Today’s the day we get to stacking models for Canadian real estate price targets. Last week I was asked by the Canada Mortgage and Housing Corporation (CMHC) to speak at their Housing Finance Symposium. These are pretty much my presentation notes, with more detail for non-technical audiences. In part 1, I discuss using a home price to income ratio model to show how unlikely it would be for real estate prices to catch up to incomes. In part 2, we use a median credit exhaustion model to see where people psychologically feel the risk/reward ratio of buying is too high. Today is the third and final part. We’ll combine both models to extract price targets, timelines, and recoveries.
Buy A House If You Want
Seriously. If you want to buy a house, buy whatever you want, whenever you want it. As long as you aren’t stretching yourself thin on payments. If you can afford to diversify your assets, you’ll probably be fine. I’ve said it before, and I’ll probably say it for as long as I deal with housing finance: There’s a cost of attached to what you want, that can’t be quantified.
Some people want to raise their kids in a house, others have a dream of just owning. If you buy something, and you lose a little money on it – consider that the cost of being you. Feel free to leave now if you’re the kind of person that watches HGTV, and dreams of your picture perfect housing future.
The rest of this piece is for people in housing finance, urban land banking, or that are curious how yesterday’s model translates into price targets. This read is for people like me, that have nearly zero emotional attachment to housing or money.
Layering Models For Precision, Confirmation, and Better Accuracy
Now, I can’t repeat this enough – a model isn’t 100% accurate. However, we can combine models to help build better precision and accuracy. You would be shocked at how close some financial models get. Today we’re going to combine the home price to income ratio, with the median credit exhaustion model. You don’t have to remember everything from the last two articles in the series, but you have to remember two things. One, home price to income ratios demonstrate support at 30% lower than peak, and prices take off again once hit. Two, median credit exhaustion models might be a solid indicator of when home prices begin growing again. Got it? Sweet.
Note: 2017 is partial, year-to-date. 2018 to 2021 are projections. I’m good with numbers, not a time traveler. Source: Better Dwelling.
Currently we’re at a home price to income ratio of 9.56, and if we assume the support is 30% lower, we get 6.69. Combining credit reduction (derived from the median credit exhaustion model), interest rate projections, and factoring the current rate of income growth – we plot the ratio. We would hit support in 2021. This is kind of interesting because it implies confirmation of a bottom. We now have two models that hit this number. Incomes would need to grow at a similar rate to the past 5 years, otherwise prices decline for much longer. This did not happen in the early 1990s, causing a little hiccup after prices bottomed, before they started climbing again.
On the upside, hitting the support in the same year could imply a quick bounce higher. Although as we move through the predicted plots, we would update the model with final numbers. Income stagnation, interest rates stalling or being slashed, etc. will have an impact on timelines. However, we’ve factored in everything we know at this point, and the bias is even a little higher to the upside.
Now remember, this is only two models combined. The more you can combine, the higher the rate of potential precision. Currently we use just over 200 different models to make our internal indicators. To be honest however, the dates are pretty similar, and the price targets are pretty close using just these two.
What This Means For Prices
Boring, get to the price targets – right? These two models when combined can be used to get a print on numbers. Today an average home in Toronto costs $780,000, and that’s just an average home – not a detached. By 2021, this model shows the cost of an average home in Toronto would be around $574,000 in 2017 dollars, about 26% lower. Now, those are 2017 dollars – not the sticker you would pay in 2021.
Let’s assume inflation hits the target every year for the next 4 years. In the unlikely event that it does, an average home would cost around $621,000 in 2021 dollars. That’s a sticker price that’s 20% lower than today’s price. If you’re wondering why I said “unlikely,” it’s because inflation has been about 25% below target for the past 5 years. An increase in interest rates, would make it even less likely for inflation to hit target. I’m an optimistic guy though, so let’s go with FrannyMo’s “firing on all cylinders” and assume we hit those targets.
Do OSFI B-20 Regulations Change This Model?
Yesterday, I’ve never received so many emails from portfolio managers asking the same question: Does the model factor in OSFI’s new B-20 regulation changes? No, it doesn’t. However, B-20 would have minimal impact on the model at this point. Our median credit exhaustion model isn’t based on the maximum credit available. Instead, it maps perceived consumer risk involved in taking out loans.
In my opinion, B-20 does reinforce that 2017 is the bottom of credit exhaustion. Credit isn’t just perceived to have high risk for home prices in Toronto at this point, but a cap has also been placed. This cap ensures that middle to lower income investors don’t max out their leverage. It sounds harsh, but let’s be honest – high income investors aren’t buying into this risk right now. Scotiabank CEO Brian Porter probably didn’t sell his house just six months after buying it because he thought it was the perfect time to invest. Ditto on why he ended up slashing the price ten months into ownership, to below his purchase price.
If you’re a millennial that read through anyway, close your mouth. Once again, modeling isn’t an exact science, it’s used to help mitigate large investor risk. Banksters and government employees are the ones interested in this. My goal here is to help millennials understand that you’re an active participant in this cycle – regardless of whether you go in blind knowing that. After all, money doesn’t care if you were unaware that you bought at peak.
You need to establish an appropriate personal risk model. Do not convince yourself every buy is an investment, especially if you did no research. Real estate almost always runs in a cycle. Figuring out where you are in the cycle, helps to determine if your buy is actually an investment, or a lifestyle choice.
If you’re from another part of Canada, sorry we only used Toronto for this presentation. Here’s a national read using the OECD House Price-To-Rent Index we ran earlier this year, showing that home prices could drop as much as 28% across the country.
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