Property Data is relied upon by many Investors and Property Advisors to make informed decisions about where to invest for maximum benefits. However, there are definitely some precautions that need to be considered when relying on Property Data. Having completed a PhD in the past, I know the importance of the reliability and accuracy of data sets, so in this review I have summarized some the investment data relied upon and why investors need to be cautious when
Median Property Price Movements
Most property data reports on the median value. The median is NOT the average, instead it is the middle number when a list of numbers are ranked from the highest to the lowest. Whilst the median can be a good representation of the market movements in a suburb where all of the properties are similar, it can actually be misleading when there are a lot of different types of properties selling in the same suburb during a specified period of time.
For example, in Brisbane, some of our blue-chip suburbs have a mix of properties that are fully renovated, high and elevated with city views, combined with older unrenovated properties that lie in flood plains. In any given month, there may be a mix of homes that sell, but if there are more homes in the elevated locations that sell in a specific time period, this can artificially inflate the median value for that set period. The opposite is also true. When more of the unrenovated, low lying properties sell in a specified period, this can artificially deflate the median value. What exists in the data, is what is termed compositional bias.
So when tracking median values in a specified location, fluctuations are often a reflection of changes in the composition of dwellings that sell as well as price changes. You see property is NOT homogeneous … one property is NOT a direct substitute for another property and the composition of residential property is continuously changing.
So when there are big price swings in a particular area, it does not always mean that there have been wild swings in capital growth. It can just be a statistical anomaly. This is where local knowledge of WHAT is selling becomes critical to understanding price shifts.
Days on Market
This indicator is a count of the number of days a property is listed for sale when it comes to the market, before it is actually sold. In most cases, a property is considered to be on the market as soon as the real estate agent lists the property for sale.
In a fast moving market (usually when there are more buyers than sellers) the Days on market often drops and the opposite occurs when the market slows down. But is this indicator reliable?
The reporting for Days on Market relies on sales agents providing accurate information. There have been many instances where we have seen the days on market value reported as being much longer than what we have observed by being part of a property transaction. Let me explain …
In the current fast-moving market, we are seeing many properties go under contract within days of being listed. Generally … less than 7 days. Then we were are seeing those properties and the DOM indicator being reported .. it is showing a much longer time frame. It makes us wonder if Agents are recording days to contract … or days to unconditional … or day to settlement. There is no firm indicator that seems to be reporting this information accurately and for this reason again … we are cautious when relying entirely on this data.
Additionally, properties can be sold without being listed (and very quickly!), some properties may have a sale fall through which may skew the data and some properties may be listed with an agent for 90 days, then relisted with a new agent – how is that data recorded?
There are often big differences that we are seeing by being “on-the-ground” versus what is being reported in the “data” and this is concerning when property investors are using and relying upon this data to make investment decisions.
This is another reason that local knowledge matters. Data is only as good as how it is collected and the parameters around its accuracy.
The vacancy rate is a measure of how many rental properties in a location are currently without a tenant. If there are 200 rental properties in a suburb and two of them are vacant, then the vacancy rate is 1%.
This indicator can also have accuracy problems at a specific date in time, especially when properties listed for rent are not currently available. Properties may still be occupied but be available at some future date.
The gross yield for a suburb is one of the most unreliable statistics commonly quoted for property markets. The reason why is that both variables required to calculate this figure (ie: median rents and median property values) are highly susceptible to statistical anomalies.
The greatest impact on these figures can occur when there are limited or very few properties selling or listed for sale, or very few leases being signed or a low number of properties available for rent. Of course, compositional bias also exists. It is therefore important to calculate the gross yield on a property by property basis, and not at a suburb level because different properties within a single location may have quite different gross rental yields.
There are many other property data indicators that are quoted from time to time and this article has certainly not been exhaustive in covering them all. But what I have tried to do is highlight the important of reading into the data to understand more about what it might be representing. Data plays an ever increasing role in property research, and therefore understanding what it is representing and what it is made up of is critical. Whilst data drives the macro approach for many investors, when it comes down to a suburb level … local knowledge becomes just as critical. That’s where a local Buyer’s Agent can help.