Changing persistence in time series models means that a structural change from nonstationarity to stationarity or vice versa occurs over time. Such a change has important implications for forecasting, as negligence may lead to inaccurate model predictions. This paper derives generally applicable...

We introduce a heuristic bias-adjustment for the transaction price-based realized range estimator of daily volatility in the presence of bid–ask bounce and non-trading. The adjustment is an extension of the estimator proposed in Christensen et al. (2009). We relax the assumption that all...

We characterize the response of U.S., German and British stock, bond and foreign exchange markets to real-time U.S. macroeconomic news. Our analysis is based on a unique data set of high-frequency futures returns for each of the markets. We find that news surprises produce conditional mean...

The recent introduction of the realized variance measure defined as the sum of the squared intra-daily returns stamped on some high frequency basis has spurred the research in the field of volatility modeling and forecasting into new directions. First, the realized variance is a much better...