Time Series Data Analysis Using EViews

Time Series Data Analysis Using EViews

Author: I. Gusti Ngurah Agung

Publisher: John Wiley & Sons

Published: 2011-08-31

Total Pages: 502

ISBN-13: 1118176308

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Do you want to recognize the most suitable models for analysis of statistical data sets? This book provides a hands-on practical guide to using the most suitable models for analysis of statistical data sets using EViews - an interactive Windows-based computer software program for sophisticated data analysis, regression, and forecasting - to define and test statistical hypotheses. Rich in examples and with an emphasis on how to develop acceptable statistical models, Time Series Data Analysis Using EViews is a perfect complement to theoretical books presenting statistical or econometric models for time series data. The procedures introduced are easily extendible to cross-section data sets. The author: Provides step-by-step directions on how to apply EViews software to time series data analysis Offers guidance on how to develop and evaluate alternative empirical models, permitting the most appropriate to be selected without the need for computational formulae Examines a variety of times series models, including continuous growth, discontinuous growth, seemingly causal, regression, ARCH, and GARCH as well as a general form of nonlinear time series and nonparametric models Gives over 250 illustrative examples and notes based on the author's own empirical findings, allowing the advantages and limitations of each model to be understood Describes the theory behind the models in comprehensive appendices Provides supplementary information and data sets An essential tool for advanced undergraduate and graduate students taking finance or econometrics courses. Statistics, life sciences, and social science students, as well as applied researchers, will also find this book an invaluable resource.


Cross Section and Experimental Data Analysis Using EViews

Cross Section and Experimental Data Analysis Using EViews

Author: I. Gusti Ngurah Agung

Publisher: John Wiley & Sons

Published: 2011-02-15

Total Pages: 506

ISBN-13: 0470828455

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A practical guide to selecting and applying the most appropriate model for analysis of cross section data using EViews. "This book is a reflection of the vast experience and knowledge of the author. It is a useful reference for students and practitioners dealing with cross sectional data analysis ... The strength of the book lies in its wealth of material and well structured guidelines ..." Prof. Yohanes Eko Riyanto, Nanyang Technological University, Singapore "This is superb and brilliant. Prof. Agung has skilfully transformed his best experiences into new knowledge ... creating a new way of understanding data analysis." Dr. I Putu Gede Ary Suta, The Ary Suta Center, Jakarta Basic theoretical concepts of statistics as well as sampling methods are often misinterpreted by students and less experienced researchers. This book addresses this issue by providing a hands-on practical guide to conducting data analysis using EViews combined with a variety of illustrative models (and their extensions). Models having numerically dependent variables based on a cross-section data set (such as univariate, multivariate and nonlinear models as well as non-parametric regressions) are concentrated on. It is shown that a wide variety of hypotheses can easily be tested using EViews. Cross Section and Experimental Data Analysis Using EViews: Provides step-by-step directions on how to apply EViews to cross section data analysis - from multivariate analysis and nonlinear models to non-parametric regression Presents a method to test for all possible hypotheses based on each model Proposes a new method for data analysis based on a multifactorial design model Demonstrates that statistical summaries in the form of tabulations are invaluable inputs for strategic decision making Contains 200 examples with special notes and comments based on the author’s own empirical findings as well as over 400 illustrative outputs of regressions from EViews Techniques are illustrated through practical examples from real situations Comes with supplementary material, including work-files containing selected equation and system specifications that have been applied in the book This user-friendly introduction to EViews is ideal for Advanced undergraduate and graduate students taking finance, econometrics, population, or public policy courses, as well as applied policy researchers.


Introductory Econometrics for Finance

Introductory Econometrics for Finance

Author: Chris Brooks

Publisher: Cambridge University Press

Published: 2008-05-22

Total Pages: 752

ISBN-13: 1139472305

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This best-selling textbook addresses the need for an introduction to econometrics specifically written for finance students. Key features: • Thoroughly revised and updated, including two new chapters on panel data and limited dependent variable models • Problem-solving approach assumes no prior knowledge of econometrics emphasising intuition rather than formulae, giving students the skills and confidence to estimate and interpret models • Detailed examples and case studies from finance show students how techniques are applied in real research • Sample instructions and output from the popular computer package EViews enable students to implement models themselves and understand how to interpret results • Gives advice on planning and executing a project in empirical finance, preparing students for using econometrics in practice • Covers important modern topics such as time-series forecasting, volatility modelling, switching models and simulation methods • Thoroughly class-tested in leading finance schools. Bundle with EViews student version 6 available. Please contact us for more details.


Applied Econometrics

Applied Econometrics

Author: Chung-ki Min

Publisher: Routledge

Published: 2019-03-08

Total Pages: 242

ISBN-13: 0429656505

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Applied Econometrics: A Practical Guide is an extremely user-friendly and application-focused book on econometrics. Unlike many econometrics textbooks which are heavily theoretical on abstractions, this book is perfect for beginners and promises simplicity and practicality to the understanding of econometric models. Written in an easy-to-read manner, the book begins with hypothesis testing and moves forth to simple and multiple regression models. It also includes advanced topics: Endogeneity and Two-stage Least Squares Simultaneous Equations Models Panel Data Models Qualitative and Limited Dependent Variable Models Vector Autoregressive (VAR) Models Autocorrelation and ARCH/GARCH Models Unit Root and Cointegration The book also illustrates the use of computer software (EViews, SAS and R) for economic estimating and modeling. Its practical applications make the book an instrumental, go-to guide for solid foundation in the fundamentals of econometrics. In addition, this book includes excerpts from relevant articles published in top-tier academic journals. This integration of published articles helps the readers to understand how econometric models are applied to real-world use cases.


Teach Yourself Econometric Data Analysis with EViews

Teach Yourself Econometric Data Analysis with EViews

Author: Chukwuemeka Tiptop Okoro

Publisher:

Published: 2020-05-18

Total Pages: 250

ISBN-13:

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There is a large group of people in a variety of fields, including finance, economics, accounting, science, mathematics, engineering, statistics, and public policy who need to understand some basic concepts of time series analysis and forecasting. Analyzing time-series data and forecasting future values of a time series are among the most important problems that analysts face in many fields. But to Successfully analyze this time series data requires that the analyst interact with computer software because the techniques and algorithms are just not suitable to manual calculations.This book has been written with the aim of solving this problems by providing a step-by-step guide to economic and financial econometrics using EViews. It contains a brief overviews of the concepts of econometric models, and data analysis techniques followed by procedures of how they can be implemented in EViews. This book is written as a compendium for undergraduate and graduate students in economics, finance, statistics and accounting. It can also serve as a guide for researchers and practitioners who desire to use EViews for analyzing financial data. This book may be used as a textbook companion for post graduate level courses in time series analysis, empirical finance, statistics and financial econometrics. Since, many organizations can improve their effectiveness and business results by making better short-to-medium term forecasts, this book should be useful to a wide variety of professionals. Topics Covered with examples Include: Chapter 1: Introduction to EViews. Chapter 2: Descriptive Statistics and Preliminary Tests. Chapter 3: Running Regression Analysis in EViews. Chapter 4: Forecasting Using Regression Models. Chapter 5: Economic Forecasting using ARIMA Modelling. Chapter 6: Volatility Modeling: ARCH, GARCH and EGARCH Models. An Introduction to Financial Econometrics. Chapter 7: Vector Autoregressive (VAR) Model. An Introduction to Macroeconometrics. Chapter 8: Vector Error Correction Model (VECM). Chapter 9: Autoregressive Distributed Lag Model (ARDL). Chapter 10: Panel Data Analysis


Economic and Financial Modelling with EViews

Economic and Financial Modelling with EViews

Author: Abdulkader Aljandali

Publisher: Springer

Published: 2018-10-22

Total Pages: 293

ISBN-13: 3319929852

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This practical guide in Eviews is aimed at practitioners and students in business, economics, econometrics, and finance. It uses a step-by-step approach to equip readers with a toolkit that enables them to make the most of this widely used econometric analysis software. Statistical and econometrics concepts are explained visually with examples, problems, and solutions. Developed by economists, the Eviews statistical software package is used most commonly for time-series oriented econometric analysis. It allows users to quickly develop statistical relations from data and then use those relations to forecast future values of the data. The package provides convenient ways to enter or upload data series, create new series from existing ones, display and print series, carry out statistical analyses of relationships among series, and manipulate results and output. This highly hands-on resource includes more than 200 illustrative graphs and tables and tutorials throughout. Abdulkader Aljandali is Senior Lecturer at Coventry University in London. He is currently leading the Stochastic Finance Module taught as part of the Global Financial Trading MSc. His previously published work includes Exchange Rate Volatility in Emerging Markers, Quantitative Analysis, Multivariate Methods & Forecasting with IBM SPSS Statistics and Multivariate Methods and Forecasting with IBM® SPSS® Statistics. Dr Aljandali is an established member of the British Accounting and Finance Association and the Higher Education Academy. Motasam Tatahi is a specialist in the areas of Macroeconomics, Financial Economics, and Financial Econometrics at the European Business School, Regent’s University London, where he serves as Principal Lecturer and Dissertation Coordinator for the MSc in Global Banking and Finance at The European Business School-London.


Applied Regression Modeling

Applied Regression Modeling

Author: Iain Pardoe

Publisher: John Wiley & Sons

Published: 2013-01-07

Total Pages: 319

ISBN-13: 1118345045

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Praise for the First Edition "The attention to detail is impressive. The book is very well written and the author is extremely careful with his descriptions . . . the examples are wonderful." —The American Statistician Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science, and social science applications. The author utilizes a bounty of real-life examples, case studies, illustrations, and graphics to introduce readers to the world of regression analysis using various software packages, including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear and careful writing style, the book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, and Bayesian modeling. In addition, the Second Edition features clarification and expansion of challenging topics, such as: Transformations, indicator variables, and interaction Testing model assumptions Nonconstant variance Autocorrelation Variable selection methods Model building and graphical interpretation Throughout the book, datasets and examples have been updated and additional problems are included at the end of each chapter, allowing readers to test their comprehension of the presented material. In addition, a related website features the book's datasets, presentation slides, detailed statistical software instructions, and learning resources including additional problems and instructional videos. With an intuitive approach that is not heavy on mathematical detail, Applied Regression Modeling, Second Edition is an excellent book for courses on statistical regression analysis at the upper-undergraduate and graduate level. The book also serves as a valuable resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work.