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HtAG Data Dictionary

Essential Metrics

Relative Composite Score™

Fundamental Metrics

Supply Metrics

Demand Metrics

Other Metrics

Essential Metrics

Relative Composite Score™

Fundamental Metrics

DescriptionUnfavourableNeutralOpportune
Renter to Owner Ratio is the proportion of Renter households to the Owner Occupier or Mortgagee Households. The higher the number, the more renters there are relative to owner occupiers. Reported jointly for houses and units.>45%15-45%<15%
DescriptionUnfavourableNeutralOpportune
Unit to House Ratio is the proportion of total unit dwellings to that of houses in the area. Calculated by apportioning the number of units sold in the last 2 years to that of houses. The higher the number, the more units there are relative to houses. Reported jointly for houses and units.>50%10-50%<10%
DescriptionUnfavourableNeutralOpportune
Unit to House Value Ratio is the proportion of Typical Price of units to that of houses. The higher the percentage, the closer unit prices are to house prices. Only use this metric if you’re intending to purchase a unit. Reported for units only.>70%30-70%<30%
DescriptionUnfavourableNeutralOpportune
Growth Rate Cycle indicates projected growth or decline in Year on Year price change. Values are listed in order of significance i.e. (+)Increasing is better than (+)Trough, (-)Increasing is better than (-)Trough. Reported independently per dwelling type i.e. houses or units.-Decreasing
-Peak
+Decreasing
-Increasing
-Trough
+Increasing
+Trough
+Peak

Supply Metrics

DescriptionLow SupplyBalancedHigh Supply
Stock on Market is the number of unsold listings on market. Reported independently per dwelling type i.e. houses or units.N/AN/AN/A
Stock On Market Percentage is the ratio of SoM to the total number of dwellings in the area. A number of dwellings is calculated based on the Australian address database. Reported independently per dwelling type i.e. houses or units.<0.4%0.4-1.3%>1.3%
DescriptionLow SupplyBalancedHigh Supply
Inventory (also known as Months of Supply) is the average number of sales per month over a year divided by SoM. Used to define how absorbent the property market is of the new listings and measured in months. Reported independently per dwelling type i.e. houses or units.<2.12.1-4.5>4.5
DescriptionLow SupplyBalancedHigh Supply
Building Approvals is the number of new residential builds approved for construction, sourced from the ABS monthly dataset. Transformed from Statistical Area Level 2 to Suburb and Localities level for suburb reports. Reported independently per dwelling type i.e. houses or units.N/AN/AN/A
BA Ratio is the proportion of newly approved residential buildings over the past 12 months relative to total dwellings in the area. Reported independently per dwelling type i.e. houses or units.<0.3%0% or 0.3%-2%>2%
DescriptionLow SupplyBalancedHigh Supply
Hold Period is calculated by comparing and averaging all properties’ sold dates to their previous sold dates. “Tightly held” markets have higher Hold Periods, measured in years. In contrast to other monthly metrics this data is curated as an yearly timeseries. Reported independently per dwelling type i.e. houses or units. >10.46.4-10.4<6.4

Demand Metrics

DescriptionLow DemandBalancedHigh Demand
Days on Market. Average number of days ‘for sale’ listings remain active on the web. Measured in Days. Reported independently per dwelling type i.e. houses or units.>9035-900-35
DescriptionLow DemandBalancedHigh Demand
Discounting is the typical discount given by property vendors when selling a property. Reported independently per dwelling type i.e. houses or units.>4%0-4%<0%
DescriptionLow DemandBalancedHigh Demand
Vacancy Rate – see this blog post for a detailed explanation. There are instances where the Vacancy Rate cannot be calculated and is presented as -1.00%. Reported jointly for houses and units.>3.5%1-3.5%<1%
Vacancies is the average number of rental listings that are advertised online for more than 21 days. Reported jointly for houses and units.N/AN/AN/A
DescriptionLow DemandBalancedHigh Demand
Days on Rental Market. Average number of days ‘for rent’ listings remain active on the web. Measured in Days. Reported jointly for houses and units. Only use this metric when Vacancy Rate is -1.00%.>4535-45<35
DescriptionLow DemandBalancedHigh Demand
Buy & Rent Search Index is the ratio of online Buy / Rent searches to the state or city average. Value of 5 signifies that searches are at state/city average. Reported independently per dwelling type i.e. houses or units.0-23-56-10
DescriptionLow DemandBalancedHigh Demand
Auction Clearance Rates is the percentage of auctions resulting in a sale. Reported jointly for houses and units.<50%0% or 50-70%>70%

Other Metrics

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Frequently Asked Questions.

Are you new to our website and have a question? Here are the top questions our new customers commonly ask.

How do I get the HtAG Market Insights data?

1. Download a report from the HtAG Store.
2. Unzip the downloaded file and open the excel file within it.
3. You will then need to apply number filters to columns based on the ranges defined on this page or rely on provided colour coding.

Note that percent column filter values should be typed in as decimal points i.e. 3% will be “less than” or “more than” 0.03.

How do I shortlist suburbs based on supply and demand metric ranges?

The starting point should be to shortlist suburbs by filtering out Unfavourable, Low Demand and High Supply markets. The resulting list is then up to you to work through by applying additional filters based on property market metrics of your choice, whilst also gauging the potential Capital Growth and ROI based on provided data.

The more metrics fall into the Favourable, High Demand, Low Supply bands for a particular market, the more likely it is that Capital Growth will be towards the high range of the forecast. Be mindful that Neutral/Balanced markets frequently provide great outlooks and should not be discounted from research.

How did you establish the High / Balanced / Low and the Unfavourable / Neutral / Opportune ranges?

The ranges are determined by data distribution for every metric with 25th and 75th quantiles serving as cut offs between the 3 bands. Note that the data distribution is reflective of the current market conditions. Whereas fundamental metrics such as R|O Ratio have a constant distribution and ranges, Demand and Supply ranges are subject to change. Given that the ranges are established based on data for the past 3 months, they can migrate up or down as new data is collected between data releases.

Why is the HtAG reported metric value different from another provider i.e. SQM?

When comparing the data from two or more data providers it is always important to ensure that the providers use the same data curation method. If the method is different, then the property market metric values will most likely also be different.

For example, differences in the HtAG Vacancy Rate and that reported by SQM can be explained by different reporting period. HtAG reports it for the rolling month, whereas SQM reports it for the fixed month period.

Why did a metric value increas or decrease since the last data release?

Most metrics are known to fluctuate at the suburb level quite notably between data releases. For example, a change in Vacancy Rate from 2.4% to 2.0% is not significant. This fluctuation is not because the rates are changing, but because of the sparsity in the underlying data, which results in data noise between updates. That’s why the rates should always be ball-parked against a wide enough range.

Why did the Capital Growth and Total ROI values change since the last data release?

As HtAG projections are based on a forecast algorithm, which caries a degree of uncertainty, the CG (Capital Growth) values should be treated as an estimate of the general trend in the rate of growth and not as an exact percentage value. Note that changes of up to plus or minus 3% in CG and all other property market metrics are common between data releases. Changes in low and very low confidence suburbs can be higher than 3%. This is due to the underlying data sparsity at the suburb level.

Although changes are common between data releases, we find that fluctuations in the reported data even out over time. This is another reason why the values should be treated as ballpark ranges and not exact figures.

To learn more, visit our FAQ page for a detailed list of questions and answers.