Chapter 15 Volatility and Correlation Forecasting

Torben G. Andersen*, Tim Bollerslev, Peter F. Christoffersen, Francis X. Diebold

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

222 Scopus citations


Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical insights to emerge from this burgeoning literature, with a distinct focus on forecasting applications. Volatility is inherently latent, and Section 1 begins with a brief intuitive account of various key volatility concepts. Section 2 then discusses a series of different economic situations in which volatility plays a crucial role, ranging from the use of volatility forecasts in portfolio allocation to density forecasting in risk management. Sections 3-5 present a variety of alternative procedures for univariate volatility modeling and forecasting based on the GARCH, stochastic volatility and realized volatility paradigms, respectively. Section 6 extends the discussion to the multivariate problem of forecasting conditional covariances and correlations, and Section 7 discusses volatility forecast evaluation methods in both univariate and multivariate cases. Section 8 concludes briefly.

Original languageEnglish (US)
Title of host publicationHandbook of Economic Forecasting
EditorsG. Elliott, C.W.J. Granger, Granger Timmermann
Number of pages102
StatePublished - 2006

Publication series

NameHandbook of Economic Forecasting
ISSN (Print)1574-0706


  • covariance forecasting
  • realized volatility
  • stochastic volatility
  • volatility modeling

ASJC Scopus subject areas

  • Economics and Econometrics


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