Postgraduate - UnitETF5231 - Business forecasting

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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.

Outcomes

The learning goals associated with this unit are to:

1. identify the basic tools of forecasting and define the basic time series analysis techniques
2. describe the decomposition techniques, exponential smoothing forecasting techniques and Box-Jenkins method of forecasting
3. 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
4. differentiate between decomposition methods, exponential smoothing methods and autoregressive methods of forecasting
5. analyse time series in the business environment using the appropriate methods and interpret computer output.

Assessment

Within semester assessment: 40%
Examination (2 hours): 60%

Chief examiner(s)

Associate Professor Elizabeth Maharaj

Contact hours

3 hours per week

Prerequisites

Students must be enrolled in course codes 3816 or 3822 or must have passed ETX2121, ETF9121, ETX2111, ETF2100, ETF9100 or MBA9007.

Prohibitions

ETX3231