EViews - Introductory Econometrics Modeling

As mentioned in the course objective, the Eviews – Econometrics modelling course aims to provide quantitative/econometrics modelling skills typically/specifically in the Finance sector. Quantitative methods and predictive modelling concepts could be extensively used in understanding the financial market's movements, and studying tests and effects. The course picks theoretical and practical datasets for econometrics/quantitative/predictive analysis. Implementations are done using EViews software. Observations, interpretations, predictions and conclusions are explained then and there on the examples as we proceed through the training. The course also emphasizes the regression models, and AIMS to also cover Auto-Correlation, Co-Integration and ARCH (Auto Regressive Conditional Heteroscedasticity) models.

• Essential skillsets – Prior knowledge of Quantitative methods and MS Office, Paint.

• Desired skillsets — Understanding of Data Analysis and VBA toolpack in MS Excel will be useful.

The course works across multiple software packages such as Eviews, MS Office, PDF writers, and Paint. Furthermore, the course is distributed across 4 sub-courses, details of which are bulleted below, with a brief description.

• Course 1: Eviews and Its Application to Econometrics Modelling: This course aims to provide basic to intermediate skills on implementing Econometrics/Predictive modelling concepts using Eviews software. Whilst it's important to develop an understanding of econometrics/quantitative modelling concepts, it's equally important to be able to implement them using suitable software packages. This course fills the gap between understanding the concepts and implementing them practically.

• Course 2: Descriptive Statistics, Means, Standard Deviation and T-test – This course explains descriptive statistics concepts, which will act as building blocks to subsequent courses.

• Course 3: Correlation Techniques – Correlation techniques explain relationships across variables and are important in explaining the model fitment in regression courses.

• Course 4: Regression modelling — Regression modelling forms the core of the Predictive Modelling course. The core objective of this course is to provide skills in understanding the regression model and interpreting it for predictions. The associated parameters of the regression model will be interpreted and tested for significance, and the goodness of fit of the given regression model.

Course Objective:

This course aims to provide econometrics/quantitative/predictive modelling skills pertaining to Finance.