Research Details

Abstract

A growing literature documents important gains in asset return volatility forecasting via use of realized variation measures constructed from high-frequency returns. We progress by using newly developed bipower variation measures and corresponding nonparametric tests for jumps. Our empirical analyses of exchange rates, equity index returns, and bond yields suggest that the volatility jump component is both highly important and distinctly less persistent than the continuous component, and that separating the rough jump moves from the smooth continuous moves results in significant out-of-sample volatility forecast improvements. Moreover, many of the significant jumps are associated with specific macroeconomic news announcements.

Type

Article

Author(s)

Date Published

2007

Citations

. 2007. Roughing It Up: Including Jump Components in Measuring, Modeling and Forecasting Asset Return Volatility. Review of Economics and Statistics.(4): 701-720.