The Future of Canadian Real Estate Prices Part 1: Filtering Noise

The Future of Canadian Real Estate Prices Part 1 - Bulls**t Detection

Recently I was invited by the Canada Mortgage and Housing Corporation (CMHC) to speak at their Housing Finance Symposium. I usually turn down interview requests, panels, and public speaking opportunities. However, this was a technical talk for banksters, and policy makers on the Future of House Prices. I was one of two Canadians invited to speak on the topic, so I took the opportunity. I figured I would do a technical talk on forecasting speculative markets, and how to use forecasting to detect BS.

The talk went well, but it was the only one over two days where I heard people audibly gasp during a presentation. Quite a few analysts and bank executives that attended (or heard what I said from friends), have since requested my slides and meetings to ask questions. Rather than respond to every email, I figured I would assemble this into a more in depth series of articles for our readers. Since you know, I only entered the housing industry to democratize housing information – not have closed door meetings. My primary belief is when markets are less opaque, they become much more stable.

Note: The following is based on the presentation made, but has been reorganized slightly. This allows us to go more in depth on certain topics, as well as break it up so it’s not too long of a read. This is part one, which summarizes the absurdity of current expectations.

First, A Little About Me

Save a few Twitter rants, I’m a little reclusive – so this where I’m coming from. My background is in artificial intelligence, machine learning, and equities analysis. Basically, I used to build robots that analyze the stock market, then make intelligent trade decisions. Yes, the kind used by high-tech trading firms, and individuals with supervillain amounts of money.

I’m the co-founder of Better Dwelling, a media company that applies these same technologies to real estate data. Our goal is to democratize analysis, and data that is typically reserved for deep pocketed investors, and put it in the hands of Millennials and policy makers, so they understand the market. 90% of the top 100 banks by AUM, have at least one executive that reads us, at least once a week. We’re just over a year old, so if you’re not a bankster you may not be a regular reader. However, we play a significant role in how the experts you do listen to see the market.

Money 101, and Support Levels

First, we need a brief introduction to a very basic money concept that’s little known outside of equities market – support levels. When commodities make an unprecedented rise, traders look for when buyers will establish support. That sounds a little technical, but basically all they’re looking for the lowest price that would trigger buying. This isn’t based on fundamental performance, it’s based on buyer psychology. Buyers and sellers leave marks on a chart, that are very often very clear to traders that understand technical analysis.

This may sound like they’re reading tea leaves, but it’s surprisingly standard. In currency and equity markets, ~23% and ~38% are popular levels to observe this response. That’s pending no additional downward pressure, like fraud or bankruptcy. It’s so popular, most private trade algorithms have it pre-programmed in as “catches.”

We’ve been applying machine learning to determine if this concept applies to real estate, and we’re finding significant correlations. Many North American real estate markets tend to establish a support level in the home price to income ratio, between 28-30% lower than an unprecedented peak. Pending your city doesn’t turn into Detroit, and has a devastating loss to its underlying economic foundation.

Why is this important? In modern real estate markets, the ratio rarely resets. They continue to rise, but with retracement around these levels. Basically, people become more comfortable devoting a higher level of income to shelter. People were wondering where that level is, and 28-30% lower is what we’re finding.

House Price To Income Ratio

The second thing you’ll need a brief understanding of, is the home price to income ratio. A home price to income ratio is a common indicator used by governments and academics. The ratio tells us how quickly home prices are growing (or shrinking) compared to incomes. There’s a few variants, but we like to use the price of a typical home, compared to the median income.

When the ratio goes down, it means incomes are growing faster than home prices are rising. When it goes up, it means home prices are growing faster than incomes. There’s a little more to it, but those are the basics.

Home Prices Will Be Flat … Is Bulls**t

One of the most common things I hear after a home prices surge, is prices will be flat until incomes catch up. It’s a common explanation, I hear from some very credible people. Most people give it a thought, then just accept that statement. If you’re a money or data person however, this is what you picture.

Adjusted to 2015 Dollars, for your inflation adjusted pleasure. Source: TREB, Better Dwelling.

You don’t have to be a data expert to understand there’s something wrong with this chart. If I saw it, I would assume there was a plotting error. However, this is how a lot of high profile experts actually explain real estate markets.

In fact, one of the people I recently heard this from is one of Toronto’s largest private wealth managers. He’s currently advising ultra-high net-worth (UHNW) clients, which are those with more than $30 million in investable assets, to continue to buy real estate. He believes home prices will be flat until income catches up, and then prices will continue to climb. He’s a credible guy, and he’s right more often than he’s wrong. So let’s take a look at how long it would take for incomes to catch up to home prices.

Toronto Would Take 41 Years

Toronto home prices had a huge run over the past 18 months, sending home prices very high, in a very short period of time. In fact, mega bank UBS now calls it the riskiest real estate bubble in the world. The current home price to income ratio is 9.56, and we’ll assume Toronto doesn’t crumble after a correction, so a support would hold. At 30% lower, we get a support ratio of 6.69. If home prices stay flat, and incomes grow at a similar rate to how they’re growing today – it would take 41 years. Forty. F**king. Years.

Source: TREB, Statistics Canada, Better Dwelling.

Essentially, this wealth manager is advising people to pay a forty year premium on a home today. Remember all of the people that you’ve heard say prices will be flat until incomes catch up? They’re either lying, haven’t run numbers, or think you can pay the same price forty years later. Either way, their advice is close to useless.

This is a national issue, so people have to accept that incomes aren’t likely going to catch up to home prices. Will home prices come down, or should people be scrambling to get into the market then becomes the question. We’ll talk forecasting and a new model we’re working on called median credit market exhaustion in the next part.

Note: Sorry Vancouver readers, the talk was mostly about Toronto. We’ll have someone give Vancouver the same love over the next few days.

Update: Read part 2 here.

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  • Trevor 7 years ago

    More of this, please. And hurry! We need transparency, data, and rationality about Canadian Real Estate from a source that doesn’t have skin in the game.

  • Bay Street Guy 7 years ago

    Ah man, and here I was thinking you were my secret weapon for housing analysis. 😛

    Hopefully now that you’re on the radar of the government and banks, you won’t tone down the sarcasm and swearing. Keep up the great work!

  • srsly 7 years ago

    Very informative post. Keep it up Stephen

  • David 7 years ago

    Thank you for the talk yesterday, and for providing this write up. I will confess, I was one of the people that gasped during your presentation. How could you not when you started giving price targets for Toronto homes.

    I was discussing your views on money and commodity analysis with my colleagues afterwards. It takes someone with very deep knowledge of finance to be able to break down numbers the way you did. We very much did not expect it from the youngest person in the room (in jeans and a t-shirt nonetheless). Can’t wait to read the second part, your credit modeling deserves a whole presentation by itself.

    Hopefully you earned a keynote next year.

    • Aaron 7 years ago

      What was his price Target?
      Is there a a place where I can get a copy of his speech to understand?

  • Alex 7 years ago

    Price to income ratio indicator has one very fundamental flaw: it does not account for interest rates. People always think in terms of “monthly payments” and not how much house costs. We are still at historically low interest rates and people tend to assume it will be like this forever. And the big problem is that no-one knows what will be he future of interest rates.
    Another point is that there is a lot of wealth accumulated and many purchases today are coming from international and local investors. And when wealthy people playing their games, local incomes make no difference to house prices.

    • Mac 7 years ago

      When Realtors say “a home is only worth what people are willing to pay,” that works both ways.

      Interest rates impact how difficult it is to carry a mortgage more than the price. Vancouver is an example where low interest rates don’t make a difference, since even regular households don’t make enough to buy homes around here. Calgary is the opposite example, since people aren’t borrowing close to the amount they would qualify.

      New York would be the ultimate example, because people can’t afford to live there. Prices still move sideways. Low interest rates, higher interest rates both barely makes a difference in that market. It moves how it moves.

      Higher interest rates would reduce buying volume, but prices are typically bound by expectations related to net worth and income.

    • Gregory 7 years ago

      Exactly, Banks don’t lend money on a “multiple of income” — it’s payments based on interest rates… people by Payments not Price.

      • Realtard Bartholemew 7 years ago

        You can always find the realtard in the room. The value of a home is based on perception, not on fundamental metrics.

        Why is land in India cheaper than land in Toronto, afterall, it’s more dense? Perceived value! Low interest rates don’t cause high land values, because the rest of Canada can borrow more than average homes cost. It’s 99% what people are convinced something would cost, and 10% how they’ll pay for it.

  • MH 7 years ago

    Thank you for doing this Stephen. Waiting for the next one…

  • bluetheimpala 7 years ago

    I understand the data (sort of, I’m not super bright unfortunately) however similar to any major urban city, won’t labour supply+demand dictate the wage and put updward pressure on it.

    Employers head to these regions to get the best talent, the pay increases as demand for resources increases with limited supply, workers get paid more and thus put pressure on housing. As long as Toronto keeps attracting the workers, the employers will follow and wages can only increase in my mind to a classic ‘big city’ wage.

    Why would Toronto, a much denser city more similar to NY than SF, not see the same results to these cities? Yes I anticipate much eye rolling…Toronto is world class city. Suck it up buttercup.

    Toronto proper seems poised to continue to do well with some pain for the outer regions and a big ? for the suburbs (more so the rural-burbs…no one should be paying $1m+ for a sub division house in Orangeville…)

    Won’t wages increase at a higher rate for white collar workers in Toronto?

    • Econosaurus 7 years ago

      In theory, in reality wages are largely stagnant – especially in major urban cities.

      The shift to nicer white collar jobs would be great traditionally, but we have a global workforce with low trade barriers. Since there’s no containment pressure outside of government and banks, companies move wherever skill/wages balance. So wages rise to a certain point, then leave if there’s too much pressure higher. Countries are racing to the bottom, and employees are the first to realize losses.

  • Adrian Knaud 7 years ago

    More and more houses are being filled with more and more wage earners..So what is the limit?

  • Jungle 7 years ago

    Great job, keep up the good work, blog is great!!

    • Michael L. 7 years ago

      Which has nothing to do with prices. I’m in Halifax, home prices may be higher than they were, but they aren’t so high that people have decided to borrow right into the maximum. Only clowns in Vancouver and Toronto have decided to spend more because they’re slapping on the “world class” tax.

  • Tom Gr 7 years ago

    A few questions:
    Who is buying all these properties?
    Foreign investors? Rich investors buying them and renting them? There are soo many houses that were purchased and just sitting vacant? Any data on that?

    The one thing I notice is, when looking at this data it reminds me of a “bell-curve” that has shifted to a certain direction because it has been heavy influence from outside sources. Sort of like a group of students got the exam copy and cheated, the overall average will go slightly higher and the Bell-curve will shift.
    So, I am just wondering, like, why is all this shift upward in pricing?

  • Randall Passmore 7 years ago

    Bubbles burst sooner or later…. don’t make the mistake of not seeing the forest for the…… get deluded with too much fine analysis and miss the call obvious.

  • Justin Thyme 7 years ago

    You are a wise man, and I am sure you know what you are talking about,

    So please explain 1989 to 1998, and why it reached support in only 9 years.

    • Alistair McLaughlin 7 years ago

      Because prices didn’t stay flat while income caught up. Prices dropped by about 30% between 89 and 98. Exactly what he’s saying is likely to happen again.

    • Ron 7 years ago

      Because prices went down.

  • Nav 7 years ago

    Can’t wait for part 2, finally I am reading something that makes sense. All the reports and guidance from CREA, Real Estate Boards, etc have so much built in bias it is disgusting.

    Thank you for this breath of fresh air!

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  • Tyler 7 years ago

    Thankyou for this. I see so many industry ‘Professionals’ talking their real estate book while glossing over the facts. It is nauseating to think honest hard working people are being jostled by these agents into making terrible financial decisions that will last a lifetime. The facts are clearly stated above. THE BUBBLE is almost twice as inflated as the bubble that exploded in early 90s. Greater than 9x income metric IS THE ONLY DATA POINT YOU NEED TO KNOW. Mean reversion is inevitable and the fallout will be painful. These ‘professionals’ require significantly more regulation they remind me of wall street stock brokers in 1987

  • Bonnie Bereskin 7 years ago

    Thanks for your skilled and courageous analysis. It is amazing that Torontonians continue to believe the hype of TREB and news media while well respected financial institutions, all over the world, call Toronto real estate a bubble. Stephen I wonder if you have any expectations about the time it will take to reach the bottom of the bubble. It is difficult to even gauge TO home prices with the substantial inventory of unsold homes. Asking prices continue to be quite unrealistic and it seems that renovated and good condition homes are what are selling. As Justin noted it took 9 years for the last bubble to unfold? Any thoughts on time? My own prediction (without your finance background) is that we are in for a multi year drop with some up/down gyrations. Any thoughts?

  • Chris T 7 years ago

    What caused the ratio in ~1990-early 2000 (can’t see the exact years from your graph) to drop? According to your house price graph, the house price in approximately the same period stayed flat. Does it mean income got a substantial increase during this period?
    Can you extend your graphs to 10-20 years before your first data point? History often is quite telling in data analysis.

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  • Dennis 7 years ago

    Please note that there is massive fraud in the system. I cannot expand due to my position of employment.

    Getting a mortgage at 2x-3x what you qualify for is easy. People only care about the monthly payment. People who have nothing have no problem returning to nothing. Moral Hazard, beautiful.
    The guy who cleans our office building just told me he bought a 1.2m home in Markham, his Real Estate Agent told him it was a great time to buy.

    God bless this new immigrant. Actually God bless the market that will be dragged down by these simpletons.

    • Dennis 7 years ago

      This is a from The superintendent of OSFI Oct 03, 2017

      “We think that the system as a whole needs to have a certain integrity,” Rudin said.

      Hint Hint…..More Fraud to be revealed? More Home Capital Issues? Maybe Equitable group..?

  • Heem Feen 7 years ago

    Thanks for this valuable insight Stephen ! This is food for thought
    Now I’m eagerly waiting for part 2 when you talk about if home prices will come down, or should people be scrambling to get into the market. Bring on the forecasting and the new model you’re working on (median credit market exhaustion)

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