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Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate

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2019-05-19
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Co-integration and common trends are studied for time series variables, by introducing the new t-QVARMA (quasi-vector autoregressive moving average) model. t-QVARMA is an outlier-robust nonlinear score-driven model for the multivariate t-distribution. In t-QVARMA, the I(0) and I(1) components of the variables are separated in a way that is similar to the Granger-representation of VAR models. The relationship between the co-integrated federal funds effective rate and United States (US) inflation rate variables is studied for the period of July 1954 to January 2019. The in-sample statistical and out-of-sample forecasting performances of t-QVARMA are superior to those of the classical Gaussian-VAR model
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Multivariate Dynamic Conditional Score (Dcs) Models, Robustness To Outliers, Cointegration, Common Trends, Quasi-Vector Autoregressive Moving Average (Qvarma) Model
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