Predictive Analytics in Business
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.
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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)
You must have successfully completed the following subject(s) before starting this subject:
No additional requirements
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.
Please Note: If it’s your first time studying a Curtin University subject you’ll need to complete their compulsory ‘Academic Integrity Program’. It only takes two hours to complete online, and provides you with vital information about studying with Curtin University. The Academic Integrity Program is compulsory, so if it’s not completed your subject grades will be withheld.
Find out more about the Academic Integrity module.
- Project Proposal (20%)
- Assignment (30%)
- Project (50%)
Current study term: 29 Aug 21 to 28 Nov 21
Textbooks are not required.