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Essays On Alternative Methods Of Identification And Estimation Of Vector Autoregressive Moving Average Models
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Book Synopsis Essays on Alternative Methods of Identification and Estimation of Vector Autoregressive Moving Average Models by : George Athanasopoulos
Download or read book Essays on Alternative Methods of Identification and Estimation of Vector Autoregressive Moving Average Models written by George Athanasopoulos and published by . This book was released on 2005 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Comparison of Estimation Methods for Vector Autoregressive Moving-average Models by : Christian Kascha
Download or read book A Comparison of Estimation Methods for Vector Autoregressive Moving-average Models written by Christian Kascha and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Three Essays in Time Series Econometrics by : Christian Kascha
Download or read book Three Essays in Time Series Econometrics written by Christian Kascha and published by . This book was released on 2007 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Three Essays on Identification and Dimension Reduction in Vector Autoregressive Models by : Dominik Bertsche
Download or read book Three Essays on Identification and Dimension Reduction in Vector Autoregressive Models written by Dominik Bertsche and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Three Essays on Identification in Structural Vector Autoregressive Models by : Robin Braun
Download or read book Three Essays on Identification in Structural Vector Autoregressive Models written by Robin Braun and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Unconventional Identification in Vector Autoregressive Models: Empirical Essays on Credit, Risk and Uncertainty by : Maximilian Podstawski
Download or read book Unconventional Identification in Vector Autoregressive Models: Empirical Essays on Credit, Risk and Uncertainty written by Maximilian Podstawski and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Essays in Nonlinear Time Series Econometrics by : Niels Haldrup
Download or read book Essays in Nonlinear Time Series Econometrics written by Niels Haldrup and published by OUP Oxford. This book was released on 2014-06-26 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Modelling Non-Stationary Economic Time Series by : S. Burke
Download or read book Modelling Non-Stationary Economic Time Series written by S. Burke and published by Springer. This book was released on 2005-06-14 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis A Unified Approach to ARMA (Autoregressive-Moving Average) Model Identification and Preliminary Estimation by : G. T. Wilson
Download or read book A Unified Approach to ARMA (Autoregressive-Moving Average) Model Identification and Preliminary Estimation written by G. T. Wilson and published by . This book was released on 1983 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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).
Book Synopsis Estimation and Forecasting in Vector Autoregressive Moving Average Models for Rich Datasets by : Gustavo Fruet Dias
Download or read book Estimation and Forecasting in Vector Autoregressive Moving Average Models for Rich Datasets written by Gustavo Fruet Dias and published by . This book was released on 2017 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Testing the Fit of a Vector Autoregressive Moving Average Model by : Efstathios Paparoditis
Download or read book Testing the Fit of a Vector Autoregressive Moving Average Model written by Efstathios Paparoditis and published by . This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new procedure for testing the fit of multivariate time series model is proposed. The method evaluates in a certain way the closeness of the sample spectral density matrix of the observed process to the spectral density matrix of the parametric model postulated under the null and uses for this purpose nonparametric estimation techniques. The asymptotic distribution of the test statistic is established and an alternative, bootstrap-based method is developed in order to estimate more accurately this distribution under the null hypothesis. Goodness-of-fit diagnostics useful in understanding the test results and identifying sources of model inadequacy are introduced. The applicability of the testing procedure and its capability to detect lacks of fit is demonstrated by means of some real data examples.
Book Synopsis Maximum Likelihood Estimation of the Autoregressive Coefficients and Moving Average Covariances of Vector Autoregressive Moving Average Models by : Fereydoon Ahrabi
Download or read book Maximum Likelihood Estimation of the Autoregressive Coefficients and Moving Average Covariances of Vector Autoregressive Moving Average Models written by Fereydoon Ahrabi and published by . This book was released on 1979 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this paper is to derive asymptotically efficient estimates for the autoregressive matrix coefficients and moving average covariance matrices of the vector autoregressive moving average (VARMA) models in both time and frequency domains. To do this we shall apply the Newton-Raphson and scoring methods to the maximum likelihood equations derived from modified likelihood functions under the Gaussian Assumption.
Book Synopsis Some Aspects of Estimation for Vector Time Series Models by : Moses Olufemi Salau
Download or read book Some Aspects of Estimation for Vector Time Series Models written by Moses Olufemi Salau and published by . This book was released on 1993 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Maximum Likelihood Estimation for Vector Autoregressive Moving Average Models by : STANFORD UNIV CALIF DEPT OF STATISTICS.
Download or read book Maximum Likelihood Estimation for Vector Autoregressive Moving Average Models written by STANFORD UNIV CALIF DEPT OF STATISTICS. and published by . This book was released on 1978 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: The vector autoregressive moving average model is a multivariate stationary stochastic process where the unobservable multivariate process consists of independently identically distributed random vectors. The coefficient matrices and the covariance matrix are to be estimated from an observed sequence. Under the assumption of normality the method of maximum likelihood is applied to likelihoods suitably modified for techniques in the frequency and time domains. Newton-Raphson and scoring iterative methods are presented.
Book Synopsis IDENTIFICATION OF PERIODIC AUTOREGRESSIVE MOVING AVERAGE MODELS. by :
Download or read book IDENTIFICATION OF PERIODIC AUTOREGRESSIVE MOVING AVERAGE MODELS. written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, identification of periodically varying orders of univariate Periodic Autoregressive Moving-Average (PARMA) processes is mainly studied. The identification of the varying orders of PARMA process is carried out by generalizing the well-known Box-Jenkins techniques to a seasonwise manner. The identification of pure periodic moving-average (PMA) and pure periodic autoregressive (PAR) models are considered only. For PARMA model identification, the Periodic Autocorrelation Function (PeACF) and Periodic Partial Autocorrelation Function (PePACF), which play the same role as their ARMA counterparts, are employed. For parameter estimation, which is considered only to refine model identification, the conditional least squares estimation (LSE) method is used which is applicable to PAR models. Estimation becomes very complicated, difficult and may give unsatisfactory results when a moving-average (MA) component exists in the model. On account of overcoming this difficulty, seasons following PMA processes are tried to be modeled as PAR processes with reasonable orders in order to employ LSE. Diagnostic checking, through residuals of the fitted model, is also performed stating its reasons and methods. The last part of the study demonstrates application of identification techniques through analysis of two seasonal hydrologic time series, which consist of average monthly streamflows. For this purpose, computer programs were developed specially for PARMA model identification.
Book Synopsis Supplement To 'Estimation and Forecasting in Vector Autoregressive Moving Average Models for Rich Datasets' by : Gustavo Fruet Dias
Download or read book Supplement To 'Estimation and Forecasting in Vector Autoregressive Moving Average Models for Rich Datasets' written by Gustavo Fruet Dias and published by . This book was released on 2017 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: The online Supplement presents the proof the auxiliary Lemmas 1-6, the entire set of tables with results from the Monte Carlo and the empirical studies, and further discussion on selected topics.Full paper is available at: 'https://ssrn.com/abstract=2707176' https://ssrn.com/abstract=2707176.
Book Synopsis Three Essays on Long Memory Tests for Persistence in Volatility and Structural Vector Autoregression Modeling of Real Exchange Rates by : Osman Kubilay Gursel
Download or read book Three Essays on Long Memory Tests for Persistence in Volatility and Structural Vector Autoregression Modeling of Real Exchange Rates written by Osman Kubilay Gursel and published by . This book was released on 2002 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the first chapter the performance of two of the long memory tests, the Modified Rescaled Range Test and Geweke and Porter-Hudak Test for persistence in small samples is examined using Monte-Carlo methods. Some possible candidates for persistence in volatility are Autoregressive Conditional Heteroskedasticity (ARCH), Markov Regime Switching ARCH, and long memory. The long memory series are simulated through a Semi-Markov process with Pareto waiting times and lognormal realizations. The persistence in volatility arising from transition waiting probabilities for a Markov Regime Switching process, and from the tail index of the waiting time distribution for the Semi-Markov process is established through simulations with different parameter values. There is evidence that persistence in a regime switching process is closely linked to state transition probabilities and waiting times. The second chapter re-examines what structural vector autoregressive modeling of real exchange rates with differenced variables tells us about interesting macroeconomic questions. Using quarterly data from G-7 countries in the post Bretton-Woods period, the evidence suggests that shock identification is not an easy process in a Blanchard and Quah decomposition framework with long run restrictions. Confidence bands do not find significant impulse responses and the signs of the estimated impulse responses are very sensitive to the lag selection criteria adopted. Possible cointegration effects seem to be the main driving force behind the unsatisfactory performance of the structural approach. Chapter three extends the structural vector autoregression model by incorporating cointegration effects. Using the method of Warne (1993), in a simple four-variable vector autoregression (VAR) characterized by cointegration, the response of real exchange rates to various economic shocks are investigated with economically plausible long-run restrictions. The long-run relations and driving stochastic trends of the real exchange rate between United States and other G-7 countries are analyzed in a structural cointegrated framework. Productivity shocks depreciate the real exchange rate and the perverse sign effect of supply shock is corrected for most countries in the sample. More significant impulse responses are observed through confidence intervals. The structural vector error correction decompositions are also found to be not robust to estimating with different lag lengths owing to additional cointegration effects.
