Breakdown of Days on Market (DoM) and Discounting Metrics

Navigating the real estate market requires a deep understanding of key indicators that shape investment decisions.

Two such pivotal metrics are Days on Market (DoM) and Vendor Discounting.

These statistical tools serve as an essential bridge between market trends and savvy investment strategies.

A shortened DoM typically signals strong market demand, whilst escalated Vendor Discounting might indicate a market nearing saturation.

This article delves into the core definitions, statistical analyses, and the intricate relationship between DoM and Vendor Discounting.

It uncovers how these measurements operate within the property market, how they influence buying and selling behaviour, and importantly, how they might shape your strategies as an investor.

By understanding the interconnected relationship between these two metrics, you’ll be well-positioned to make effective property decisions, whether it’s identifying market trends, gauging demand, or planning targeted investment strategies.

DoM (Days on Market)

So what is DoM and why is this metric important?

We explain Days on Market thoroughly in this short youtube video.

Let’s deep dive into the exploration of DoM and Discounting data.

By the end of this analysis, you’ll realise that these 2 metrics are closely related.

DoM is the difference in days between the date of property first being listed for sale and the actual day of sale. Shorter DoM indicates strong demand for the property.

A smaller value indicates a more favourable short-term market outlook.

As can be seen on the chart below, majority of suburbs in our dataset have DoM in the 25-75 day range. Based on that we can conclude that:

• DoM of 35 days or less is representative of seller’s markets experiencing strong demand from buyers
• Range of 35-90 days is representative of balanced markets where demand generally meets supply
• 90 days or more is representative of a buyer’s market

DoM is calculated as a median of all transactions per month and per suburb/locality. This calculation is based on properties listed and reported as sold online.

A shorter DoM means a higher demand, which can be an advantage for sellers and a potential disadvantage for buyers.

Variables such as the location, type of property (houses, units, or land), and the market situation can sway this figure.

HtAG’s Days on Market Methodology

Our sophisticated methodology ensures that HtAG’s supply and demand metrics, specifically Days on Market, provide the most relevant, up-to-date, and comprehensive market insights, empowering our clients to make well-informed decisions on our platform.

1. We report median DOM for sales recorded in the past month (using rolling month period) i.e. not sales in the past 12 months like other providers.
2. We include sales without listed price and auction sales – in the end a sale is a sale and if a property is sold we measure how long it stayed on the market.
3. DOM is calculated using the first listed date and the date the property is marked as sold by real estate agents.
4. DOM is reported independently for houses and units – Houses are free standing houses (excl. townhouses & villas). Units are apartments, studios, flats, units (excl. unit blocks).
5. We apply outlier detection and remove listings that are anomalies i.e. old houses listed for sale as demolish and rebuild, land listed for sale as houses etc.

This approach insures that we have the most current value per month for this important demand metric with wider coverage for all types of sales.

In addition using monthly values enables us to better gauge trends for this metric as it is not smoothed out by rolling year medians.

Lastly, for improved stability and comparability in our reporting, we also present current period values as a three-month rolling average.

This approach helps to moderate short-term fluctuations inherent in the DoM metric, providing a more consistent and easily interpretable dataset for our users to analyse.

Vendor Discounting

Vendor Discounting showcases the percentage by which the vendor marks down the original advertised price.

It is calculated from the same transactions as DoM, represented as a percentage decrease in the advertised price.

Here is the formula:

Oddly enough, negative percentages suggest that a property has been sold for more than the advertised price.

Such instances are rare and signify an exceedingly strong market demand.

The chart below suggests that a discount in the range of 2-5% is very common among the vendors in the suburbs on our list.

Similar to DoM, the Discounting metric is calculated as an average discount of all known on-market sales in the suburb/locality.

Is there a relationship between DoM and Discounting?

Yes, these two metrics are moderately correlated with a value of 0.31.

However, vendors often maintain their advertised prices or offer minimal discounts, even when properties linger on the market past the average DoM.

Let’s now explore the correlation between DoM and Discounting for 3 of the property types in our dataset: houses, units and land.

We intentionally excluded townhouses from this analysis as they account for a very small portion of sales recorded.

Property Types & DoM Distribution

The chart below shows both the distribution (histogram) for each of the metrics as well as correlation plot per each property type.

Let’s first look at the distributions of Days on Market, Discounting, Sales data for all suburbs on our list.

In simpler terms, we’re diving deep to understand how Days on Market, Discounting, and Number of Sales relate to each other for different property types, namely houses, units, and land.

If you look at the graph, you’ll see three lines, each representing a property type.

• The blue line (houses) shows that when a house stays on the market for longer, the price tends to come down a bit more. This connection is strongest for houses.
• The orange line (units) line has a less clear-cut relationship. This means that even if a unit stays on the market for long, the pricing discount isn’t as predictable.
• The green line (land) is even lower, indicating that land often stays on the market quite a bit longer and the discounts given are not as deep as for houses or units.

Generally speaking, the longer a property type tends to stay on the market, the more likely there will be a discount, though this is most pronounced for houses.

Gauge Demand Based on DoM & Discounting

One of the most critical applications of understanding the Days on Market (DoM) and the Vendor Discounting metrics is in identifying what is often referred to as a seller’s market and a buyer’s market.

1. A Seller’s Market – A seller’s market is often characterised by a low DoM. Strong demand manifests in properties selling quickly, often with multiple offers being made soon after a listing goes live. In these circumstances, the amount of discount offered by vendors is often minimal, as the high demand allows sellers to command prices close to or even over their advertised price.
2. A Buyer’s Market – On the other hand, a buyer’s market features a longer DoM, signifying that properties typically remain listed for sale for extended periods. This can be due to a variety of factors, such as reduced demand, economic downturn or perhaps an oversupply of similar properties. In this scenario, Vendor Discounting rises as sellers may reduce prices to attract potential buyers.

Let’s delve more into the difference between property types, houses, units, and land, and how each behaves in the real estate market.

Houses

Houses often exhibit strong correlations between DoM and Discounting.

A low DoM exhibits a strong demand for houses. In a seller’s market, houses get sold swiftly, and there’s hardly any discount offered by sellers.

However, in a buyer’s market, houses may stay listed for longer, and larger discounts may be given to attract potential buyers.

Units

The relationship between DoM and Discounting for units isn’t as strong as houses, suggesting other influential factors at play.

Units might exhibit characteristics of a seller’s market with low DoM, and yet may still have noticeable discounting, perhaps due to regular fluctuations in the demand for units.

Land

Land sales present a unique scenario taken that they typically have longer DoM and less Discounting compared to houses and units.

There are several possible reasons for this.

Land purchases often involve substantially higher initial costs and long-term planning, thus deterring instant purchase decisions.

The longer time frames allow for detailed deliberation, hence a longer DoM.

As far as discounting is concerned, land is often perceived as a finite resource with inherent value, and therefore sellers might not feel the pressure to provide significant discounts as it may retain or even increase its value over time.

Summary

To conclude, understanding DoM and Discounting metrics for various property types is a key aspect of making informed investment decisions in the Australian real estate market.

By carefully monitoring these metrics, real estate investors can gauge market trends, adjust strategies, optimise timing for buy or sell decisions, and maximise their investment returns.

Ultimately, investing in the real estate market is about understanding the demand and supply dynamics, economic indicators, property type attributes and local market conditions.

While DoM and Vendor Discounting provide useful insights, they should be analysed as part of a broader set of investment tools to ensure sound decision making.

From a strategic point of view, investors might choose to invest in property types with lower DoM and minimum Vendor Discounting during sellers’ market conditions, while taking advantage of properties that stay longer on market with considerable discounts during a buyer’s market.

Our analysis elucidates the nuanced relationship between Days on Market and Discounting, both vital indicators in providing insights into the market’s condition.

However, exceptions and variations always exist.

I hope you enjoyed reading this short but insightful analysis. I certainly had a lot of fun deriving meaning from the new HtAG dataset.

Whereas the data paints one story, there are always exceptions and deviations from the norm.

I invite you to share your insights via the comment form below.