*The Data used to predict potential capital growth locations -to give investors confidence that a particular location is a sound investment - uses algorithms which are continuously fine tuned using Artificial Intelligence with the chief data scientist having patents in various fields of data science and data engineering.
The modelling approach adopted to create the capital growth predictions uses the following 7 steps:
1. Explore multiple variables in search of those that show a clear ‘demand’ or ‘supply’ relationship with residential property at the suburb or more focused level
2. Once key variables are identified, access data from multiple sources collecting as much raw data as possible
3. Clean, aggregate and transform data within the data model to ensure accuracy, stability and reliability of the future data outputs
4. Perform a monthly data run to produce suburb level predictions for both house and unit property types
5. Ongoing back-testing of predictions against actual performance to test reliability
6. Continued testing of new variables to improve the data model and future capital growth predictions
7. Introduce any new variable, if proven viable, to the overall data model to increase forecasting accuracy.
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