Economic and Financial Modelling with EViews : A Guide for Students and Professionals 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 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