Money Magazine Australia - - COVER STORY -

For prop­erty buy­ers and in­vestors alike, it’s cru­cial to find mar­kets in which de­mand ex­ceeds sup­ply. But how is this done? Here is a list of some of the key met­rics used to gauge sup­ply and de­mand for real es­tate:


The auc­tion clear­ance rate is the num­ber of prop­er­ties that sell at auc­tion as a per­cent­age of all prop­er­ties auc­tioned. Imag­ine a mar­ket in which the bid­ding is fierce for most auc­tions; the auc­tion clear­ance rate will ob­vi­ously be very high. This sin­gle met­ric can be used as a gauge of de­mand rel­a­tive to sup­ply.

But what if there was only one auc­tion? The clear­ance rate can only be 100% or 0%. That’s a mas­sive dif­fer­ence for the sup­ply and de­mand story based on the re­sult of a sin­gle auc­tion. This is why it’s im­por­tant to con­sider mul­ti­ple in­di­ca­tors, rather than just one in­di­ca­tor in iso­la­tion.


The length of time a prop­erty spends listed for sale be­fore sell­ing is called the “days on mar­ket”. Imag­ine ea­ger buy­ers ready to make quick of­fers as soon as a new prop­erty hits the mar­ket. Prop­er­ties will sell very quickly in mar­kets where de­mand ex­ceeds sup­ply. The lower the av­er­age days-on-mar­ket fig­ure for a sub­urb, the more likely de­mand ex­ceeds sup­ply.


This is the dif­fer­ence be­tween the orig­i­nal ask­ing price and the even­tual sale price. When de­mand ex­ceeds sup­ply, sell­ers are in the box seat and are less ne­go­tiable on price. Buy­ers are forced to make strong of­fers or miss out, so the av­er­age dis­count rate is usu­ally quite small.


The ren­ter pro­por­tion is the per­cent­age of renters in a mar­ket com­pared with the to­tal num­ber of res­i­dents. In­vestors don’t want to be com­pet­ing for ten­ants with other land­lords. The pro­por­tion of renters should ideally be as low as pos­si­ble since it is a sup­ply met­ric.


The per­cent­age of rental prop­er­ties that are cur­rently avail­able for rent is a mea­sure of the de­mand and sup­ply for rental prop­er­ties by ten­ants. When va­cancy rates drop, it means rents are likely to rise.


The rental yield is the an­nual rental in­come as a per­cent­age of the prop­erty’s value. The yield can some­times be a pre­cur­sor to cap­i­tal growth. But it is also an in­di­ca­tor of the cash flow po­ten­tial for a prop­erty mar­ket.


The mea­sure is the num­ber of prop­er­ties for sale in a spe­cific mar­ket ver­sus the count of all prop­er­ties in that same mar­ket. Some sub­urbs are larger than oth­ers, so when cal­cu­lat­ing sup­ply you need to do so as a per­cent­age. The per­cent­age of stock on mar­ket is a great in­di­ca­tor of sup­ply. For strong price growth we want sup­ply to be as low as pos­si­ble.


When a po­ten­tial buyer ex­am­ines a prop­erty for sale listed on a real es­tate web­site, their search is recorded. If we have a count of the num­ber of searches and com­pare it with the num­ber of prop­er­ties, we have a rough idea of the level of de­mand rel­a­tive to sup­ply.


It’s vir­tu­ally im­pos­si­ble to man­u­ally col­late the data to re­search thou­sands of prop­erty mar­kets around the coun­try in a short time. For­tu­nately, there’s a short­cut that can be used to cull the list to some­thing more man­age­able with­out miss­ing a ter­rific op­por­tu­nity – it’s the use of big data.

Big data is the new re­sources boom for prop­erty buy­ers and in­vestors. So in­stead of buy­ing in risky min­ing towns, you can now mine data to find safer lo­ca­tions set to de­liver quicker gains.

Gone are the days of sub­jec­tive, opin­ion­ated re­search used to find growth hotspots. The ex­perts and their di­vin­ing rods are be­ing re­placed by data sci­ence. Big data al­go­rithms have al­ready been out­per­form­ing the growth picks of the high­est-pro­file ex­perts in prop­erty in­vest­ment.

So in tak­ing up the chal­lenge of pre­dict­ing the best mar­kets to­day that we be­lieve will out­per­form by 2020, we used our de­mand­sup­ply for­mula that we call the Lo­ca­tionS­core. We score ev­ery sub­urb (by house or unit) out of 100. The higher the score, the more de­mand ex­ceeds sup­ply, which greatly in­creases the prob­a­bil­ity of prop­erty value rises in that lo­ca­tion for that prop­erty type.

To de­ter­mine the Lo­ca­tionS­core for each sub­urb and prop­erty type, we com­bine the eight met­rics listed here. Some met­rics are more im­por­tant than oth­ers, so we al­lo­cate each one an im­por­tance rat­ing. Then we com­bine all eight met­rics based on their rel­a­tive im­por­tance into one over­all score.

Th­ese top 20 lists con­tain the top mar­kets as or­dered by Lo­ca­tionS­core for each price range. It’s th­ese mar­kets that, in our view, have a bet­ter chance of ex­pe­ri­enc­ing im­me­di­ate cap­i­tal growth than mar­kets with lower scores, in­di­cat­ing de­clin­ing or soft de­mand.

His­tor­i­cally, 83% of the top 20 Lo­ca­tionS­core mar­kets have out­per­formed the na­tional av­er­age growth rate over the next three years. What is also in­ter­est­ing is that quite of­ten the Lo­ca­tionS­core top 20 had growth rates that were dou­ble the na­tional av­er­age, re­in­forc­ing the fact that the law of sup­ply and de­mand in­flu­ences price move­ment in prop­erty.

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