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Economic and Financial Modelling wit...
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Economic and Financial Modelling with EViews = A Guide for Students and Professionals /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Economic and Financial Modelling with EViews/ by Abdulkader Aljandali, Motasam Tatahi.
Reminder of title:
A Guide for Students and Professionals /
Author:
Aljandali, Abdulkader.
other author:
Tatahi, Motasam.
Description:
XVII, 284 p. 277 illus., 238 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Statistics for Business, Management, Economics, Finance, Insurance. -
Online resource:
https://doi.org/10.1007/978-3-319-92985-9
ISBN:
9783319929859
Economic and Financial Modelling with EViews = A Guide for Students and Professionals /
Aljandali, Abdulkader.
Economic and Financial Modelling with EViews
A Guide for Students and Professionals /[electronic resource] :by Abdulkader Aljandali, Motasam Tatahi. - 1st ed. 2018. - XVII, 284 p. 277 illus., 238 illus. in color.online resource. - Statistics and Econometrics for Finance,2199-093X. - Statistics and Econometrics for Finance,.
Chapter 1: Introduction to eviews -- Chapter 2: A guideline for running regression -- Chapter 3: Time series analysis -- Chapter 4: Time series modelling -- Chapter 5: Further properties of time series -- Chapter 6: Economic forecasting -- Chapter 7: The box-jenkins methodology: arima forecasting -- Chapter 8: Modelling volatility in finance and economics - arch, garch and egrach models -- Chapter 9: Limited dependent variable models -- Chapter 10: Vector autorgressive models -- Chapter 11: Panel data analysis -- Chapter 12: Captial asset pricing model (capm) -- Chapter 13: Event studies.
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 econometric 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 Economies, Quantitative Analysis and 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. .
ISBN: 9783319929859
Standard No.: 10.1007/978-3-319-92985-9doiSubjects--Topical Terms:
1211158
Statistics for Business, Management, Economics, Finance, Insurance.
LC Class. No.: QA276-280
Dewey Class. No.: 330.015195
Economic and Financial Modelling with EViews = A Guide for Students and Professionals /
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Chapter 1: Introduction to eviews -- Chapter 2: A guideline for running regression -- Chapter 3: Time series analysis -- Chapter 4: Time series modelling -- Chapter 5: Further properties of time series -- Chapter 6: Economic forecasting -- Chapter 7: The box-jenkins methodology: arima forecasting -- Chapter 8: Modelling volatility in finance and economics - arch, garch and egrach models -- Chapter 9: Limited dependent variable models -- Chapter 10: Vector autorgressive models -- Chapter 11: Panel data analysis -- Chapter 12: Captial asset pricing model (capm) -- Chapter 13: Event studies.
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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 econometric 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 Economies, Quantitative Analysis and 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. .
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