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 National Bureau of Economic Research, Inc in its series NBER Working Papers with number
11188.
Length: Date of creation: Mar 2005 Date of revision: Handle: RePEc:nbr:nberwo:11188
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Paper
Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005.
"Volatility Forecasting,"
PIER Working Paper Archive
05-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
[Downloadable!]
Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005.
"Volatility Forecasting,"
CFS Working Paper Series
2005/08, Center for Financial Studies.
[Downloadable!]
Find related papers by JEL classification: C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General G1 - Financial Economics - - General Financial Markets
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