The Steps to Residential Property Data Performance

The 4 steps to take advantage of residential property data

 

Do you agree supply and demand has a correlation with price?  If yes, then you need to immerse yourself with data at suburb level.  Observing the moving data for many locations provides many insights that you can take advantage of. 

 

Why?

Because the change in supply and demand data is much more volatile than price movement.

 

This is because real estate markets are inefficient.  In real estate this means, the amount of information available about a property is not equal for every potential buyer.  Many potential buyers have to rely on publicly available information and possess a lack of knowledge around things like construction quality. 

 

Because of this lack of publicly available information, the price of a real estate asset does not reflect the information available, and therefore makes it hard to value.

 

Real estate markets are inefficient for many reasons and I’ve discussed these here in my free e-book available to subscribers, but to name a few let’s consider the following:

 

  • Property is immovable, heterogeneous, illiquid, and has limited essential information available to buyers for markets all over the country.
  • Ownership tenure is long e.g. many years.
  • Changes in population and demographics are difficult to measure with any certainty. This makes it difficult to forecast future housing supply requirements.
  • Dwellings are tangible. Therefore, they age and depreciate.
  • Supply usually lags behind demand due to the timeframes to create more real property.
  • No access to real time data.

 

The opposite of an inefficient market, is an efficient market.  Here the price is relevant to the freely available information accessible to everyone.  Many argue securities are an efficient market for this very reason.  I believe this was originally presented by American economist Eugene Fama called efficient market hypothesis.

 

What does this mean?

It means real estate markets are never at equilibrium.  Because real estate markets are never at equilibrium, data is highly necessary in order to detect where demand outweighs supply and by how much.  If we know this information, we can make real estate markets more efficient.

 

The 4 steps

To track or gauge this data, we can use various metrics or indicators specific to a market that illustrate how supply and demand turns, pushes, and pulls against each other.  Ultimately we can source whether demand outweighs supply or supply outweighs demand and by how much.

 

As a starting point, to help you in your journey towards making better decisions, the following is a process you can use to familiarise yourself.  The indicators mentioned in the article are microeconomic and specific to every residential market in Australia. 

 

Always remember, don’t take one indicator in isolation from the rest.

 

Step 1 – Becoming familiar with the many different indicators 

Days on market, auction clearance rates, online property views, stock on market, yield, vacancy rates, turnover rates, building approvals, borrowing power, absorption rates, discount rates, number of new off the plan sales, are all highly relevant to maximising the buying decision.

 

Step 2 – Interpreting the indicators 

Knowing the important indicators and correctly interpreting them are two different things.  You will need to be sure what side of the equation these indicators are on – supply or demand.  Getting this wrong could mean purchasing in the wrong location and impacting your future. 

 

As an example, the following are on the demand side: days on market, auction clearance rates, online property views, borrowing power, yield, and absorption rate.

 

You will also need to interpret the direction of the indicators.  As an example, a sign of increasing demand is when days on market is trending lower NOT higher.  Whereas, it’s the opposite for online property views.  Both these indicators lie on the demand side, however they need to trend in opposite directions to both increase demand.   

 

Lastly, ensure you complete this for most property types e.g. houses, townhouses, units, apartments, villas etc. 

 

Step 3 – Analysing the indicators

Track the indicators over a couple of months.  Look for any patterns, anomalies, trends, relationships, and match with any price movements.  How many indicators are trending up? 

 

When analysing be sure to match apples with apples, don’t mix and match data. 

 

Step 4 – Checks and balances

Double check your analysis and start considering available properties.  To help with this please read some other articles by Urban Statistic.     

 

Conclusion

Personally I trust data over someone’s opinion because I’m immersed in it.  The more familiar someone is with something, the more they trust it.  There is no doubt many people aren’t accustom to consuming data for decision making, particularly when it comes to investing, but we need to change our mind frame to maximise decisions. 

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