Torben G. Andersen
Northwestern University - Kellogg School of Management; National Bureau of Economic Research (NBER); University of Aarhus - CREATES
Duke University - Finance; Duke University - Department of Economics; National Bureau of Economic Research (NBER)
University of Toronto - Rotman School of Management; Copenhagen Business School; University of Aarhus - CREATES
Francis X. Diebold
University of Pennsylvania - Department of Economics; National Bureau of Economic Research (NBER)
February 22, 2005
PIER Working Paper No. 05-011; CFS Working Paper No. 2005/08
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.
Number of Pages in PDF File: 114
JEL Classification: C10, C53, G1
Date posted: February 28, 2005
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