114 Pages Posted: 28 Feb 2005
Date Written: February 22, 2005
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, 4 and 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.
JEL Classification: C10, C53, G1
Suggested Citation: Suggested Citation
Andersen, Torben G. and Bollerslev, Tim and Christoffersen, Peter and Diebold, Francis X., Volatility Forecasting (February 22, 2005). PIER Working Paper No. 05-011; CFS Working Paper No. 2005/08. Available at SSRN: https://ssrn.com/abstract=673405 or http://dx.doi.org/10.2139/ssrn.673405
By Meb Faber