HtAG Data Dictionary
HtAG Analytics revolutionises decision-making for investors & real estate professionals by offering a comprehensive Software as a Service, designed to streamline market selection for property investment briefs.
Our platform not only simplifies the discovery of optimal investment opportunities through pinpoint market matching but also enriches subscribers with the knowledge to become data-driven market experts.
This data guide covers the most important metrics that you should be taking into account when researching the property market.
If you are new to data-driven property investment, we encourage you to follow the hyperlinks on this page. Most metrics have a dedicated post which explains the rationale behind the data with guiding points and examples.
A real estate investor who uses the key performance indicators on this page will be able to make more informed decisions about which markets have better prospects for increased returns and create more wealth for themselves in the long run.
Essential Metrics
All essential metrics are reported independently per dwelling type i.e. houses or units.
Typical Price is HtAG’s solution to the shortcomings of the Median Price metric which results in a more accurate representation of home values and price trends at the suburb level.
Rental prices are based on a rolling year median and reported independently per week for both houses and units.
Similar to price, the current rental value does not hold significant weight in strategic decision-making. Greater emphasis should be placed on factors such as rental increases, yield, and vacancy rates, both in terms of their current figures and observed trends.
Number of property sales recorded online during the calendar month. Resets every month.
The sales volume for the current month typically holds limited significance in forecasting returns, whether they are short-term or long-term, in both sales and rental markets. It mainly reflects the current sales volume momentum.
For a more reliable growth indicator, consider the sales-to-dwelling ratio, which offers insights over a longer period and accounts for market size, allowing for more precise relative analysis.
A number of properties are listed for rent online during the calendar month. Resets every month.
The rental volume for the current month typically holds limited significance in forecasting returns, whether they are short-term or long-term, in rental markets. It mainly reflects the current rental volume momentum.
For a more reliable rental market growth indicator, consider the rentals-to-dwelling ratio, which offers insights over a longer period and accounts for market size, allowing for more precise relative analysis.
Δ (Delta) is the percent difference of the current price for sales or rentals to the referent value X periods ago. X can be 1M (month), 1Q (quarter), 1Y (year), 3Y (years) etc.
Gross Rental Yield is the value you generate from an investment property, which is represented as a percentage. Derived from Typical Price and Median Rent metrics. Calculated for the current month.
Capital Growth expressed as a CG Low/High range is the percent difference between the future typical price and its current value. Estimated per annum based on 2 year forecast produced by HtAG ML model.
Return on Investment is a performance measure used to evaluate the efficiency of an investment. Calculated as a sum of Gross Rental Yield + Capital Growth metrics above.
Projected per annum increase of median rent. Estimated per annum based on 2-year forecast produced by HtAG Statistical model.
Deviation of short-term price growth from the long-term trend. Higher values indicate higher market volatility. Uses the mean absolute percentage error (MAPE) formula to measure market volatility and estimate future price growth channels. Calculated and averaged periodically when forecasts are back-tested.
Confidence is a metric that indicates the accuracy of data. It is calculated based on the average monthly sales per suburb.
Relative Composite Score™
When trying to understand the complexities of the real estate market, it can be helpful to create a singular score that represents a collection of different metrics. This not only reduces potential information overload but also simplifies comparisons between different markets.
Relative Composite Score was designed to automate and simplify the analysis of real estate markets via a proprietary algorithm created by HtAG Analytics. All RCS metrics are reported independently per dwelling type i.e. houses or units.
Lower Risk RCS™ is calculated based on more than 80 metrics where higher weighting is assigned to environmental, market and data risk indicators. Higher values indicate lower risk.
Capital Growth RCS™ is calculated based on more than 80 metrics where higher weighting is assigned to indicators that suggest a strong future growth potential such as long-term price projections, IRSAD, renter-to-owner ratio etc. Capital Growth RCS™ is specifically designed to identify locations with strong long-term capital growth potential, typically spanning 5 years or more.
Cashflow RCS™ is calculated based on more than 80 metrics where higher weighting is assigned to indicative gross yield, vacancy rate, rental price trend etc.
The overall Relative Composite Score is an average of Capital Growth, Cashflow and Lower Risk scores listed above.
Strategy Guidance: The Overall Relative Composite Score (RCS) is a straightforward average that combines indicators of capital growth, cash flow, and risk.
While this score offers a balanced overview of a market’s potential, it is not recommended for use when targeting markets for specific strategies due to its generalization across three distinct domains. However, it serves as a useful tool for identifying markets that may offer balanced return opportunities with relatively low long-term investment risks.
Fundamental Metrics
The Unfavourable / Neutral / Opportune ranges are static with the exception of GRC.
| Description | Unfavourable | Neutral | Opportune |
|---|---|---|---|
| IRSAD stands for Index of Relative Socio-economic Advantage and Disadvantage and is published by ABS. The index defines people’s access to material and social resources, and their ability to participate in society. For details see SEIFA Technical Paper. Reported jointly for houses and units. | 1-2 | 3-8 | 9-10 |
| Description | Unfavourable | Neutral | Opportune |
|---|---|---|---|
| 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% |
| Description | Unfavourable | Neutral | Opportune |
|---|---|---|---|
| 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% |
| Description | Unfavourable | Neutral | Opportune |
|---|---|---|---|
| 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% |
The “Years to Own” metric represents the estimated duration required to fully own a property, factoring in variables such as current interest rates, median family income, and typical property prices in the area. This calculation is based on the assumption of a standard 30-year mortgage. A value exceeding 30 years could be an indicator of decreased affordability in the area.
Strategy Guidance: This macro-metric is paramount for ensuring sustained demand from both owner-occupiers and investors in the long and short term. Affordable property is key to identifying suburbs likely to deliver above-average long-term returns. Consequently, the ranking order is always reversed, with more affordable properties receiving higher decile rankings. This approach prioritizes affordability as a critical factor for future growth potential.
| Description | Unfavourable | Neutral | Opportune |
|---|---|---|---|
| Growth Rate Cycle indicates projected growth or decline in Year on Year price change. Values are listed in order of precedence i.e. (+)Increasing is better than (+)Trough, (-)Increasing is better than (-)Trough. However the precedence under the Neutral and Opportune ranges may change depending on your investment strategy. Reported independently per dwelling type i.e. houses or units. | -Decreasing -Peak | +Decreasing -Increasing -Trough | +Increasing +Trough +Peak |
Supply Metrics
The Low Supply / Balanced / High Supply ranges are dynamic and are subject to change. Defined for the market conditions as of the current year.
| Description | Low Supply | Balanced | High Supply |
|---|---|---|---|
| Stock on Market is the number of unsold listings on market. Reported independently per dwelling type i.e. houses or units. | N/A | N/A | N/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% |
| Description | Low Supply | Balanced | High Supply |
|---|---|---|---|
| Inventory (also known as Months of Supply) is cumulative SoM divided by the average number of sales per month over a year. 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. | <2.1 | 2.1-4.5 | >4.5 |
| Description | Low Supply | Balanced | High 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/A | N/A | N/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% |
| Description | Low Supply | Balanced | High 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. | >10.4 | 6.4-10.4 | <6.4 |
Demand Metrics
The Low Demand / Balanced / High Demand ranges are dynamic and are subject to change. Defined for the market conditions as of the current year.
| Description | Low Demand | Balanced | High Demand |
|---|---|---|---|
| Days on Market is the median number of days ‘for sale’ listings remain active on the web. Reported independently per dwelling type i.e. houses or units. Our methodology, highlighted for its uniqueness and accuracy, surpasses standard practices. For a thorough understanding of how HtAG stands out, we encourage you to explore our detailed article on DoM. | >90 | 35-90 | 0-35 |
| Description | Low Demand | Balanced | High 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% |
| Description | Low Demand | Balanced | High Demand |
|---|---|---|---|
| Vacancy Rate – see this article 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/A | N/A | N/A |
| Description | Low Demand | Balanced | High 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%. | >45 | 35-45 | <35 |
| Description | Low Demand | Balanced | High 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. | 0-2 | 3-5 | 6-10 |
Buy SI
The Buy Search Index reflects a level of interest in an area but maintains a few degrees of separation from actual purchases. Consequently, it does not have a direct relationship with growth and ranks lower in the demand hierarchy compared to metrics like Days on Market and vacancy rates.
The significance of this metric is typically no greater than 4, and the decile ordering is generally natural, with higher search index values receiving higher decile rankings in Dex.
Buy SI LS
The long-term slope of the Buy Search Index, while indicative of improving (or declining) search trends, holds a similarly reduced significance as the current Buy Search Index value. Within the hierarchy of search indices, short-term trends are more significant than current values.
Consequently, the significance of the long-term slope typically does not exceed a score of 5. The decile ordering is usually natural in Dex, with higher search index values corresponding to higher decile rankings.
Buy SI SS
The short-term slope in the Buy Search Index holds greater significance in identifying sentiment shifts compared to the long-term slope and current index values. Identifying an upward trend in the short-term slope suggests growing interest in the area.
However, as this demand indicator remains somewhat distanced from actual purchase activity, it typically does not receive a multiplier higher than 5. The decile ordering in Dex is generally natural, with higher search index values assigned higher decile rankings.
Rent SI
The Rent Search Index reflects a level of interest in an area but maintains a few degrees of separation from actual purchases. Consequently, it does not have a direct relationship with growth and ranks lower in the demand hierarchy compared to metrics like Days on Market and vacancy rates.
The significance of this metric is typically no greater than 5, and the decile ordering is generally natural, with higher search index values receiving higher decile rankings in DEx.
Rent SI LS
The long-term slope of the Rent Search Index, while indicative of improving (or declining) search trends, holds a similarly reduced significance as the current Buy Search Index value. Within the hierarchy of search indices, short-term trends are more significant than current values.
Consequently, the significance of the long-term slope typically does not exceed a score of 5. The decile ordering is usually natural, with higher search index values corresponding to higher decile rankings.
Rent SI SS
The short-term slope in the Rent Search Index holds greater significance in identifying sentiment shifts compared to the long-term slope and current index values. Identifying an upward trend in the short-term slope suggests growing interest in the area. However, as this demand indicator remains somewhat distanced from actual purchase activity, it typically does not receive a multiplier higher than 5.
The Dex decile ordering is generally natural, with higher search index values assigned higher decile rankings.
| Description | Low Demand | Balanced | High 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% |
Risk Indices
This section delves into several key risk indices, arming investors and real estate professionals with the insights necessary to navigate the intricacies of regional economic and environmental considerations.
The Flood Risk Index is a comprehensive assessment tool that integrates both riverine and surface water flood hazards by calculating the ratio of high risk properties in a given area. The ratio is then used to create a rank score on a scale of 0 to a 100.
Higher values indicate a lower relative level of risk. Areas with scores below 50 are considered high risk. We recommend to always perform property level due-diligence for floods even in suburbs that have scores as high as 100.
Extreme exposure to flooding can increase holding costs and dampen growth. Suburbs that have a higher exposure to negative environmental effects pose higher risk levels to long-term growth and stability.
The Bushfire Risk Index assesses the vulnerability of a region by determining the percentage of properties situated within bushfire-prone zones. Higher values represent a decreased risk (in relative terms). Areas with scores below 50 are considered high risk.
We recommend to always perform property level due-diligence for bushfires even in suburbs that have scores as high as 100.
Extreme exposure to bushfires can increase holding costs and dampen growth. Suburbs that have a higher exposure to negative environmental effects pose higher risk levels to long-term growth and stability.
The index is derived by employing a modified version of the Shannon-Wiener Index algorithm to analyse employment data. This methodology quantifies the diversity of employment sectors within a region. Moreover, occupational categories commonly associated with elevated socio-economic standings receive increased weightings.
The higher the score the better. Always pair this index with MAD (Mining Agriculture Dominance).
Economic Diversification Index is very important for long-term growth and stability. Suburbs that have a higher Diversification Index pose lower risk levels to long-term growth and stability.
The Mining and Agriculture Dominance Index, abbreviated as MAD Index, quantifies the relative influence of the mining and agriculture sectors within a specific locale — be it a suburb or a Local Government Area (LGA).
Higher value on the MAD Index indicates a lesser prevalence of either industry in the area. Always pair this index with EDI (Economic Diversity Index).
Mining and Agriculture Dominance Index is very important for long-term growth and stability. Suburbs that have a higher MAD Index pose lower risk levels to long-term growth and stability.
Other Metrics
The following advanced metrics possess a versatile nature that can provide greater insights into a property market, enhancing your understanding and decision-making process.
Adult population in LGA or suburb recorded during the most recent census.
Please note that the population data corresponds to the adult population recorded as of the latest census. This means that the reported figure may differ from the total population, which includes individuals aged 15 years and under.
Since the adult population plays a pivotal role in driving the economy, we place significant emphasis on this particular figure.
Number of residential dwellings in the area estimated based on the Australian address database.
| Description | Poor | Good | Extraordinary |
|---|---|---|---|
| The Average School rank is a significant metric that reflects the quality of education in the area. This composite metric is derived from a combination of average NAPLAN scores and ACARA rating, and is measured on a scale of 1 to 100, where 100 represents the highest rank possible. | <40 | 40-70 | >70 |
The “Non-Residential Building Approvals Per Capita” dollar value signifies the total monetary amount that was authorized for non-residential construction projects in the past 12 months divided by the adult population in the area. This metric acts as an approximation of local and state government investments in infrastructure development.
Annual Sales to Dwellings Ratio represents the cumulative number of property transactions within the area over the preceding 12-month period divided by total dwellings.
Annual Rentals to Dwellings Ratio represents the cumulative number of rentals within the area over the preceding 12-month period divided by total dwellings.
Distance to the nearest General Post Office typically located in the CBD of a state/territory capital.
For detailed guidance and interpretation of GRC Index, GRC Minima, GPD, GSP as well as LS and SS metrics please join our Mastermind Community.
Frequently Asked Questions.
Are you new to our website and have a question? Here are the top questions our new customers commonly ask.
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.
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.
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.
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.
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.
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.
