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Volatility forecasting

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

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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Paper provided by Center for Financial Studies (CFS) in its series CFS Working Paper Series with number 2005/08.

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Date of creation: 2005
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Handle: RePEc:zbw:cfswop:200508

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