two newly available ultrahigh-frequency datasets, we investigate empirically how frequently one can sample certain foreign exchange and U.S. Treasury security returns without contaminating estimates of their integrated volatility with market microstructure noise. Using volatility signature...

With the aim of constructing predictive distributions for daily returns, we introduce a new Markov normal mixture model in which the components are themselves normal mixtures. We derive the restrictions on the autocovariances and linear representation of integer powers of the time series in...

This paper considers a stylized asset pricing model where the returns from exchange rates, stocks and bonds are linked by basic risk-arbitrage relationships. Employing GMM estimation and monthly data for 18 economies and the US (treated as the domestic country), we identify through a simple test...