Skip to main content
Journal cover image

Volatility forecasting with range-based EGARCH models

Publication ,  Journal Article
Brandt, MW; Jones, CS
Published in: Journal of Business and Economic Statistics
October 1, 2006

We provide a simple, yet highly effective framework for forecasting return volatility by combining exponential generalized autoregressive conditional heteroscedasticity models with data on the range. Using Standard and Poor's 500 index data for 1983-2004, we demonstrate the importance of a long-memory specification, based on either a two-factor structure or fractional integration, that allows for some asymmetry between market returns and volatility innovations. Out-of-sample forecasts reinforce the value of both this specification and the use of range data in the estimation. We find substantial forecastability of volatility as far as 1 year from the end of the estimation period, contradicting the return-based conclusions of West and Cho and of Christoffersen and Diebold that predicting volatility is possible only for short horizons. © 2006 American Statistical Association Journal of Business & Economic Statistics.

Duke Scholars

Published In

Journal of Business and Economic Statistics

DOI

ISSN

0735-0015

Publication Date

October 1, 2006

Volume

24

Issue

4

Start / End Page

470 / 486

Related Subject Headings

  • Econometrics
  • 49 Mathematical sciences
  • 38 Economics
  • 35 Commerce, management, tourism and services
  • 15 Commerce, Management, Tourism and Services
  • 14 Economics
  • 01 Mathematical Sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Brandt, M. W., & Jones, C. S. (2006). Volatility forecasting with range-based EGARCH models. Journal of Business and Economic Statistics, 24(4), 470–486. https://doi.org/10.1198/073500106000000206
Brandt, M. W., and C. S. Jones. “Volatility forecasting with range-based EGARCH models.” Journal of Business and Economic Statistics 24, no. 4 (October 1, 2006): 470–86. https://doi.org/10.1198/073500106000000206.
Brandt MW, Jones CS. Volatility forecasting with range-based EGARCH models. Journal of Business and Economic Statistics. 2006 Oct 1;24(4):470–86.
Brandt, M. W., and C. S. Jones. “Volatility forecasting with range-based EGARCH models.” Journal of Business and Economic Statistics, vol. 24, no. 4, Oct. 2006, pp. 470–86. Scopus, doi:10.1198/073500106000000206.
Brandt MW, Jones CS. Volatility forecasting with range-based EGARCH models. Journal of Business and Economic Statistics. 2006 Oct 1;24(4):470–486.
Journal cover image

Published In

Journal of Business and Economic Statistics

DOI

ISSN

0735-0015

Publication Date

October 1, 2006

Volume

24

Issue

4

Start / End Page

470 / 486

Related Subject Headings

  • Econometrics
  • 49 Mathematical sciences
  • 38 Economics
  • 35 Commerce, management, tourism and services
  • 15 Commerce, Management, Tourism and Services
  • 14 Economics
  • 01 Mathematical Sciences