Prediction in ARMA models with GARCH in Mean Effects
AbstractThis paper considers forecasting the conditional mean and variance from an ARMA model with GARCH in mean effects. Expressions for the optimal predictors and their conditional and unconditional MSE's are presented. We also derive the formula for the covariance structure of the process and its conditional variance.
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Bibliographic InfoPaper provided by Department of Economics, University of York in its series Discussion Papers with number 99/11.
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Postal: Department of Economics and Related Studies, University of York, York, YO10 5DD, United Kingdom
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Web page: http://www.york.ac.uk/economics/
More information through EDIRC
ARMA Model; Conditional Moments; GARCH in Mean Effects;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-1999-10-28 (All new papers)
- NEP-ECM-1999-10-28 (Econometrics)
- NEP-ETS-1999-10-28 (Econometric Time Series)
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Cahiers de Recherches Economiques du DÃ©partement d'EconomÃ©trie et d'Economie politique (DEEP)
04.10, Université de Lausanne, Faculté des HEC, DEEP.
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"The Covariance Structure of Mixed ARMA Models,"
00/11, Department of Economics, University of York.
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- Christian Conrad & Enno Mammen, 2008. "Nonparametric Regression on Latent Covariates with an Application to Semiparametric GARCH-in-Mean Models," Working Papers 0473, University of Heidelberg, Department of Economics, revised Jul 2008.
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