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Volatility Forecasting

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

No 11188, NBER Working Papers from National Bureau of Economic Research, Inc

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.

JEL-codes: C1 G1 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cfn, nep-ecm, nep-ets and nep-fin
Date: 2005-03
Note: AP EFG
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