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Econometric Modelling With Time Series

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Econometric Modelling With Time Series

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Author : Vance Martin
language : en
Publisher: Cambridge University Press
Release Date : 2012-12-28

Econometric Modelling With Time Series written by Vance Martin and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-28 with Business & Economics categories.

This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalised method of moments estimation, nonparametric estimation and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.

The Econometric Analysis Of Time Series

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Author : Andrew C. Harvey
language : en
Publisher: MIT Press
Release Date : 1990

The Econometric Analysis Of Time Series written by Andrew C. Harvey and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Business & Economics categories.

The Econometric Analysis of Time Series focuses on the statistical aspects of model building, with an emphasis on providing an understanding of the main ideas and concepts in econometrics rather than presenting a series of rigorous proofs.

Econometric Modelling With Time Series

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Author : Vance Martin
language : en
Publisher: Cambridge University Press
Release Date : 2013

"Maximum likelihood estimation is a general method for estimating the parameters of econometric models from observed data. The principle of maximum likelihood plays a central role in the exposition of this book, since a number of estimators used in econometrics can be derived within this framework. Examples include ordinary least squares, generalized least squares and full-information maximum likelihood. In deriving the maximum likelihood estimator, a key concept is the joint probability density function (pdf) of the observed random variables, yt. Maximum likelihood estimation requires that the following conditions are satisfied. (1) The form of the joint pdf of yt is known. (2) The specification of the moments of the joint pdf are known. (3) The joint pdf can be evaluated for all values of the parameters, 9. Parts ONE and TWO of this book deal with models in which all these conditions are satisfied. Part THREE investigates models in which these conditions are not satisfied and considers four important cases. First, if the distribution of yt is misspecified, resulting in both conditions 1 and 2 being violated, estimation is by quasi-maximum likelihood (Chapter 9). Second, if condition 1 is not satisfied, a generalized method of moments estimator (Chapter 10) is required. Third, if condition 2 is not satisfied, estimation relies on nonparametric methods (Chapter 11). Fourth, if condition 3 is violated, simulation-based estimation methods are used (Chapter 12). 1.2 Motivating Examples To highlight the role of probability distributions in maximum likelihood estimation, this section emphasizes the link between observed sample data and 4 The Maximum Likelihood Principle the probability distribution from which they are drawn"-- publisher.

Modeling Financial Time Series With S Plus

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Author : Eric Zivot
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-10

Modeling Financial Time Series With S Plus written by Eric Zivot and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-10 with Business & Economics categories.

This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. It is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This edition covers S+FinMetrics 2.0 and includes new chapters.

Modelling Trends And Cycles In Economic Time Series

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Author : Terence C. Mills
language : en
Publisher: Springer Nature
Release Date : 2021-07-29

Modelling Trends And Cycles In Economic Time Series written by Terence C. Mills and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-29 with Business & Economics categories.

Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Several developments in econometrics then led to an overhaul of the techniques used to extract trends and cycles from time series. In this second edition, Terence Mills expands on the research in the area of trends and cycles over the last (almost) two decades, to highlight to students and researchers the variety of techniques and the considerations that underpin their choice for modelling trends and cycles.

The Econometric Modelling Of Financial Time Series

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Author : Terence C. Mills
language : en
Publisher: Cambridge University Press
Release Date : 2008-03-20

The Econometric Modelling Of Financial Time Series written by Terence C. Mills and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-20 with Business & Economics categories.

Terence Mills' best-selling graduate textbook provides detailed coverage of research techniques and findings relating to the empirical analysis of financial markets. In its previous editions it has become required reading for many graduate courses on the econometrics of financial modelling. This third edition, co-authored with Raphael Markellos, contains a wealth of material reflecting the developments of the last decade. Particular attention is paid to the wide range of nonlinear models that are used to analyse financial data observed at high frequencies and to the long memory characteristics found in financial time series. The central material on unit root processes and the modelling of trends and structural breaks has been substantially expanded into a chapter of its own. There is also an extended discussion of the treatment of volatility, accompanied by a new chapter on nonlinearity and its testing.

Econometric Modelling With Time Series

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Author : Vance Martin
language : en
Publisher: Cambridge University Press
Release Date : 2012-12-28

This book provides a general framework for specifying, estimating, and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation, and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.

The Econometric Modelling Of Financial Time Series

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Author : Terence C. Mills
language : en
Publisher: Cambridge University Press
Release Date : 1999-08-26

Econometric Modeling With Matlab Multivariate Time Series Models

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Author : B. Noriega
language : en
Publisher: Independently Published
Release Date : 2019-03-06

Econometric Modeling With Matlab Multivariate Time Series Models written by B. Noriega and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-06 with Mathematics categories.

Econometrics Toolbox provides functions for modeling economic data. You can select and estimate economic models for simulation and forecasting. For time series modeling and analysis, the toolbox includes univariate Bayesian linear regression, univariate ARIMAX/GARCH composite models with several GARCH variants, multivariate VARX models, and cointegration analysis. It also provides methods for modeling economic systems using state-space models and for estimating using the Kalman filte. You can use a variety of diagnostics for model selection, including hypothesis tests, unit root, stationarity, and structural change.The more important topics in this book are the next: -"Vector Autoregression (VAR) Models" -"Multivariate Time Series Data Structures" -"Multivariate Time Series Model Creation" -"VAR Model Estimation" -"Convert VARMA Model to VAR Model" -"Fit VAR Model of CPI and Unemployment Rate" -"Fit VAR Model to Simulated Data" -"VAR Model Forecasting, Simulation, and Analysis" -"Generate VAR Model Impulse Responses" -"Compare Generalized and Orthogonalized Impulse Response Functions"-"Forecast VAR Model"-"Forecast VAR Model Using Monte Carlo Simulation" -"Forecast VAR Model Conditional Responses"-"Multivariate Time Series Models with Regression Terms" -"Implement Seemingly Unrelated Regression" -"Estimate Capital Asset Pricing Model Using SUR" -"Simulate Responses of Estimated VARX Model"-"Simulate VAR Model Conditional Responses" -"Simulate Responses Using filter -"VAR Model Case Study" -"Cointegration and Error Correction Analysis" -"Determine Cointegration Rank of VEC Model" -"Identifying Single Cointegrating Relations"-"Test for Cointegration Using the Engle-Granger Test" -"Estimate VEC Model Parameters Using egcitest"-"VEC Model Monte Carlo Forecasts" -"Generate VEC Model Impulse Responses" -"Identifying Multiple Cointegrating Relations" -"Test for Cointegration Using the Johansen Test" -"Estimate VEC Model Parameters Using jcitest" -"Compare Approaches to Cointegration Analysis" -"Testing Cointegrating Vectors and Adjustment Speeds" -"Test Cointegrating Vectors" -"Test Adjustment Speeds"

Nonlinear Econometric Modeling In Time Series

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Author : William A. Barnett
language : en
Publisher: Cambridge University Press
Release Date : 2000-05-22

Nonlinear Econometric Modeling In Time Series written by William A. Barnett and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-05-22 with Business & Economics categories.

This book presents some of the more recent developments in nonlinear time series, including Bayesian analysis and cointegration tests.

Econometric Modelling With Time Series

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