Working Paper: NBER ID: w11188
Authors: Torben G. Andersen; Tim Bollerslev; Peter F. Christoffersen; Francis X. Diebold
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.
Keywords: Volatility; Forecasting; Financial Economics; Risk Management
JEL Codes: C1; G1
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| volatility (E32) | financial decision-making (G11) |
| volatility (E32) | risk management (G22) |
| conditional variance of asset returns (C46) | volatility forecasting (G17) |
| optimal forecasts from volatility models (G17) | risk management practices (G22) |