This is the second post in the multi-part blog series. In this post we will deep dive into best practice of “suburb investability assessment” within an LGA boundary. The author is using an assumed persona of a DYI investor researching the Camden Council Area property market.
Considering the input and output concerns presented in part 1, we have established that the main ranking table is very informative and useful. It is, however, somewhat static as it does not highlight the full historical ‘behaviour’ of relevant property submarkets.
What can bring ‘liveliness’ to the key metrics we report on, is the ability to benchmark one suburb against the others within the boundaries of a Council Area. This can be achieved based on the same filter criteria demonstrated in part 1. However, in this instance the filters will be applied to list of suburbs within Camden LGA (Local Government Area) as opposed to the full list of Council Areas or Suburbs on the main page.
Aside from zooming further into the submarket data, decision to classify some suburbs as more ‘investable’ than others can be simplified when presented with the historical visualisation of suburb typical price and median rent. Visualisation of price/rent trend and sales/rental volume always creates additional context for the investor.
Table of Contents
Second-level submarket search on the LGA page
The LGA page for Camden Council Area provides statistics on the many submarkets (suburbs). This view is not available on the table provided at the first level search on the homepage.
The first thing that we see when we click through to an LGA page from the homepage is the ‘ranking table’. This table contains statistics for all suburbs in Camden Council.
There are a couple of ways to sort through the information provided to choose the most “ivestable” suburb pertaining to input and output concerns discussed in the previous post:
- You can interact with the data in the table by way of filters provided above the ranking table.
- You can also sort by way of different columns in the ranking table.
For example, you can sort by using the confidence metric by simply clicking on the word ‘Confidence’. The important thing to note here is that one can combine the sorting ‘criteria’. You can sort by ‘confidence’ but also by ‘yield’ option using parameters in your search based on your investment strategy.
Although sorting is a simple feature, it enables a powerful and intuitive means to quickly compare submarkets within a Local Government Areas.
Infer “investability” through visual assessment of historical trends
The best way to explain what ‘historical behaviour of the area’ means is to highlight why having this information is useful in the first instance. To determine the ‘investability’ of a particular suburb, I need to know whether changes in the typical value of property in the relevant market had:
- exorbitant growth and decline(s) or
- steady, stabilised and persistent growth
Essentially, the aim is to determine the investment stability (‘investability’) of the suburb. Sharp changes in prices typically highlight speculation and/or price changes resulting from inorganic demand surges (i.e. strong but short-lived). This is evident in some mining towns that grow and shrink alongside the mining economy.
Such locations might present opportunities for ‘flippers’ or risk tolerant developers, who will dispose of the property in the short-term. However, they do not provide a sound backing for a long-term property investor looking to build a solid portfolio.
The ‘investability’ of an area is determined by what economists refer to as ‘market fundamentals’. The fundamental metrics subsume the balance of supply and demand variables such as population, unemployment, building approvals, stock on market, migration, vacancy rate etc.
Generally speaking, an area with good market fundamentals would not exhibit sharp, sporadic changes in typical values of its properties. It would rather see more of a sustained and continuous growth.
Let’s explore the visualisation of price and rent trend via the graphs on the LGA dashboard.
Assessing suburb “investability” via capital growth & rent forecast charts
Once we select the ‘forecast’ tab, the first result we retrieve is a graph of the Council’s (LGA) ‘performance’. The chart highlights both historical as well as forecasted price movements in typical price and median rent.
The historical data goes back as far as there is data of statistical significance to be collected. We decide to explore the Gledswood Hills submarket and retrieve it by selecting it from the Suburb dropdown.
You can also hover over the graph(s) which yields additional information. For example, the customers can retrieve number of sales/rentals for a particular period in time.
As Gledswood Hills is a newly developed area, the historical data goes back to mostly 2014. The darker shadings of both graphs present historical data up to the current quarter. The lighter shading of the graph represents the forecasted values. The green and grey bars (y-axis) represent the number of sales/rentals data.
Having this information is useful when deciding on the initial investment outlay. As rents will increase at a slower rate, it behooves the investor not to overstretch funds for the sake of anticipated capital growth. Furthermore, the gross and net yield of the area will pace. This can have adverse effects on highly leveraged portfolios or those exclusively focusing on capital growth.
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Implications of price trend for suburb “investability” assessment
Now that we have visualised the historical price movements, we can see that Gledswood Hills, although a relatively young area, has not experienced large oscillations in its typical price which qualifies for our purposes.
We can see that the development of this area did not eventuate from the need to support finite industries, but as a result of solid economical fundamentals which will likely position the area as a suitable long term investment. This will be more evident when we move onto discussing the ‘Growth Rate Cycle’ tab in part 3.
In the next blog post we will reveal a new way to visualise historical prices, which brings further insight into the price cyclicity of the relevant property submarket.
Continue to part 3 >>>