Working Paper: NBER ID: w11775
Authors: Torben G. Andersen; Tim Bollerslev; Francis X. Diebold
Abstract: A rapidly growing literature has documented important improvements in financial return volatility measurement and forecasting via use of realized variation measures constructed from high-frequency returns coupled with simple modeling procedures. Building on recent theoretical results in Barndorff-Nielsen and Shephard (2004a, 2005) for related bi-power variation measures, the present paper provides a practical and robust framework for non-parametrically measuring the jump component in asset return volatility. In an application to the DM/$ exchange rate, the S&P500 market index, and the 30-year U.S. Treasury bond yield, we find that jumps are both highly prevalent and distinctly less persistent than the continuous sample path variation process. Moreover, many jumps appear directly associated with specific macroeconomic news announcements. Separating jump from non-jump movements in a simple but sophisticated volatility forecasting model, we find that almost all of the predictability in daily, weekly, and monthly return volatilities comes from the non-jump component. Our results thus set the stage for a number of interesting future econometric developments and important financial applications by separately modeling, forecasting, and pricing the continuous and jump components of the total return variation process.
Keywords: Volatility; Jump Components; High-Frequency Data; Asset Pricing; Forecasting
JEL Codes: C1; G1
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| macroeconomic news announcements (E60) | jumps in asset return volatility (G17) |
| jumps in asset return volatility (G17) | less persistence than continuous sample path variation (C41) |
| continuous sample path variation (C22) | primary driver of forecasts for return volatilities (G17) |
| jumps in asset return volatility (G17) | no predictive power for future volatility when isolated from continuous component (C22) |