Course Title: Business Forecasting Methods

Part A: Course Overview

Course Title: Business Forecasting Methods

Credit Points: 12.00

Terms

Course Code	Campus	Career	School	Learning Mode	Teaching Period(s)
ECON1069	City Campus	Undergraduate	625H Economics, Finance and Marketing	Face-to-Face	Sem 2 2006, Sem 2 2007, Sem 2 2008, Sem 2 2009, Sem 2 2010
ECON1186	City Campus	Postgraduate	625H Economics, Finance and Marketing	Face-to-Face	Sem 2 2006

Course Coordinator: Dr. Ashton De Silva

Course Coordinator Phone: +61 3 9925 1313

Course Coordinator Email: ashton.desilva@rmit.edu.au

Course Coordinator Location: 108.12

Pre-requisite Courses and Assumed Knowledge and Capabilities

ECON1030 Business Statistics 1 Or OMGT1117 Property Data Analysis

Course Description

The basic aim of this course is to introduce you to the Time Series methods and the elementary Econometric methods that are used by practitioners to obtain forecasts of important decision variables such as cash flows, earnings, interest rates, exchange rates, share prices and costs. You will be shown how to use the EViews package to evaluate these forecasts. The quantitative techniques that are discussed in this course include Naive methods, Smoothing techniques, the Box-Jenkins approach and basic Regression methods.

Objectives/Learning Outcomes/Capability Development

Capabilities

At the conclusion of this course, you should be able to:
1. Discuss the key factors which affect the success of forecasting procedures.
2. Use Basic Statistical Techniques and statistical Graphics to forecast values.
3. Understand the key concepts needed to use the Linear Regression model when forecasting.
4. Use EViews to perform the key operations needed to obtain Descriptive Statistics and Regression Analysis.
5. Model and Forecast the different possible Trend components of a set of values.
6. Use the World Wide Web to obtain information on forecasting methods and useful data to be used when forecasting
7. Find different sets of Smoothed or Average values to be used when forecasting.
8. Model and Forecast the Seasonal component of a set of values.
9. Model the different types of Cyclical behaviour observed in different sets of values.
10. Understand and use the Box-Jenkins or ARMA Procedure.
11. Combine the Trend, Seasonal and Cyclical components to produce a more accurate forecast of a set of values.

Overview of Learning Activities

To achieve the objectives listed above this course reqires you to participate in various learning activities. These include the following:
attendance at and notetaking at scheduled lectures
rading of and notetaking from prescribed and recommended text books and other references
completion of demonstration lecture questions

Overview of Learning Resources

Lecture notes

Text book

DLS

Overview of Assessment

Assignments

End-of-semester examination paper