I am so excited to welcome Stefan Tsetkov to the show. Stefan is the Founder of RealtyQuant at RealtyQuant.com. It is a company that brings data-driven and quantitative techniques to the real estate industry. They are on a mission to add industry value through education, investment, technology, and analytics. He is a financial engineer turned multifamily investor, analytics speaker, and live webinar host.

He holds a Master’s degree in Financial Engineering from Columbia University. Entering his finance career, he managed $90 billion of derivatives portfolio jointly with colleagues. He was featured on multi podcasts and webinar events including Elevate, Best Ever Real Estate Show, and Investing in the USA. He is the host of the Finance Meets Real Estate webinar series.

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Welcome to the show, Stefan.

That was a great introduction. Thanks for having me.

Tell us a little bit about you. Give the executive version of how you got to where you are investing in real estate and why you love talking about analytics.

I’m a financial engineer. Originally, I’m Eastern European. I came to States. I went to Columbia and New York for my graduate degree. I worked in the financial industry for about a decade. In the last couple of years, I’ve been a real estate investor as well as a founder of a technology analytics company in the real estate industry called RealtyQuant. I took on analytics related to that. We publish market evaluations as to how over, under, and fairly valued our different markets are. We also do data-driven investing and build different technology and tools in the industry for that.

We’ve had one person come on and talk about data-driven real estate, but he wasn’t an analyst. This is exciting. Don’t be shy about talking about numbers. We can handle it. I’m super excited to hear how you run this. First, let’s define data-driven real estate investing.

It incorporates different data science or technology techniques for investing or discovering inefficiencies and opportunities in the real estate market. A big part of that is automated underwriting. Automated underwriting where you can pull thousands of on-market and off-market listings and underwrite them even to a partial extent. Later, you would perhaps need to go to the property in person, but it is still this preliminary analysis.

Automated underwriting is a big part. To that, there are different machine learning also that comes into play a bit. These are things like computer vision where you are able to see real estate images and define the condition of those properties. You can define the condition scoring based on real estate images or texture descriptions and also extract other intelligence from texture descriptions.

There’s also financial modeling for off-market inventory in the commercial multifamily space. That’s very useful. It’s a set of techniques for finding deals and markets. On the market side, it’s also engaging valuations. It’s having appreciation predictors and downside predictors for your markets. That’s so very useful in the commercial multifamily space. In residential investing, you’re able to gauge markets and pick the best ones. That’s what data-driven investing is. It’s a slightly different approach than the more local real estate investing, and there are good reasons for that such as you want to be vertically integrated. You want to have your team within a location. You want to understand that location really well.

Data investing is more agnostic to that. Thus, you try to gauge those markets somewhat in a bigger way. You’ll be able to scale and do this anywhere in the US. That is the difference. It’s also getting your own intuition with the data rather than reading reports. That’s not data-driven in my mind. If you’re purely working on reports, it could be, but it’s a little bit hard without also interacting with the data yourself or an analyst on your team doing it. It takes bigger insights with that.

With the reading of reports, do you think it takes more insights?

Yes. It takes more than a summary reports of what are the best markets in the US for this and that. In my experience, at least, you need the whole data for the whole US everywhere. It’s a bigger endeavor.

How did you get started investing in real estate? I want a little bit of context. How did you get started and why did you move from where most of us are where we’re looking at reports or listening to the news? We’re trying to invest locally because those are markets that we understand. That’s the more intuitive way that most of us invest, and you moved to more data-driven. Could you give us a little bit of your journey? How did you get started, and how did you get to where you are?

I’m in New York. The first property I bought was with a house hacking strategy. Many people are familiar with that. I bought a multifamily post in New Jersey. I lived in one unit and rented out the other one. I thought it was working well. There was a beautiful discount on the price as well. I thought, “I should work into it more professionally and find investment opportunities as a professional investor.”

From there, I started as a residential investor doing condominium conversions in the New York City area and other projects. I started pulling lots of data. I pulled perhaps 6,000 on-market and off-market properties within three hours from New York City and would have them underwritten on different strategies. It’s not only that, then you can compute your cap rates and different things like that. You can also underwrite on strategies that are otherwise hard to think about at such a scale for so many properties such as condo conversions or perhaps converting a residential to a commercial property. That was the way I started.

I’ve been doing residential deals in the New York City area in the small multifamily space that are close to markets like downtown Jersey City and WeHo which are very close to the city and some in upstate New York. From there, I’ve been transitioning to the commercial multifamily space in the Midwest and working for different deals in places like Iowa, Minnesota, and more fairly valued markets at that time.

When you moved out of New York is when you started becoming more data-driven. Is that true?

No. I am still physically in New York. I was data-driven when investing around in the New York City area as well. We pull residential listings for many. When you’re transitioning to commercial multifamily, the market side becomes more relevant because you’re not in your local market. You want to pick the best markets out of state. There are also concerns about whether they are overvalued or if we are going to have a recession. That prompts some of that analysis on the market side.

That’s a perfect segue. Let’s talk about how to determine if a market’s overvalued or what is the downside risk. Let’s talk a little bit more about that. 

That is a million-dollar question if you think about it. Think ahead of the global financial crisis. Ahead of the global financial crisis, there were investors who invested in, for instance, California or Nevada. Those had a 50% decline, roughly speaking. They were extremely successful investors. That’s more speaking to the residential single-family space for this discussion because the commercial multifamily market is a bit of a different dynamic with cap rates and so forth.

Some of those investors lost all their networks. They were not the biggest investors, but the biggest people you watch in podcasts in the US. They were extremely successful and they were extremely successful with their operational process. They knew how to find deals, yet, they lost a lot of their network. The reason is those markets were extremely overvalued.

On the contrary, there are others. One of the bigger syndicators purchased his property in Midland, Texas. It was his first syndication. It had a super huge return. The reason is that Texas was undervalued. That’s ahead of the global financial crisis. This is a backward discussion. It was undervalued at the time that didn’t decline. They did decline but at a 4% average. They declined very little. They declined on their income, but on valuation terms or normalized terms, they didn’t.

I want to stop right there quickly because you’re going fast. It’s super awesome. You’re coming in with a lot of good stuff. I want to highlight some interesting things that you said. Which decline are you talking about? Do you talk about 2008 and 2009?

Data Driven Real Estate: You don’t just get to compute your caps and different things like that, but you can underwrite on strategies for properties that are hard to scale.

Yeah.

That’s what you’re referring to. I’ve been through three of them, so I want to make sure I knew which one you were talking about. In many of the markets in California, we were overvalued. I tell this story on my show many times. In 2009 and 2008, I lost 50% of the valuation of my properties in a period of three months. Things dropped so fast. When you go to a market like what he’s talking about in Texas, it’s not overvalued. It still did have a response to the crash, though, but it was only 4%. That is what he’s quoting us at.

It doesn’t mean that the other markets don’t move, but it’s a gentler move down. The correction is much easier to make that happen. In California, we saw a correction. It took about 6 or 7 years, and not all markets recovered. Only some of them recovered. Location was a big deal. I don’t know the rest of the country, but based on what you said, I wanted to point out that it’s not that because you’re in a low-risk market, you’re not going to see a drop. It’s that it’s a much gentler drop in response to the national or international crisis that we had.

Some markets in North Dakota at the time could see no drop as well. They could see zero drops. That was during the global financial crisis. Since you asked me what is the definition, the definition is price deviating from fundamentals of income population and housing supply. This is a fundamental analysis similar to the stock market.

I did a back study for the past three recessions. The global financial crisis is 1 of those 3 recessions. The correlation for the Metropolitan Statistical Areas or MSAs was of decline with the market evaluation and the peak ahead of the global financial crisis. Price decline peaked to bottom over the next roughly four years and one quarter on average. There are different periods in different regions, but those are declines that took four years forward. The correlation between the magnitude of decline and valuation was 89%. That’s huge. Declines were predictable in magnitude ahead of the global financial crisis.

There were people who were talking at that time. I don’t want to go into too much detail. He was a guy from Massachusetts. He doesn’t come to a local market monetary but he was on CNN in 2005 and 2006. This is practiced by the Quadrants Institution and done by Moody’s Analytics. This is studied for entrepreneurs. It’s done by my company, RealtyQuant. For your audience’s benefit, we do publish the data for every US County. We have 2,700 US counties. We have every single county if it’s over, under, or fairly valued. That is a statistical predictor of declines in the recession. It’s an important one. I’m not sure if it’s a good time to share my screen to show a table on this.

He asked me for permission to share his screen. I said yes because those of you that are going to check this out on YouTube will get the visual benefit of this. He is going to walk us through this. If you’re audio-only, don’t worry. He’s going to walk us through this. This also might be a good time to go check things out on YouTube. You can look me up, Moneeka Sawyer, and you’ll see all the YouTube things. It’s all yours.

Thanks. Are you able to see tables in an Excel sheet?

There are a lot of numbers.

That’s a big table with a lot of numbers, but I’m going to give you the gist of it. What I’m showing here is ten years ahead of appreciation or price changes in the US. These are how different markets perform after a mild or a severe recession for ten years forward based on how over, under, or fairly valued they are. It’s the peak ahead of the recession. To repeat, this is how different markets perform for ten years forward based on their evaluation and based on how overvalued the peak of a recession goes, and how different markets perform following that.

The 1990 recession is referred to by most economists as a milder recession. The global financial crisis is a scenario for a severe recession. That is what this table shows. It’s a lot of numbers, but it’s extremely interesting. It gives a perspective for many investors. At this time, investors have had the price performance in Western and Southern markets. The first column on the table shows overvalued percentage. The valuations in some Western and Southern markets are 20% to 30%. Some are in the 40% to 50% range. That’s overvalued. I can get to that part as well.

This has a picture of the United States and all the different states and markets. We’ve got a little bit more clarity on which states he’s talking about.

I’m showing a picture of the US and what is the overvaluation or undervaluation in different US states. This is the deviation from fundamentals. The dark-colored states in the picture are to the West and to the South. Idaho, for example, is at the top. It has been reported by Moody’s Analytics and other studies. It had a consistent observation for everyone with Boise, Idaho being the most overvalued city in the US. You can even search for different methodologies by Mark Zandi, Chief Economist of Moody’s and others, or RealtyQuant in my capacity. It’s generally consistent. Boise is at the top of 800 US cities.

Idaho is over 50% overvalued. On the counter, the Northeast and Midwest are under to fairly valued. These variations have been accelerating a lot with inflation since 2021, starting with what was a fairly valued US market at that time. I know it’s a lot of numbers, but it’s extremely important. I could put a lot of work into that myself.

It’s not to get a doomsy perspective. In the Western market, Idaho, Nevada, Arizona, Utah, and Colorado are overvalued to an extent. It’s less so than Idaho, but still to an extent. I speak to investors and syndicators who say, “We think these markets have such strong fundamentals even if they have a bit of a decline for some time. Let’s say they have a 5% to 10% decline. They’re going to do well afterward because they have such strong fundamentals. There’s so much job growth there.” That’s not what history suggests. What happened in the previous recessions was markets were at the very peak of valuation.

I suppose we take either at 54% overvalued. I have a table that shows the valuation ranges of how overvalued different markets are and how they perform ten years ahead. Markets that were in the 50% to 60% range were extremely booming ahead of time. For instance, the 1990 recession is a milder session. We have nothing doomsy. Nobody even knows about this as far as the real state declines.

I know about that one. I lost 20% of my value.

It’s a very milder session. There’s nothing terrible happening in your state. If one invests in a metropolitan area that is valued at 50% to 60%, which is the case of a few metropolitan areas in Idaho and some other states, what happens is not the situation of a milder recession where the market declines quickly a little bit and jumps back. What happens is the market declines a little bit, but it doesn’t jump back quickly. It takes a long time for that decline to happen. In that case, it took eight years. What is more important is, what is the relative performance over ten years of a market like that that was overvalued versus the other ones?

For instance, in this case, older markets in Metro areas that were over about 56% only appreciated a little bit. It was 16% over ten years. They were heavily outperformed by the undervalued ones. That is not intuitive. That’s not what people are imagining for Western and Southern extremely booming markets. They’re imagining that those are fast markets. The Midwest is a small market. Other places have small markets that are steady. They’re not slow and steady. They are expected to outperform another recession. It’s interesting. Undervalued markets following a recession outperform the overvalued ones. It’s important to know that the overvalued ones were also the top-performing ones ahead of the recession.

Ahead of recession correlation between how overvalued they are and how well they’re doing becomes very high. They’re doing incredible. For instance, if we go to 1990, that’s Hawaii. Hawaii was the top state at that time. They were 150% top from their previous market cycle. They were the top market. Nobody would easily imagine unless doing this kind of fundamental analysis that their prices are going to be lower 80 years later. They’re going to have the weakest price performance for the following decade. That was the strongest performer. That’s why fundamental analysis is extremely important.

Similarly, if we go to the global financial crisis, California, Arizona, Nevada, and Florida were the four big overvalued states at that time. In the table, they had the worst bottom performance consistently year after year for ten years ahead. That’s extremely important. On the contrary, if someone invested in undervalued markets at the peak of the global financial crisis, they outperform. They didn’t perform great, but they still performed. Let’s say 20% over the course of ten years is extremely poor performance, but it was not negative. It was better than the others, so they outperform.

This isn’t true of the whole state. California is a huge state. There are different pockets that perform differently. It’s the same with Texas.

Data Driven Real Estate: The Midwest are small markets, and, like other small markets, they are steady. They’re not slow and steady; they are expected to outperform a recession.

These are the statistics for the MSAs or Metropolitan Statistical Areas.

What he’s saying is that, for instance, California was 52% overvalued. It went down 50% in five years, but then its recovery up to ten years took it to 25% down. It was still a negative 25%. If you look at some of these other markets that were maybe 6% or 3% overvalued, they went down initially during the crisis by 1% or 2%. One of them went down 3%. After ten years, they had gone up 18%, 27%, or 17%.

As opposed to these highly overvalued markets that are still down 25% from when the crisis started, in ten years, they’re still down 25%. In these lower-valued markets, they went down a little bit. Their recovery was not phenomenal, but at least it was recovery. We weren’t negative. We were closer to 18% or 19% after ten years.

That’s a great summary. Thank you for that. I don’t want to focus on too many numbers. It is the big picture intuition of it. The big picture intuition is valuation is extremely important in general, but it is even more important than the turning points in the market cycle. When we’re at the peak of a market, it’s the most important variable that overshadows fundamentals themselves. At the other times, I’m like, “I’m going to be forecasting fundamentals.” That’s how I get to the best appreciation. The goal of this is not a doomsy thing. My goal is where I get the best appreciation. That’s what I care about.

As commercial investors or residents, we do our forced appreciation. As good business people, we generate our business and business profit in this way by being quality investors on the forced appreciation side. That’s always there. If you do that well in a recession, you do it well in other times. You still don’t want to have the effect of markets overlaying on top of that. That is the goal here. That’s why I want to show this complicated table with many numbers. It’s to point that across different levels of overvaluation ahead of a recession where one is mild like in 1990 and one is severe like the global financial crisis, the undervalued markets is a big shift in what most investors are thinking.

Austin, Texas is an extremely booming market that has very strong fundamentals. It happens to be that Austin, Texas is overvalued. That overvaluation has to find relative to those fundamentals. Some investors say, “There’s so much housing shortage. Real estate is not going to decline because of the housing shortage.” That’s not true because housing shortage depends on how you define it.

If you take the broad housing shortage, which is the US Census Bureau total population in that market versus the US Census Bureau housing supply in that market, that is reflected in the numbers that I’m showing. They’re reflecting income and also population to housing supply ratios. Austin, Texas is the best market, but if prices run too forward, it’s going to underperform. That’s a consistent observation. There are around 400 metropolitan areas here and these are two very different recessions. Investing in a 50%-plus overvalued market, which is likely to be the top performer in the market cycle and going to have a reversal in price performance.

That is so not intuitive. You think that a strong market, once it goes through a recession, will continue to be strong. That’s very interesting. The numbers prove to be exactly the opposite.

It depends. In itself, a strong market would recover better, but that is even the comparison of the 1990 recession versus the global crisis. In 1990, why did they have markets that were over 40% to 50%, but they only dropped 15%? The reason is it’s not that the global financial crisis was a “crash” of sorts so much. It was a severe recession and the recovery of fundamentals was very weak.

I know you did mention a sharp decline in some months. I feel terrible about that. That sucks, but in the big picture, the declines took whole four years. Prices still kept dropping. With those four years of declines, what happens in a mild recession is that the fundamentals are strong and they catch up. Even though the market is overvalued more, it ends up declining less because there is a strong recovery. It’s not that one is a crash and the other one is another crash. It depends on how severe that recession is and how strong the economic recovery is from a fundamental perspective. That’s, at least, my perspective.

From this standpoint, it’s true that a strong market would recover faster. That happens in markets that may be overvalued and may recover fast and well and would get a small decline. That is possible. The question for me is not only predicting downside risk. We don’t have a recession yet. That’s all hypothetical. There’s no official declaration of a recession still, but if we were to have one, how do we forecast appreciation? Where is there going to be the best appreciation? This is suggesting that it’s not going to be in the booming ones anymore and they would underperform. The reason is valuation.

I can go overvaluations in different cities, but that is what the studies suggest. It’s a very different scenario. For instance, we had a recession such as a dot-com bubble in 2001. I’ve studied that one, too. It’s a different scenario. If we have that and there isn’t any significant overvaluation in the market, which there wasn’t at the time, then nothing happens. That’s because they’re mostly fairly valued and things continued going forward. That’s what happened. They continued going forward and then they became overvalued ahead of the global financial crisis. It was a fairly valued period.

It was very fairly valued, but we had a lot of people that lost jobs. People couldn’t afford homes. We did see the markets pull back a little bit to accommodate all those people that couldn’t get homes. Rent went way up because people’s credit got screwed up. Some other issues that happened there that did cause the market to go down a little bit, wouldn’t you say? They’re not strictly statistics.

That could have been perhaps in new listing prices or some of the more transitory kind of data of sorts. At least in the recorded statistics for prices, they’re showing no decline anywhere. It’s quite interesting.

This is the difference between real life and statistics. I want to talk about 1990. I’m sorry. I was mistaken when I said we lost valuation on that one. I do remember that. I was in college. I was listening to my dad and what happened there. I wasn’t personally involved. In 2001, I was personally involved. In 2008, I was personally involved.

In 2001, it was interesting. It was the dot-com crash. It was in Silicon Valley, which is where I lived and where I owned all my homes. This is a market-specific thing. During that time, because of the bust, so many people lost their jobs or had this weird thing that happened with stocks. If you would get laid off, you would have to exorcise your stock and then owe taxes. They couldn’t afford the taxes, so they would have to either sell their homes. There were some weird things that were happening in Silicon Valley. Your numbers are probably national.

What was interesting to me was property values dropped about 20%. During that time, they recovered very quickly. Interestingly, rents went up dramatically during that time because people that would normally buy were not able to buy anymore. When you say you look across all metropolitan areas and you didn’t see anything, that’s interesting to me. San Francisco, San Jose, and Sacramento areas are big metropolitan areas in California. They didn’t see what we saw in 2008, but they saw some discomfort. They recovered quickly, but there was some distinctive discomfort.

That is extremely interesting. If you think about real estate prices, you could have a change in value and there’s illiquidity. The price at which those transactions would happen would be lower. There could be a big decline in unrealized terms. Let’s say it is something like COVID.

What he’s talking about is what I always say. You don’t lose money and you don’t see the valuations change until selling happens. It’s all on paper. That’s all I wanted to add.

That’s the Federal Housing Finance Agency or the main government agency following US prices. The specific thing for 2001 is the 400 or so metropolitan areas in the US. There is San Jose and San Francisco. In the MSAs, they don’t have the data, but then, you did experience it in real life. That’s quite interesting.

That surprises me and confuses me a little bit. How is that possible?

It’s interesting. That’s what you observed, but on the other hand, we haven’t heard anyone else say about any real estate declines in 2001.

Data Driven Real Estate: What happens in a mild recession is that the fundamentals are strong, and they catch up. Even though the market is overwhelmed more, it ends up declining less.

What is true is that anybody that could hold, did. Rents were going up so fast. My property dropped 20% in value during those couple of years. It was not immediately, but it was over those two years. It recovered quickly. During that entire time, rents were going up dramatically, so I could hold property. When you’re talking about the numbers that are only going to show when people sell, maybe people were holding. What do you think? Is that a possibility?

Was it multifamily, perhaps?

Mine was all single-family. I’m sorry to challenge you, but it’s interesting, isn’t it?

It could be segmented in the market or possibly in neighborhoods. Still, that’s the whole MSA. As you are saying with the dot-com bubble with some people losing their jobs in some regions in Silicon Valley, perhaps some neighborhoods had declined and others still continued going up. It flattened out the metropolitan area. This is still a pretty high level for the whole metropolitan area. That one that did not have declines is another single metropolitan area. You’re making a very good point. If you’re in a neighborhood, the decline doesn’t matter. You have the same effect. It doesn’t matter what the market did. It appears that perhaps other neighborhoods did better.

What I’m learning from this is that the market went down, but then it recovered very quickly. Rents went up, so holding was easier. What I love about this is that as you talk about the market data, it showed that there was no real decline. I was in a pocket where I experienced a decline. As long as I held, I had time to be right, but it was still a good time to buy. This is such an interesting thing for people. People were asking these questions every day. They were like, “Interest rates are going up. I want to capture the lower interest rates, but markets feel overvalued. Is it a good time to buy?”

Your statistics show that even during that time, it was an okay time to buy because everything was valued fairly. Even though I personally experienced a decline and many of my friends did in Silicon Valley in this little bubble that we were in, it recovered very quickly. We were able to hold. It was still a good time to buy even then. The recovery happened very quickly even though you saw a dip. That’s what I’m taking from that. What do you think?

I agree. You’re making great points there. If we think of what we are doing here, it is a very high-level fundamental analysis. If we start making it super granular, it’s going to be working less well, I suppose. If we go to super tiny neighborhoods and try to do fundamental analysis, it’s not going to work too well. For instance, in my data counties’ predictive power is less strong than states’ predictive power, but it happened with metropolitan areas for some reason. I don’t know if it’s the quality of statistics of those versus counties.

Metropolitan statistics have extremely high predictive power. That’s a little bit interesting. I’m sure if I went to ZIP codes, neighborhoods, and so forth, it’s going to get harder because there are going to be so many other factors. You’re making a point that there is also the liquidity thing. These are quarterly governmental price statistics. If your price dropped for two months in between and jumped back to the same level, then that’s not even detected. If the neighborhood dropped, other neighborhoods increased. It is smoothened out.

On the other hand, for a fundamental analysis like that, perhaps we want it smoothened out. It’s not even going to be tied to fundamentals if it’s too not smooth. It’s like these other things that are either not fundamental. That is the thesis there. You make a great point that it is not applicable to where your property can still decline or your neighborhood can still decline. It’s the broad market.

You were talking about appreciation of the properties with these statistics. We’re not talking about increases in rents or any of that stuff. In a lot of these stable markets, rents continued to go up even though they didn’t appreciate as fast. They didn’t go down as much. Their rents went up dramatically. When you’re looking at which markets to invest in, you want to look at the statistics of whether the markets are going to appreciate whether they’re going to take a hit when the markets go down or when we have a recession. If you’ve got some markets that you’re interested in, you want to keep in mind what your cap rates are, what the rents are looking like, and how those are going up, wouldn’t you say?

I agree. That is a great point, especially for commercial multifamily investors. We’ve seen that very much in this period with humongous rent growth in some markets. Those are different dynamics. If we think of cap rates in the commercial space, they’re driven in a theoretical sense. They tie to something in finance called the Dividend Growth Model. It’s the denominator in that one. It’s the discounted cashflow analysis for commercial property. There are interest rates there. It’s the risk-free rates and then risk premium on top of that.

Also, what is reducing the cap rates is the expectation for future income growth. That would be the same for any business and valuing other companies as well. That wouldn’t be only for commercial real estate. It would be the same methodology. That methodology derives from a mathematical series of discounted cashflow analysis of any company, business, or property. Rent growth is extremely important, and that drives cap rates in a theoretically valid way. That is a whole different dynamic. We’ve seen that in the commercial multifamily space.

We see it in single-family homes, too. If you’re out there buying a portfolio of ten homes, or for me, whatever I own, we see that in the cap rates also. When we’re buying a single-family home, how is that? We want the property to appreciate, but we also want to know that we’re going to be cashflowing within a certain number of years or hopefully, right away. Those sorts of things matter. When we had our bubble burst here in Silicon Valley, it was the rents going up that saved us from having to sell because we could carry our mortgages still.

This is so interesting. I feel like we could talk forever, but we’re running out of time. First of all, thank you for all that information. You blew up my brain. I’ll have to read this again. Ladies, you do the same. There was a lot of good information. What I want to talk about a little bit is the states. Who’s overvalued? Who’s undervalued? Where are the opportunities? Where should we stay away from?

From your perspective, this is the end of the first quarter of 2022. It’s only the first quarter. The second quarter hasn’t come out yet because that’s a fundamental analysis based on the governmental statistics of income, population, and housing supply. Those will come out soon. Those take time. This is the first quarter of 2022, but it’s not going to be too different. It changes a little, but it has kept increasing. What’s important to notice is that US real estate was quite fairly valued even through the first quarter of 2021 at the broad level.

This surprises me a lot.

The way to see that at the country level is there is a study by Niraj Shah at Bloomberg Economics. He had it for different countries in 2019. It came out at the beginning of 2021 as well. US real estate has pricing combinations, for example, and that’s a good one I can explain why that works well, but in another discussion. It was around zero. That’s very contrary to some countries.

Other countries were reported to be SCANNZ Economies. That’s Sweden, Canada, Australia, Norway, and New Zealand. They were overvalued even as early as 2018. They still don’t decline because there are economic conditions. There’s no trigger for them to decline. There are low-interest rates and so on and so forth, but they are overvalued since then. That’s driven by central bank policies in water and small coast oil-exporting economies. Their real estate has been reported to be overvalued. That’s by Bloomberg Economics and other sources.

US real estate was fairly valued. I had it in my data as well that it was fairly valued. I started doing this in 2020, the beginning of COVID, on my end, it’s RealtyQuant. This is data powered by RealtyQuant.com. As late as 2021, the first quarter of US real estate at the broad level was close to 0%. If we take the US real estate broadly at this data, it is around 13% only. The whole nation would be only 13%.

It’s not a small number because if you take the global financial crisis, it’s the same government data in the FHFA data, the global financial crisis in the same one would be past 20%. That’s already 2/3 of the global financial crisis. You have to keep in mind that’s a history many years back. Most other time periods tend to be slightly undervalued. This is the material overvaluation, but that is at the whole level. The whole level doesn’t matter so much to particular investors.

If you go to specific states, it gets more overvalued. The reason is that we have undervalued states like Illinois. We have fairly valued states like New York, Pennsylvania, New Jersey, and so on and so forth. What was overvalued is Idaho. It is above 50%. Idaho has been the leader. The states of Nevada, Utah, and Arizona are above 30%. We have Texas, Florida, and Colorado at above 20%. There are, in total, ten US states in Q1 of 2022 that are above 20% overvalued. They’re all Western and Southern states. That’s Idaho, Arizona, Utah, Nevada, Florida, Washington, Texas, Colorado, and Montana.

On the contrary, if we go to the opposite end of the spectrum of what’s undervalued, I’m not saying that’s necessarily desirable. That ends up being desirable over the next decade, but not necessarily until a recession hits in that period. The undervalued ones are still the markets that are not performing well, which are Illinois, North Dakota, West Virginia, and Connecticut. They are not trending. They are poor in their fundamentals, but they do tend to carry less downside risk simultaneously in a recession because they didn’t get overheated.

Data Driven Real Estate: If we go to super tiny neighborhoods and try to do fundamental analysis, it will not work too well. For instance, a county’s predictive power is less strong than a state’s predictive power, but it happens with metropolitan areas for some reason.

Boise is at the top. There is Boise MSA and Austin. There are some other MSAs in Idaho, Nashville, Phoenix, Tampa, and Dallas. These are booming and strong markets. They’re incredible markets. They have incredible people who have made fortunes in those markets. That’s completely true. In the past few years, things accelerated with inflation. Those are some overvalued cities. It’s half at the county level. Perhaps, there are some other ones that can be based on county data as well. That’s a good list around the top ten.

The important thing to notice is it’s not that it’s predicting necessarily big declines in something. Let’s say Boise’s overvaluation is at 74%. That sounds very high. In Boise, if we experience a severe recession like the global financial recession, that would be a decline. I have predicted declines in different scenarios. If you have a GFC-like recession, which nobody expects, then the decline for Boise’s overvaluation of 74% evaluation will be 46%.

That’s if we have a huge crash in the market.

If we have a milder recession like 1990, even though it’s overall at 74%, but because the recovery is going to be so strong, the decline is only 18%. To clarify, that overvaluation is still a real thing because that 74% overvaluation is going to go to zero. It always does. It’s not that the number is fictional. Some investors might say, “If something is overvalued, it stays overvalued.” That doesn’t happen. It doesn’t stay overvalued. It will go to zero in valuation terms. If prices don’t decline too much because we have a very strong economy or strong recovery, then the declines will go about 18%.

That decline takes a long time. It takes six years. Especially for small declines with big overvaluation, it tends to take a long time. It could be even eight years forward. Over these eight years along that period of time, incomes increase and populations and housing supply ratios change in whichever way they change. Those fundamentals shift in a way that they compensate for valuation. They drive it to zero. That is a strong recovery case, but this is an example of what would happen.

We take the case of Austin, Texas. It is an incredible city with hugely strong fundamentals. Though exceeded by the pricing, what would happen to its valuation is it will be around 66% overvalued. The model for the severe recession that I have has a 40% decline and only 15% in a mild recession. Those are all possible. It’s not a doom thing. I’m a positive and eager investor who wants to continue investing my funds in a recession as well. What is important to me is how to make a model to forecast appreciation and what is the best one.

Here, it’s suggesting that even without incorporating in a model fundamental forecasting itself but purely looking at market valuation at the peak ahead of the recession, so to say, I can take the simple model and invest it in the undervalued MSAs. Those would be very counter-intuitive at the time. Those would be MSAs like San Francisco and San Jose. They were undervalued at the time with population issues and all kinds of issues.

Purely, what the history suggests from those two different recessions at different times in US economic history, if you will, is in both of those cases, the lowest markets of most undervalued metropolitan areas outperformed over a decade forward. That is extremely interesting for me. We have to keep this in mind. They were performing poorly at that peak. That’s why they were undervalued at that time. It’s a mix of those weak fundamentals. It would be below the prices or those weak fundamentals, but they do tend to have weak fundamentals.

There is a strong correlation between how strong a market is and how overvalued it becomes towards the end of a market cycle by overheating, like investors taking up more stuff there and so forth. That’s an interesting thing. For me, this is the perspective of how you forecast appreciation in those. It becomes counterintuitive because that’s shifting the whole expectation of investors. It’s also how we’re accustomed to the west and south as the booming places and how it perhaps is statistically likely to shift in the next market cycle.

That was awesome. How can people get more information? I know that you’ve got a free report. It’s the free state-level market valuation report. To get that, go to BlissfulInvestor.com/Markets. You can download that. How can they reach out to you?

My website is RealtyQuant.com. That’s the best way to reach me. They can also read my blog about some of the things we discussed. They can look up the data that we have there for 2,700 US counties. I also have a YouTube channel. It’s Stefan Tsvetkov – Finance Meets Real Estate on YouTube. It’s a weekly webinar.

We don’t have time for three rapid-fire questions. We are going to try to do an EXTRA. We’ll see how this goes. Stay tuned if you are subscribed to EXTRA. If you’re not and you’re leaving us, thank you so much for joining Stefan and me for this portion of the show. I appreciate you. I hope it was helpful. I look forward to seeing you next time. Until then, remember, goals without action are just dreams. Get out there, take action, and create the life your heart deeply desires. I’ll see you soon. Bye.

 Important Links

• RealtyQuant.com
• Finance Meets Real Estate
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• Stefan Tsvetkov – Finance Meets Real Estate – YouTube

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