Could Software predict the Rise and Fall of Real Estate?

For decades economists have been trying to predict the rise and fall of stock market prices - and some have even postulated that it would be possible to create computer models using software which would predict how stock market prices would go up or down over both the short and long term.

But the problem with making such predictions is that there are too many factors and you can't predict accurately where things are going to go. Especially with the stock market, which is notoriously volatile.

Even with real estate it is difficult to make predictions for the future unless there is a large factor that is guaranteed to happen.

Many people turn to experienced economists to try and get predictions. But even they can be wrong when it comes to their doomsday predictions or predictions of sunny skies and smooth sailing. Its like trying to predict the weather - even the expert meteorologists suck at predicting when it will rain.

For example in 2011 economist David Madani sent shock waves through the Toronto real estate industry when he predicted that Toronto’s overheated housing market was due for a 25% correction which would result in much lower prices.

Two years later, prices have continued going up to the current point where prices have now stagnated.

David Madani is still waiting expectantly for Toronto's housing boom to falter.

Meanwhile myself, I must admit I am doing the same thing. In 2012 I predicted Toronto's condo market would collapse approx. 40% by 2015-2016 due to the over-abundance of condos that will come on the market around that time. I will be waiting expectantly to start seeing some downward movement in condo prices in Spring 2015... But that is 2 years and a couple months away, so I've got plenty of time to wait.

David Madani says he remains convinced that the most prolonged housing boom in history, fuelled largely by low interest rates, is headed for a hard landing, particularly in Toronto’s “overbuilt” condo sector. So he is looking at the same big factor I am looking at... But why was he predicting that back in 2011 and when did he think it would happen?

Well he thinks things will start to change this year - Spring 2013.

“What’s critical is what happens in the Spring,” says Madani. “If we continue to see increases in active listings as sales continue to decline, then we’ll start to see more obvious signs of prices dropping.”

The March-to-May period is traditionally the peak buying and selling season and a barometer of consumer confidence when it comes to real estate. But he is banking his prediction on a mighty big "if" that something will happen in 2013 when many more solid-minded economists are saying nothing major will happen with the prices until 2014 at the earliest.

It is true that many veteran real estate watchers can’t agree where the market is headed. There is simply too many factors to consider - and chief among them is consumer confidence, which is an often unknown factor that you cannot predict which way it will go until the time actually comes and then we see changes.

Which begs the question - could we design a piece of computer software to make predictions for us instead? If we feed enough - ENOUGH - data into the computer concerning prices, interest rates, sales rates, mitigating factors etc. shouldn't it be able to predict what the sales and prices in the near future will be?

It wouldn't be able to predict long term changes, but it might be able to predict small term changes based on current trends in the market - and using historical data we could check the accuracy of predictions.

The average sales price of a GTA home was up 4.1% in January 2013 over a year earlier, up to $482,648.

However we should note that it has actually dropped from the benchmark price by almost 1.5% just in the last six months, according CREA figures.

It really is the issue of bidding wars - a blood sport for those who can't really afford it - and some Torontonians are bidding way too much and banking on the economy to stay good and housing prices to continue going up. Sellers in Toronto have become so used to having bidding wars that they are now holding out for high prices - while buyers are realizing that they are better off waiting for deals.

So the question is, who will blink first? Will buyers give in and buy anyway? Or will sellers give in and finally lower their prices?

“Buyers and sellers remain in a standoff,” says John Andrew, Queen’s University business professor and real estate expert. “Sellers are holding out for their prices and buyers are waiting for deals. I think it’s too early yet, but there will be a correction.”

Thus predictions of slowdowns and dropping in prices has buyers interested - and sellers worried.

If someone were to make real estate software which could accurately predict when a slowdown in sales will happen - and when prices will drop - and how much prices will drop, well then that would make many real estate agents, buyers, sellers and economists sit up and pay attention.

But no such software exists.

Indeed, when you talk about real estate sofware usually people think of property management software - or online real estate databases (MLS)... things like that.

Even if someone - eg. an university professor with some serious computer skills - were to create a computer model that predicts future real estate prices then other real estate experts would step forward to naysay and claim the software is bugged and faulty, trying to point out inaccuracies in the software's predictions.

And they would be right to do so. We use such software to predict weather patterns, and it still fails despite people trying for decades to get it to accurately predict the weather.

But we have reached a point wherein the computer model is "reasonably accurate". Its off a little, but its pretty darn close to the target.

So I have to wonder, if we can do that for the weather and its reasonably accurate, maybe it is time we try and do that for predicting real estate prices?