12-Factor Growth Scoring Model

The Growth Engine scores Australian suburbs on their potential for future capital growth using a quantitative model built on four weighted categories and twelve individual factors. Each suburb receives a composite score from 0-100, translated to a letter grade.

The model is designed for standalone houses priced under $1M, targeting suburbs with strong fundamentals for buyers agents and investors seeking capital appreciation over a 3-7 year horizon.

Scoring Categories & Weights

Category	Weight	Factors	Rationale
Demand Signals	30%	Days on Market, Stock Pressure, Auction Activity, Search Interest	Leading indicators of buyer intent. Faster sales and tighter listings signal genuine demand exceeding supply.
Supply Pressure	25%	Vacancy Rate, Rental Yield, Building Approvals	Supply constraints are the strongest predictor of price growth. Low vacancy + high yield + limited new builds = upward price pressure.
Structural Fundamentals	25%	Infrastructure Score, Population Growth, SEIFA Decile	Long-term drivers of desirability. Infrastructure investment, population inflow, and socioeconomic composition predict sustained growth.
Cycle & Affordability	20%	Growth Gap (vs. adjacent suburbs), Price-to-Income Ratio	Markets grow fastest when affordable relative to their neighbours and when past growth hasn't already peaked.

Scoring Methodology

For each factor, the raw value is converted to a Z-score against the national distribution of all tracked suburbs. The Z-score is then mapped to a percentile (0-100) using the standard normal cumulative distribution function.

Factors where "lower is better" (vacancy rate, days on market, crime index) are inverted so that a low raw value produces a high percentile score.

Category scores are the weighted average of their constituent factor percentiles. The overall score is the weighted sum of category scores.

Cycle Adjustment Multiplier

To avoid recommending suburbs that have already peaked, the model applies a cycle multiplier based on recent 1-year price growth:

1yr Growth	Multiplier	Rationale
> 20%	0.85	Overheated — high reversion risk
10-20%	0.95	Strong — moderate reversion risk
0-10%	1.00	Healthy — no adjustment needed
< 0%	1.10	Recovery — potential upside from mean reversion

Grade Scale

Data Sources

Suburb-level metrics are assembled from public and commercial data feeds including CoreLogic RP Data (median prices, days on market, growth rates), SQM Research (vacancy rates, stock on market, rental yields), Australian Bureau of Statistics (population estimates, SEIFA indices, building approvals), and Infrastructure Australia project databases.

PPI Hotspotting Property Performance Indicators (PPI) — suburb-level market trend classifications (Rising, Consistent, Recovery, Plateau, Declining) sourced from Hotspotting's quarterly survey of sales transaction data across Australian suburbs. Used to contextualise Growth Engine scores with independent market cycle analysis.

PT PropTrack Market Analytics API — suburb-level median sale prices, days on market, median rents, rental yields, total/new for-sale listings, sale volumes, and inventory months. Sourced directly from REA Group's PropTrack data platform via API. Provides 24-month price history sparklines and supply/demand metrics across all 190 tracked suburbs.

HT HTAG Dex Scores — proprietary Capital Growth, Cashflow, and Lower Risk indices from HTAG's Dex and GeoDex modules. Includes suburb-level inventory months, ROI projections, IRSAD socioeconomic index, and rent-to-own ratio analysis. Used to cross-validate Growth Engine grades with independent algorithmic assessments.

Research Foundation

The weighting structure draws on empirical findings from:

• RBA Research Discussion Paper 2018-03 — vacancy rates and supply constraints as leading indicators of house price movements in Australian capital cities.

• Erol & Unal (2022) — infrastructure investment and population growth as structural drivers of long-run property price appreciation.

• DSR (Demand-to-Supply Ratio) methodology — the foundational framework for combining demand and supply signals into a single metric, widely used in Australian property analytics.

• CoreLogic Hedonic Home Value Index — the industry-standard methodology for measuring Australian property market conditions.

Limitations

This model uses historical and current data to identify suburbs with favourable growth conditions. It is not a price forecast. Property markets are influenced by macroeconomic factors (interest rates, credit availability, regulation) that operate outside the scope of suburb-level scoring. The model should be used as one input within a broader investment assessment process.