ETF5231 - Business forecasting
6 points, SCA Band 0 (NATIONAL PRIORITY), 0.125 EFTSL
Postgraduate Faculty of Business and Economics
Leader(s): Dr Ann Maharaj
Caulfield First semester 2009 (Day)
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.
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.
Within semester assessment: 40%
Examination (2 hours): 60%
Two 1-hour lectures and one 1-hour laboratory/tutorial per week