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Prediction in dynamic models with time-dependent conditional variances

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2.9 Mb
Date
1992-01-01
Authors
Bollerslev Richard, T
Baillie, T
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Abstract
This paper considers forecasting the conditional mean and variance from a single-equation dynamic model with autocorrelated disturbances following an ARMA process, and innovations with time-dependent conditional heteroskedasticity as represented by a linear GARCH process. Expressions for the minimum MSE predictor and the conditional MSE are presented. We also derive the formula for all the theoretical moments of the prediction error distribution from a general dynamic model with GARCH(1, 1) innovations. These results are then used in the construction of ex ante prediction confidence intervals by means of the Cornish-Fisher asymptotic expansion. An empirical example relating to the uncertainty of the expected depreciation of foreign exchange rates illustrates the usefulness of the results. © 1992.
Type
Journal article
Permalink
https://hdl.handle.net/10161/1913
Published Version (Please cite this version)
10.1016/0304-4076(92)90066-Z
Publication Info
Bollerslev Richard, T; & Baillie, T (1992). Prediction in dynamic models with time-dependent conditional variances. Journal of Econometrics, 52(1-2). pp. 91-113. 10.1016/0304-4076(92)90066-Z. Retrieved from https://hdl.handle.net/10161/1913.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
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