Postgraduate - UnitETF5231 - Business forecasting

This unit entry is for students who completed this unit in 2013 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

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6 points, SCA Band 2, 0.125 EFTSL

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Level	Postgraduate
Faculty	Faculty of Business and Economics
Organisational Unit	Department of Econometrics and Business Statistics
Offered	Caulfield First semester 2013 (Day)
Coordinator(s)	Associate Professor Ann Maharaj

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:

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: 60%

Chief examiner(s)

Associate Professor Ann Maharaj

Contact hours

3 hours per week

Prerequisites

Students must be enrolled in course codes 3816 or 3822 or must have passed ETX2111, ETX2121, ETF2100, ETF9100, ETF9121, ETF9300 or MBA9007.

Prohibitions

ETX3231