Understanding Stock on Market (SoM) for Real Estate Investment

Looking to penetrate the Australian real estate market? It’s crucial to get a grasp on the role of the ‘Stock on Market’ (SoM) metric. Providing a rapidly accessible view of supply, this tool tallies the number of properties currently up for sale.

However, leaning too heavily on these reported numbers can miss out on the wider context that different geographical realities lend to the property market. After all, suburbs come in varying sizes, leading to a natural disparity in total stock availability.

These metrics provide further value to property investors in that they can now perform in-depth assessment of supply levels in any given market. In this article we explore SoM and SoM% metrics and explain how to perform suburb shortlisting based on pre-established thresholds.

What is Stock on Market (SoM)?

Stock on Market is probably one of the most straightforward metrics requiring little explanation. It is simply the number of properties currently listed for sale. Whilst SoM provides a quick supply snapshot, the reported numbers are not put into the geo-demographical context of relevant property market. Because some suburbs are larger than others, they will naturally have more total theoretical stock available.

Stock on Market Percentage or SoM% brings the different size markets to one common denominator by apportioning the SoM to the total number of dwellings within the area. Therefore SoM% is a more precise metric to go by when bench-marking different markets one to another.

So what’s a good SoM and SoM%? In order to answer this question let’s explore the data distributions of these 2 metrics in the current market.

Low, Balanced & High Supply Ranges for SoM

It’s important to highlight that the distributions presented in this article are ‘point in time’ and are reflective of the current Australian property market conditions. These distributions change and shift as markets go through their usual cycles. HtAG updates the ranges based on the latest data on the Data Dictionary page.

To distil this complex data, we place SoM values into categories (horizontal axis) and plot the volume of suburbs in each category range (vertical axis).

Our data illustrates that numerous suburbs boast no more than 10 active online ‘for sale’ listings for both houses and units. Conversely, a few suburbs simultaneously host as many as 60 active listings.

We produced the histograms in this article by assigning SoM values to bins (horisontal axis) and plotting the number of suburbs falling into the bin range on the vertical axis.

Looking at the distribution of SoM we can see that a large portion of suburbs have no more than 10 active online ‘for sale’ listings for both houses and units. We can also see that only a few suburbs have as many as 60 active listings.

Generally speaking supply balances out at and around the mid-point i.e. between 25% and 75% quantiles. Values below 25% or above 75% quantiles (green lines) are more likely to be reflective of low and high supply conditions respectively.

In this instance, SoM values under 5 are reflective of “low supply” markets for houses.

Difference Between SoM and SoM%

Given that SoM of 5 can mean different things in a suburb with 100 dwellings as opposed to a suburb with 1,000 dwellings, we need to benchmark the actual number of listings against total stock.

To provide a universal measure, we present the ‘Stock on Market Percentage’ (SoM%). For a more accurate insight into the market, this metric takes the SoM and relates it to the number of dwellings in a particular area. SoM% levels the playing field when comparing dissimilar markets, ensuring your benchmarks are precisely positioned.

SoM% is calculated by dividing SoM by the total number of house or unit dwellings in the area. Total number of units/houses is calculated based on the Australian address database.

So, how can we identify preferable SoM% values? Let’s cast a light on the data distributions of these two crucial metrics in the contemporary market.

In contrast to SoM, units have a smoother SoM% distribution curve compared to that of houses. This means that ranges for units can be somewhat wider than for houses. However they are still in the same ballpark.

Both units and houses are more likely to exhibit low supply conditions (relative) at SoM% under 0.5% in this environment.

Differences in SoM Reporting – Unsold vs All Listings

It’s important to note that our method of reporting the Stock on Market (SoM) may differ from other service providers, and this could influence potential considerations for property investors. We quantify SoM as the number of unsold property listings that remain at the end of the month, presenting a snapshot of the market at a specific point in time.

This contrasts with some other providers, who report SoM as all properties listed for sale over a one-month period – this gives an overall viewpoint of activity in the market throughout that month, but may not accurately represent the actual remaining unsold properties. Therefore, it is essential to understand these differences when comparing SoM figures across various sources.

Using the end-month unsold listings data provides a clear insight into where the market stands at a particular month-end, offering an indicator of market absorption rates.

If unsold stock carries over into the new month, it points toward either low buyer demand, high property prices, or a combination of both. As such, our method of SoM calculation offers a useful barometer to gauge the health of the property market.

Remember, a lower end-month SoM could potentially indicate a sellers’ market where demand outpaces supply, leading to upward pressure on property prices. A higher SoM, on the other hand, might suggest a buyers’ market with greater selection and potential for negotiating favourable purchase terms.

Tracking our end-month SoM figures can help investors to identify variances and trends over time, offering vital cues on shifts in the market. This nuanced analysis facilitates more strategic investment planning and risk mitigation, benefiting both novice and seasoned property investors in Australia.

Conclusion

SoM and SoM% reflect relative supply conditions in a property market i.e. council area or suburb. By comparing SoM reported for suburbs within your research scope, you should be able to identify markets with low and high supply based on a predefined range.

You are likely to find better deals in suburbs offering higher SoM/SoM% if you are a buyer. On the other hand, if you are a seller, lower SoM/SoM% are great indicators for little competition in the market from other vendors.

Be cautious of markets with over-extended supply reporting SoM% above 2%.

It will probably be challenging finding a property in markets with high competition from other buyers reporting SoM% under 0.25%. This is assuming there is a high enough demand to match the supply.

Just remember: the Stock on Market (SoM) metric shouldn’t be employed as a standalone tool. It should always be interpreted alongside other supply and demand metrics to get a robust overview of the market dynamics.

Staying informed and interpreting these metrics accurately can be the determining factor between secure property investment and risky ventures.

So, whether you’re a seasoned real estate investor or just starting out, understanding SoM and SoM% can help inform your decisions and keep your property portfolio on the path to success.