ETF5231 - Business forecasting
6 points, SCA Band 0 (NATIONAL PRIORITY), 0.125 EFTSL
Postgraduate Faculty of Business and Economics
Leader(s): Dr Ann Maharaj
Offered
Caulfield First semester 2009 (Day)
Synopsis
Review of basic time series analysis techniques. Moving averages and exponential smoothing forecasting methods. Box-Jenkins method of forecasting. Comparison of forecasting techniques. Introduction to time series regression, dynamic models and cointegration. Applications to time series from accounting, economics, banking, finance and management areas. Use of Excel and SPSS.
Objectives
The learning goals associated with this unit are to:
- identify the basic tools of forecasting and define the basic time series analysis techniques
- describe the decomposition techniques, exponential smoothing forecasting techniques and Box-Jenkins method of forecasting
- compare the forecasts of real economic, business and financial time series by decomposition techniques and exponential smoothing techniques using Excel and Box Jenkins method using SPSS
- differentiate between decomposition methods, exponential smoothing methods and autoregressive methods of forecasting
- analyse time series in the business environment using the appropriate methods and interpret computer output.
Assessment
Within semester assessment: 40%
Examination (2 hours): 60%
Contact hours
Two 1-hour lectures and one 1-hour laboratory/tutorial per week
Prerequisites
Students must be enrolled in course codes 3816 or 3822 or must have passed ETX2121, ETX2111 or MBA9007
Prohibitions
13 October 2017
19 December 2024