Essays on Alternative Methods of Identification and Estimation of Vector Autoregressive Moving Average Models PDF Download
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Author: George Athanasopoulos
Publisher:
ISBN:
Category : Autoregression (Statistics)
Languages : en
Pages : 470
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Book Description
Author: George Athanasopoulos
Publisher:
ISBN:
Category : Autoregression (Statistics)
Languages : en
Pages : 470
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Book Description
Author: Christian Kascha
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Christian Kascha
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 97
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Author: Dominik Bertsche
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Author: Robin Braun
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Author: Maximilian Podstawski
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Niels Haldrup
Publisher: OUP Oxford
ISBN: 0191669547
Category : Business & Economics
Languages : en
Pages : 393
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Book Description
This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Teräsvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, time-varying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semi-automatic general to specific model selection for nonlinear dynamic models, high-dimensional data analysis for parametric and semi-parametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Teräsvirta has had and will continue to have, on the profession.
Author: S. Burke
Publisher: Springer
ISBN: 0230005780
Category : Business & Economics
Languages : en
Pages : 253
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Book Description
Co-integration, equilibrium and equilibrium correction are key concepts in modern applications of econometrics to real world problems. This book provides direction and guidance to the now vast literature facing students and graduate economists. Econometric theory is linked to practical issues such as how to identify equilibrium relationships, how to deal with structural breaks associated with regime changes and what to do when variables are of different orders of integration.
Author: G. T. Wilson
Publisher:
ISBN:
Category :
Languages : en
Pages : 35
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Book Description
This paper reviews several different methods for identifying the orders of autoregressive-moving average models for time series data. The case is made that these have a common basis, and that a unified approach may be found in the analysis of a matrix G, defined to be the covariance matrix of forecast values. The estimation of this matrix is considered, emphasis being placed on the use of high order autoregression to approximate the predictor coefficients. Statistical procedures are proposed for analyzing G, and identifying the model orders. A simulation example and three sets of real data are used to illustrate the procedure, which appears to be very useful as a tool for order identification and preliminary model estimation. (Author).
Author: Gustavo Fruet Dias
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
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Book Description
We address the issue of modelling and forecasting macroeconomic variables using rich datasets by adopting the class of Vector Autoregressive Moving Average (VARMA) models. We overcome the estimation issue that arises with this class of models by implementing an iterative ordinary least squares (IOLS) estimator. We establish the consistency and asymptotic distribution of the estimator for weak and strong VARMA(p,q) models. Monte Carlo results show that IOLS is consistent and feasible for large systems, outperforming the MLE and other linear regression based efficient estimators under alternative scenarios. Our empirical application shows that VARMA models are feasible alternatives when forecasting with many predictors. We show that VARMA models outperform the AR(1), ARMA(1,1), Bayesian VAR, and factor models, considering different model dimensions.Supplement is available at: 'https://ssrn.com/abstract=2830838' https://ssrn.com/abstract=2830838.
