#05-04
Volatility Forecasting
Torben G. Andersen, Tim Bollerslev, Peter F. Christoffersen, and Francis X. Diebold
Abstract: 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.
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