Offered
Caulfield First semester 2008 (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 co-integration. 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
ETX3231