Roughing it up: Including jump components in the measurement, modeling, and forecasting of return volatility

• 成果类型: Review
• 署名作者: Andersen, Torben G.; Bollerslev, Tim; Diebold, Francis X.
• 署名单位: Northwestern University; Duke University; University of Pennsylvania
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/rest.89.4.701
• 发表日期: 2007-11
• 页码: 701-720
• 关键词: continuous-time model; high-frequency data; stochastic volatility; long-memory; foreign-exchange; realized volatility; power variation; MARKET; variance; DYNAMICS

摘要

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.