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Volatility and Correlation Forecasting

Torben Andersen (), Tim Bollerslev (), Peter Christoffersen and Francis Diebold ()

Chapter 15 in Handbook of Economic Forecasting, 2006, vol. 1, pp 777-878 from Elsevier

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 3-5 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-codes: B0 (search for similar items in EconPapers)
Date: 2006
ISBN: 0-444-51395-7
References: View references in EconPapers View complete reference list from CitEc
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