This is the second post in the 4-part blog series that deep dives into best practice of property market research using the HtAG platform. The author is using an assumed persona of a DYI investor researching the Camden Council, NSW property market. If you have not yet read the first part, click here.
Considering the input and output concerns presented in part 1, it can be said that the main ranking table is very informative and useful, however, somewhat static as it does not highlight historical ‘behaviour’ of relevant property markets in question.
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 based on the filter criteria defined by the user. However, decision to settle on a particular suburb can be swayed when presented with the historical price movements of the suburb, which creates further context for the forecasted metrics presented so far.
Back to the fundamentals
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 investment grade of the particular location, I would want to know whether changes in the median value of property in the Council have been characterised with:
- exorbitant growth and decline(s) or
- steady, stabilised and persistent growth
Essentially, the aim is to determine the investment stability of the location. Sharp changes in median value typically highlight speculation and/or price changes resulting from inorganic demand surges (i.e. strong but short-lived) as is evident in some mining towns that grow and shrink alongside the mining economy. Such locations might present opportunities for ‘flippers’, or maybe even developers who will dispose of the property in the medium- to short-term timeframe, but do not provide a sound backing for a long-term investor who is looking to have a solid portfolio.
The investment stability of an area is determined by what economists refer to as ‘market fundamentals’ which subsumes 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 median values of its properties but would rather see more of a sustained and continuous growth.
Another thing that is of interest to our DYI investor is determining whether some suburbs are of better investment quality compared to other suburbs in the council area we are researching.
LGA page and the second-level search
What is good about HtAG’s service is that market fundamentals can be ascertained from the historical data which is available at the second search level (i.e. within the LGA boundaries) thus avoiding the need to collate pertinent information from many different sources. The second level search also provides statistics on the many submarkets within Camden Council which cannot be ascertained from the table provided at the first level search on the homepage.
This might sound confusing so let’s look at some screenshots which will clarify what is being said.
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 suitable 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 (last column) 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 ‘growth rate cycle’ option using parameters in your search which best suit your investment strategy.
Hold shift and click on multiple columns to sort by more than one column.
Let’s assume that I am interested in ‘bottom’ or ‘rising’ markets as I want to take advantage of the imminent capital growth to either buttress my existing cash-flow geared portfolio or to flip or develop the property within the suburb of choice. Clicking on the ‘growth rate cycle’ column we retrieve desired results which are sorted by ‘rising’, ‘declining’, ‘bottom’ and ‘top’ growth rate positions.
However, this parameter alone might not be sufficient to make a sound investment decision so I also sort by ‘confidence’ to retrieve areas which are experiencing a ‘bottom’ or ‘rising’ growth rate but whose provided statistics are marked with high confidence. The search retrieved is highlighted in the screenshot below.
The high confidence metric assures us that highlighted projected capital growth and yield figures will have a 5% or below error rate which considerably improves our ability to plan and make decisions.
As we can see, the combined sorting retrieves a result that highlights all suburbs with growth rate cycle in the ‘rising’ position which confidence of provided statistics is high in Camden Council. The way we approach the next round of analysing the retrieved information depends on a combination of individual-specific input and output concerns briefly addressed in previous pages which are also reflected in the following questions:
- What is my entry point? How much am I prepared to spend will dictate which median price suits my investment strategy and hence which out of the areas listed based on my initial search I choose;
- Am I interested in capital growth or rental return on both (i.e. total return)? Buying in a rising market suggests we are interested in capital growth but the projected yield should also be considered depending on our financial situation and the cash flow generated from our existing portfolio.
A negatively geared property, although positioned for capital growth, will put additional pressure on our existing cash flow with potential effects on our existing and future lifestyle.
After sifting through the table by using a combination of search parameters which best fit your investment strategy and current financial circumstances, we can move from the ‘ranking table’ tab onto the other tabs on the LGA page:
- Growth rate cycle
- Demand profile
These tabs contain additional statistics on all suburbs within Camden Council and provide us with information which deals with the previously mentioned ‘static’ tabulated format by ‘contextualising’ the provided statistics in time and geography dimensions. For instance, the provided YoY and forecasted capital growth figures seen in the ranking table, have a greater value when considered in terms of past cyclical movements of the area in question.
Once we select the ‘forecast’ tab, the first result we retrieve is a graph of the Council’s (LGA) ‘performance’ highlighting both historical as well as forecasted price movements in median rent and home value.
It is a pictorial (as opposed to tabulated) representation of data which highlights the additional information on historical movement in both home prices and rents. The historical data goes back as far as there is data of statistical significance to be collected.
This page can also be further customised to suit an individual’s needs. For example, we can switch between dwelling types (i.e. units and houses) or we can opt to retrieve a graph representation of the suburb of interest within Camden Council.
For example, by filtering for Gledswood Hills, we retrieve the following graph:
As Gledswood Hills is a newly developed area, the historical data goes back to 2014 only. The lighter shadings of both graphs present historical data up to the current quarter (Q3, 2020). The heavier shading of the graph (i.e. post Q3, 2020 point in time) represents the forecasted values. The green and grey bars (y-axis) represent the number of sales/rentals data which if referring to the above graph suggests that Gledswood Hills will experience a steady uptick from Q3, 2020 to Q2, 2022 in both number of rents and number of sales.
What is important to note that a rise in the number of sales and rentals does not immediately correspond to price/rent growth as standard economic modelling would makes us believe (i.e. higher demand = price/rent rise). This is a perfect example of why introducing additional variables such as population growth, building approvals, unemployment etc to anticipate market movements is unnecessary if one leverages HtAG’s algorithms to make informed decisions.
Looking at the rental graph alone one can see that a steady increase in the demand for rentals and its lack of correspondence with the increase in the rent values (the rent will essentially return to approximately $530 per week at Q2, 2022) suggests that there could be an oversupply of rentals in this market. The forecasted information eliminates the hassle of obtaining statistics from various sources (such as population and number of rentals advertised) to determine the vacancy rate of a particular area to make appropriate decisions.
Returning to the explanation of the graphs, the blue line in the graph highlights the median price movements from Q3, 2014 to Q1, 2020. As indicated, the median value of properties in Gledswood Hills is also positioned for growth between Q3, 2020 to Q1, 2020. As mentioned previously, rents on the other hand (the red line) are positioned to oscillate returning to about Q3, 2020 position in Q2 2022.
Having this information is useful when deciding on the initial investment outlay. As rents will not increase, it behoves the investor not to overstretch for the sake of anticipated capital growth thus diminish one’s ability to maintain the property in the first instance (i.e. service the loan, pay utility and council fees, support vacancy rates etc). Furthermore, since prices are positioned to grow while rents will remain in the same position, the gross and net yield of the area will actually decrease which can have adverse effects on highly leveraged portfolios or those exclusively focusing on capital growth.
Implications of historical and forecasted values
Another thing to note is that the total return of the area (capital growth plus rental yield) will diminish which needs to be taken into consideration when benchmarking investment potential of Gledswood Hills against other areas.
The rental demand will, however, stay strong indicated by the rise in the grey bars (bottom graph) meaning that even though there could be an oversupply of rental properties in Gledswood Hills, one can ensure that her property is not kept vacant for an inordinate amount of time by buying and subsequently renting a property that best fits the ‘demand profile’ of the area.
What is not evident in the above screenshot but is available on the platform is that customers can also hover over the graph(s) with their mouse which would yield various statistics. For example, the customers can retrieve number of sales/rentals statistics for the particular period in time. On the other hand, by pinpointing a particular section of the line on the graph, the customers can retrieve exact median price/rent statistics for the period of time of interests, whether historical or forecasted. Once can also zoom into a particular section of the graph, amplifying it to retrieve a more ‘detailed’ view of areas behaviour for the highlighted period.
Finally, referring back to comments made about the importance of having historical data when making a property investment decision, we can see that Gledswood Hills, although a relatively young area, has not experienced large oscillations in its median price which adds to its being perceived as a quality investment area. This is particularly pertinent for the fact that it is a newly developed location, as 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 fundamentals which position the area as a suitable long term investment. This will be more evident when we move onto discussing the “Growth Rate Cycle” (referred to as GRC) tab.
Continue to part 3 >>>