文章基本信息

标题：Estimation and forecasting in large datasets with conditionally heteroskedastic dynamic common factors
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作者：Lucia Alessi ; Matteo Barigozzi ; Marco Capasso 等
期刊名称：Euro Area Balance of Payments and International Investment Position Statistics
印刷版ISSN：1830-3420
电子版ISSN：1830-3439
出版年度：2009
卷号：1
出版社：European Central Bank
摘要：We propose a new method for multivariate forecasting which combines Dynamic Factor and multivariate GARCH models. The information contained in large datasets is captured by few dynamic common factors, which we assume being conditionally heteroskedastic. After presenting the model, we propose a multi-step estimation technique which combines asymptotic principal components and multivariate GARCH. We also prove consistency of the estimated conditional covariances. We present simulation results in order to assess the finite sample properties of the estimation technique. Finally, we carry out two empirical applications respectively on macroeconomic series, with a particular focus on different measures of inflation, and on financial asset returns. Our model outperforms the benchmarks in forecasting the inflation level, its conditional variance and the volatility of returns. Moreover, we are able to predict all the conditional covariances among the observable series.
关键词：Dynamic Factor Models; Multivariate GARCH; Conditional Covariance;Inflation Forecasting; Volatility Forecasting.