ARCH Models

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1994

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Abstract

This chapter evaluates the most important theoretical developments in ARCH type modeling of time-varying conditional variances. The coverage include the specification of univerate parametric ARCH models, general inference procedures, conditions for stationarity and ergodicity, continuous time methods, aggregation and forecasting of ARCH models, multivariate conditional covariance formulations, and the use of model selection criteria in an ARCH context. Additionally, the chapter contains a discussion of the empirical regularities pertaining to the temporal variation in financial market volatility. Motivated in part by recent results on optimal filtering, a new conditional variance model for better characterizing stock return volatility is also presented.

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Bollerslev

Tim Bollerslev

Juanita and Clifton Kreps Distinguished Professor of Economics, in Trinity College of Arts and Sciences

Professor Bollerslev conducts research in the areas of time-series econometrics, financial econometrics, and empirical asset pricing finance. He is particularly well known for his developments of econometric models and procedures for analyzing and forecasting financial market volatility. Much of Bollerslev’s recent research has focused on the analysis of newly available high-frequency intraday, or tick-by-tick, financial data and so-called realized volatility measures, macroeconomic news announcement effects, and the pricing of volatility risk. Recent reviews of his work are available in the two Handbook chapters "Volatility and Correlation Forecasting” (with Torben G. Andersen, Peter Christoffersen and Francis X. Diebold), Handbook of Economic Forecasting, (eds. Graham Elliott, Clive W.J. Granger and Allan Timmermann), 2006, and "Parametric and Nonparametric Volatility Measurement” (with Torben G. Andersen and Francis X. Diebold), in Handbook of Financial Econometrics, (eds. Yacine Aït-Sahalia and Lars P. Hansen), 2009.


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