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Structural analysis with multivariate autoregressive index models

Carreiro, Andrea; Kapetanios, George; Marcellino, … - 2015

Persistent link: https://www.econbiz.de/10011391928

Structural analysis with Multivariate Autoregressive Index models

Carriero, Andrea; Kapetanios, George; Marcellino, … - In: Journal of econometrics 192 (2016) 2, pp. 332-348

Persistent link: https://www.econbiz.de/10011704654

A stochastic variance factor model for large datasets and an application to S&P data

Cipollini, Andrea (contributor); … - 2004 - [Elektronische Ressource]

Persistent link: https://www.econbiz.de/10001920657

The asymptotic distribution of the cointegration rank estimator under the Akaike information criterion

Kapetanios, George - In: Econometric theory 20 (2004) 4, pp. 735-742

Persistent link: https://www.econbiz.de/10002163092

Forecasting large datasets with Bayesian reduced rank multivariate models

Carriero, Andrea; Kapetanios, George; Marcellino, … - 2009

Persistent link: https://www.econbiz.de/10003887159

Forecasting large datasets with Bayesian reduced rank multivariate models

Carriero, Andrea; Kapetanios, George; Marcellino, … - 2009

Persistent link: https://www.econbiz.de/10003897081

Forecasting large datasets with Bayesian reduced rank multivariate models

Carriero, Andrea; Kapetanios, George; Marcellino, … - In: Journal of applied econometrics 26 (2011) 5, pp. 735-761

Persistent link: https://www.econbiz.de/10009408921

A stochastic variance factor model for large datasets and an application to S&P data

Cipollini, Andrea; Kapetanios, George - In: Economics letters 100 (2008) 1, pp. 130-134

Persistent link: https://www.econbiz.de/10003747500

Forecasting large datasets with reduced rank multivariate models

Carriero, Andrea (contributor); … - 2007

Persistent link: https://www.econbiz.de/10003564869

A Stochastic Variance Factor Model for Large Datasets and an Application to S&P Data

Kapetanios, George - 2009

The aim of this paper is to consider multivariate stochastic volatility models for large dimensional datasets. We suggest the use of the principal component methodology of Stock and Watson [Stock, J.H., Watson, M.W., 2002. Macroeconomic forecasting using diffusion indices. Journal of Business...

Persistent link: https://www.econbiz.de/10013159687