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Predictive Analytics in Business
Postgraduate | CUR-PA520 | 2021
Course information for 2021 intake
Harness analytics to predict and forecast inflation, interest, plus stock and commodity prices. Gain skills to consider a range of variables. Use models including Vector Autogressive Moving Average, Vector Error Correction and more.
- Study method
- 100% online
- Assessments
- 100% online
- Entry requirements
- Part of a degree
- Duration
- 13 weeks
HECS-HELP and FEE-HELP available
Predictive Analytics in Business
About this subject
At the completion of this subject students will be able to:
- explain the nature of prediction and forecasting in the business context
- explain the difficulties in analysing and forecasting non-stationary variables
- analyse non-stationary variables by applying appropriate data analytic techniques
- formulate appropriate empirical models to predict economic and financial variables
- Analysing and forecasting non-stationary variables
- Model time-varying variance
- Vector Autoregressive Moving Average (VARMA) models
- Vector Error Correction (VECM) models
- Volatility models
- Using models to predict and forecast economic and financial variables (such as inflation, interest rates, stock prices and commodity prices)
The subject has two objectives: firstly, it focuses on analysing and forecasting non-stationary variables where elementary techniques are not appropriate. Secondly, it introduces techniques to model time-varying variance for purposes of modelling risk of financial assets. In order to achieve these, this subject introduces several time series models including Vector Autoregressive Moving Average (VARMA) models, Vector Error Correction (VECM) models and volatility models for predicting and forecast economic and financial variables, such as inflation, interest rates, stock prices and commodity prices.
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- Project Proposal (20%)
- Assignment (30%)
- Project (50%)
For textbook details check your university's handbook, website or learning management system (LMS).
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Entry requirements
To enrol in this subject, you must be admitted into a degree.
Prior study
You must have successfully completed the following subject(s) before starting this subject:
Additional requirements
No additional requirements
Study load
- 0.125 EFTSL
- This is in the range of 10 to 12 hours of study each week.
Equivalent full time study load (EFTSL) is one way to calculate your study load. One (1.0) EFTSL is equivalent to a full-time study load for one year.
Find out more information on Commonwealth Loans to understand what this means to your eligibility for financial support.