Data-Driven Real Estate Investing – Stefan Tsvetkov

Real estate investing is all about trends and numbers. By adopting a data-driven approach in your deals, you can increase the likelihood of securing handsome profits. Exploring this strategy with Ava Benesocky and August Biniaz is data scientist Stefan Tsvetkov, founder of Realty Quant. He presents his database full of relevant real estate information to help investors navigate overvalued states, grasp the immense impact of inflation, understand fluctuating interest rates, and a lot more. Stefan also shares how he transitioned from a financial engineer to a multifamily investor, analytic speaker, and live webinar host.

Get in touch with Stefan Tsvetkov:

LinkedIn: https://www.linkedin.com/in/stefantsvetkov/

Company: https://www.realtyquant.com

If you are interested in learning more about passively investing in multifamily & Build-to-Rent properties, click here to schedule a call with the CPI Capital Team or contact us at info@cpicapital.ca. If you like to Co-Syndicate and close on larger deal as a General Partner, click here. You can read more about CPI Capital at https://www.cpicapital.ca/ #avabenesocky #augustbiniaz #cpicapital

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Listen to the podcast here

Important Links

• Stefan Tsvetkov – LinkedIn
• RealtyQuant
• When Genius Failed
• Finance Meets Real Estate – YouTube
• https://www.RealtyQuant.com/analytics

About Stefan Tsvetkov

Stefan Tsvetkov is the Founder of RealtyQuant (https://www.realtyquant.com), a company that brings data-driven and quantitative techniques to the real estate industry. On a mission to add industry value through education, investment, technology, and analytics.

Financial engineer turned multifamily investor, analytics speaker, and live webinar host. He holds a Master’s degree in Financial Engineering from Columbia University, and during his finance career managed ~$90 billion derivatives portfolio jointly with colleagues.

Featured on multiple Podcast and Webinar events including Elevate, Best Ever Real Estate Show, The Apartment Guys etc. Host of Finance Meets Real Estate webinar series.

Data-Driven Real Estate Investing – Stefan Tsvetkov

In this episode, we’re joined by Stefan Tsvetkov. We’re excited to have him. We’re switching roles. We were on his show and then he’s on our show.

He’s going to talk about a topic that I’m very interested in. I’m a very data guy, data-driven analytics, and what have you. Someone’s going to be talking about that. We had the privilege of being on his show. He’s created something great. He’s got a live format, a Meetup online webinar show where he brings on tremendous guests and people whom I’ve learned a lot from. I invite you to follow Stefan.

We’re going to have his LinkedIn and other ways you can get in touch with him but sign up for what he’s doing because he’s doing tremendous work. We’re glad to have him on our show. There were a few times that we missed getting him on our show so we’re glad to have him here and explore this far. Also, to ask this data scientist, what was it about real estate, multifamily, or our sector that piqued his interest? I’m interested in getting into that but maybe we can tell our readers a little bit of background about Stefan and we get right into it.

Stefan is the Founder of RealtyQuant, a company that brings data-driven and quantitative techniques to the real estate industry. He’s a financial engineer turned multifamily investor, analytics speaker, and live webinar host. He holds a Master’s degree in Financial Engineering from Columbia University. Welcome to the show, Stefan. Thanks for being here with us.

Thanks. It’s a pleasure to be here.

Getting Into Real Estate

Everybody wants you to tell us about your background and your start in real estate, please.

I had a career in finance before for about a decade. I was trading a large derivatives portfolio together with a few colleagues of mine. It was a $90 billion portfolio for a financial institution. I’m Eastern European originally. I am Bulgarian myself. I came to the States when I was 22 for my Master’s. It’s a pretty standard thing at the time. I continued a career in finance. In the past few years, I’ve been an investor in the New York City area and have been transitioning to commercial multifamily in the Midwest.

It’s unfortunate that there is a brain drain taking place from places like Eastern Europe, the Middle East, other places in the world, and Asia. A lot of times people gravitate to North America, the US, and Canada. It’s unfortunate for developing nations but the reason I’m bringing that up is all of these great minds are coming over like Stefan but something about multifamily and this space piques his interest. We want to find out what was it. Talk to us about your transition or what was it about the space. You’re already involved on the equity side of things but what was it about real estate? What was that connection?

It was always like when you study finance, you’re taught that you cannot make money essentially because you’re told things like efficient market hypothesis and stuff like that is essentially difficult. You need to have very large volumes, good IT capacity, and so forth to achieve it. It always felt discouraging to me in that sense as far as entrepreneurial endeavors.

For me, the motivation was, “Let’s find a market. It has to be a private equity market of sorts where I can find efficiency and use data like I could do.” Also, find efficiency and opportunities this way. That was the main motivation. At first, I house-hacked a house twenty minutes from Times Square and so forth. I liked it. I’ve done some short-term rentals also in New York City as a personal investor. That was what spiked my interest initially while I was still working on my W-2. I thought, “It’s good returns. There are lots of marketing efficiencies so let’s utilize that.”

Kudos to him for coming to the US and living in New York City. That’s quite a busy place to be and real estate’s very expensive there as well.

How Data Comes Into Play

Talk to us a bit more. You are investing on the personal side but at what point do you see the potential that your expertise and data could assist you in real estate more on the larger side? Talk to us about how are you involved and how data comes into play.

I am the Founder of an analytics company called RealtyQuant. We have lots of in-house analytics for commercial and residential real estate on the property side. We also have some market analytics that focus on downside risk and forecasting appreciation. What was the interest for me in that space? If we take for instance commercial multifamily, what is data-driven investing there?

Compared to the more standard-like approach of, let’s say you have a multifamily syndicator, they pick their market based on job growth, population growth, income growth, and so forth. Here, it’s more statistical market studies that are trying to guess the best market as one aspect or the best appreciation. They’re also trying to gauge and do some risk management on it. They’re trying to see, “What is the downside in various markets in the event they go over borrowed or not?”

That’s the market side. It’s more statistical and has actual predictive power. It’s not just growing but translating into prices and so forth. That’s as far as on the market side. On the property side, there are various technology pieces. Let’s say for commercial multifamily, one thing that I do is pull tons of rental listings data and try to model out which buildings, however many units they have, 50, 100, or 200 units, what value-add would they have?

A fairly unique approach I would say, at least, I have seen it in the industry is where you try to utilize rental listings as preliminary income expense information on those properties and model them at scale. I did my webinar and did a lecture where I was showing you can do this. They were modeling about 32,000 commercial multifamily properties and having them ranked in different cities. The benefit of this is how you source your deals.

It could be agent relationships, primarily, I’m sure especially in private equity or different direct owner campaigns and so forth, or perhaps speaking and going to a coffee shop with the owner or something like that. However, in whichever way, it’s based to have this kind of preliminary intelligence of which are the priced assets in your market or the ones that show the most potential for value-add. This is an example of financial modeling in the real estate industry.

There are other technology pieces. If you want to do underwriting on multiple deals, there’s automated underwriting, which has all your cap rate, cash on cash, and IRR computed. However, to achieve it, there’s also a part where you need to have an acquisition analyst to read all your property, look at all the images, and so forth. All of that gets done with machine learning. It can be done in another data-driven thing.

For example, RealtyQuant has an NLP or Natural Language Processing algorithm that can read descriptions and classify property conditions approximately based on that. What condition is the problem? It’s very approximate and preliminary but allows you to do this kind of preliminary analysis at scale. Those are some examples. It’s machine learning, statistics, and looking at more data.

Region Analysis

When you are doing analysis on a region, collecting data to put into your system, and figuring out if it makes sense for a real estate private equity firm to invest within that region, how do you compete with the RealPages and Marcus & Millichap who are out there because of their large volume property management firms that data comes directly to them? They don’t have to go research it. What are doing apart from these large Goliaths in the business?

To your point, they might focus on a specific market, their personal relationship, and so on. To me, it’s a layer. For instance, in the commercial multifamily example, I layer financial modeling on top of it. They can do it. It’s just that I haven’t seen it being implemented. It’s like, “Are you able to find motivated sellers? Are you able to find all those lead generation based on the likelihood of a sale like expired listings, and so on?”

That’s what is there in the space but they haven’t seen much financial modeling for buildings that are off-market because most people would say, “Why are we going to do it? Why financially model buildings that off the market?” However, to me that allows me to pick the best assets in every market and then have good knowledge about the markets so I can look at the top buildings in every market and be more geographically diverse.

Are you doing this research on these buildings proactively without anybody coming to you for the services?

For commercial multifamily, we have the data for pretty much every market in the country as far as that but it hasn’t been released yet, to be honest. I’ve been busy and I haven’t released this product.

We can’t get our hands on the data quite yet.

On the property data, what we do have that is available is what they call market valuations. This is a very interesting concept. August, you have it in markets and you have all those big companies like the Blackstone Group and so forth. They can do all that stuff. They hire so many smart people and they can do anything. However, in reality, you don’t see everything being done.

One thing I see underutilized in the industry is the fundamental analysis of markets. For me, having a market valuation based on the fundamentals of income population and housing supply is essential to a private equity firm. Idaho is an example. I’ve spoken in Idaho since 2020. Idaho is a very booming market. If you listen to Niels Bohr, Boise is the best-performing city in America this market cycle.

We were talking about Boise, Idaho. We had a guest on our show who was there. It blew my mind because he was saying that the market prices are about 20% to 30% higher than in a place like Dallas.

We’re shocked to hear that but keep going, please.

That’s a very interesting example. Let’s say Boise has the highest appreciation. If you pull 800 cities in America and look at this market cycle, since the last fair valuation, Boise is number one. With that being said, Boise is very overvalued when you pull its population income, housing supply, and fundamentals. Where prices should be and are now, there are different estimates. There is Moody’s Analytics by Mark Zandi. He is one guy. They came up with a 73% overvalue for Boise.

My model has it at 66% but pretty much, everyone’s consensus is that Boise is the most overvalued city. It’s funny because it’s a pretty consistent observation but to use it as an example with Idaho, there is an influx similar to other Western markets like the small Western states with the collection of markets there. It’s a small state comparatively. The impact happened to its pricing but it is excessive. This fundamental analysis tells you, “You can project where prices are,” if we are assuming we enter into a recession.

Data-Driven: Fundamental analysis allows you to project market prices in case a recession happens.

A comparison point for Idaho is I did a study of the prior recessions. 1990 was a very interesting recession where real estate didn’t decline but nine states were overvalued at the time and did decline. One example was Hawaii at the time. Hawaii was overvalued at about 48% in fundamental analysis. It’s very interesting what happened. The economy continued strong and the income continued to be very strong. That’s a potential scenario for overvalued markets.

In Hawaii, it was 48% overvalued. It declined only 14% but it doesn’t so much matter whether it has a sharp correction over the longer run or it has such a small correction such as 14% because it took it 8 years and 1 quarter to drop 14%. It’s to give a perspective of how underperforming or overvalued markets can be assuming we hit a recession. This is a very important thing. It’s like in forecasting prices and so forth. For people who have done incredibly well in Idaho, it’s to understand that you have a state in this case that is 53% overvalued. I updated my data on that.

In all likelihood, its valuation is going to converge to zero and even negative. In the history of 45 years, valuations have always been resolved every single time. If we take the global financial crisis, there were many overvalued countries and it rounds to 0% of counties that remained overvalued at the bottom after GFC. That’s an example. It’s 11 counties out of 2,700. It’s quite impressive with this kind of fundamental analysis.

It’s very statistically predictive. It worked for the 1990 recession. It worked for the 2001 recession when there were no declines but there was nothing that was overvalued. It worked for GFC in 2008. It’s going to work in 2024 as well. I don’t think there’s anything that’s significantly changing as far as fundamentals. Some things are changing as far as what drives the error term of freeway state. The overvaluation is driven by all those different things but where prices should be in my opinion is not.

This is another aspect that I’ve been speaking to different syndicators. They did a lecture for another private equity fund where they changed their strategy and decided to invest in only Midwest secondary and tertiary markets. That’s a very conservative strategy going that far but it’s this perspective where it doesn’t mean if something is overvalued. It’s going to decline much but it affects your growth. It’s like the Hawaii example in 1990. There’s no crush on real estate whatsoever.

I have a couple of questions for you. Who is the end user of your data? Is it real estate private equity firms like us? Could it be used by brokers? Who is your perfect end user for the analysis that you provide?

I would say real estate investors, investment managers, or both. It could be retail or larger groups as well.

In your analysis, you talk about how some cities are overvalued and you used Boise as your case study of how it is. You made a comparison where it doesn’t always correlate just because something is overvalued. If it is going to have a massive correction, then the same overvaluation I understand that conceptually. In the research you’re doing, especially since the last few years, there’s been such a hypergrowth in so many different regions. Is there a city that stands out in your analysis like, “This city has tremendous potential for growth?” What is your topic city when it comes to all this analysis that you’re looking at?

It’s not as attractive as you might think, August, unfortunately. I feel like when we’re further into the market cycle, all the well-performing cities go a little bit overvalued if not much. As far as places that are fairly valued, they’re already in the Midwest. It’s not particularly attractive in that sense. There are no Southern and Western cities that I would label as undervalued or even fairly valued as far as the exact data that goes on that.

Is it fair to say the number one overvalued city is Boise then?

It’s number one consistently across Moody’s Analytics. For the Atlantic University study, it’s what I have as well. From there, Western states are more overvalued than Southern ones. Midwest is fairly valued and then the Northeast for its legitimate weakness and policies is undervalued because nobody wants it. It is something like that. California is fairly valued in fact.

Impact Of Inflation

Another thing is when you talk about data, a lot of data that groups like you collect comes from rent growth where you can visually see it in the market. It comes from sale prices. There’s a lot of data out there that you can collect that is factual but also, inflation is something that we’re dealing with. How does that come into play when you know that inflation is there? You also got the increase of interest rates that are continuing.

How do inflation and the increase in interest rates that are happening to fight inflation come into play when it comes to the data that you’re collecting? Can you also see, “Since the inflation is going to be here and the interest rates are rising, how could that affect the growth you’re seeing in certain cities?” Is that in any way a factor or that’s aside from the data you’re collecting?

August, you do great work with real estate private equity articles on LinkedIn. I’ve read some of that and it’s great. You know that the Fed hikes interest rates to fight inflation but then they do it until they can’t fight it. At some point, the economy does not allow it anymore, then it stops. Ultimately, the way we know we are in a recession, even the COVID recession, there was a three-month very short recession. I was trading interest rate derivatives in finance at the time. With my colleagues, we knew we were already in a recession even though it wasn’t measured. There was a huge plummeting and going down in interest rates.

If you look at all historical recessions and inflation, even when it was extremely high in the ‘70s, ‘80s, and so forth, inflation sharply goes down in a recession with the slowdown of economic activity. It’s a little bit of a self-correcting mechanism where commodity prices are a big component of inflation and they drive the CPI number up but then we have essentially a self-correcting mechanism where that then leads to slowed economic growth and activity so to say and then it goes down. I’m not particularly sure if interest rates are becoming extremely high because they will but then in the event we enter a recession, they would go down.

That’s at least what the history in the past suggested. That was even during the COVID very brief recession and so forth. As far as I know, there’s so much money supply, and then asset prices go up. There’s so much inflation that multifamily prices go up. My view is a little bit different on that because first of all, the money supply is true that it has driven many years of the stock market and other assets like the huge upward trend in US equities especially. However, there’s already tightening and a reverse of the trend. That’s partly what drove the stock market down, especially technology stocks. It’s small-cap technology stocks.

For one, the money supply is on a downward trend already. You see to what extent or how much down it’s going to go but that is one discussion. Second, inflation to me drives assets overvalued. If you don’t have income and don’t catch up with inflation, you have an overvalued market. I saw it in 2021. The US real estate was fairly valued even through the first quarter of 2021.

When I was at events like this one, US real estate was fairly valued. You guys are Canadian. Canada was overvalued for a long time. Sweden, Canada, Australia, Norway, and New Zealand are commodity exporters. They have independent central banks. There was the commodity crunch of 2014 and 2016. The central banks cut interest rates. It’s pretty consistent in these countries that are in very different locations and places but their independent central banks can’t cut interest rates in response to the commodity markets so they have very overvalued real estate.

That’s one observation by analysts that they have very overvalued real estate. Bloomberg Economics published a study in 2019 and then at the beginning of 2021, they published it as well where those countries with real estate for instance are very overvalued but US real estate was fairly valued. That’s what I was seeing as well in my data. It’s quite interesting because many investors feel like it’s expensive but when you look at the fundamentals, it was fairly valued.

In the middle of 2021, this started to change and it’s been changing quarter after quarter with inflation and essentially going more and more overvalued over a very short time. That is to me the effect of inflation. To me, inflation is not something fundamental. Inflation is going to go down. With the recession, eventually, there is a self-correction to it so to say but it does lead to overvaluation. This is what I saw and it did lead in the second and third quarter of 2021 to some overvaluation. I don’t mean to say that US real estate is extremely overvalued. It’s nothing like Canada in that sense or New Zealand. It’s still relatively favorable but it’s been getting more and more every quarter.

Taking Overvaluation Into Consideration

Is overvaluation a metric that investors should strongly look at before making an investment in a region?

Yes, that’s my opinion because they should look at it as much as they look at population growth for instance. If you look at the predictive power of population growth for the upside, it’s 40%. If you look at the predictive power of overvaluation for the downside, it’s in the 70% and 80%.

Data-Driven: If you look at the predictive power of population growth for upside, it’s 40%. When looked at the predictive power of overvaluation for downside, it’s between 70%-80%

Is it 70% inaccuracy of the overvaluation?

Overvaluation to subsequent decline is at 85%.

How do you see a term on that? Let’s say you look at a city. We use Boise as a case study here. Let’s say it’s 53% overvalued. That’s the number you were saying. Does that tell us what the term of the correction is? If it is overvalued now, could that correction be done in the next six months, next year, or the next five years? How does an investor know, “This region is overvalued but how much time do I have?” In some cases, groups like us can exit in three years. Tell us about that.

It doesn’t tell you the time itself in that sense but what one needs to do if one wants to get as close as possible to the timing is it’s not about the price side or the overvaluation. One needs to forecast the fundamentals of that market such as if it’s within a recession. For instance, speaking of the 1990 recession versus the GFC, it’s not that the GFC was an enormous crash of real estate in itself because it was inflated by all those credit conditions and so forth.

There was an overvaluation for whichever reasons that could be those, let’s say but it’s the fact that markets declined as much as their overvaluation. Let’s say California and Florida were 40% to 50% overvalued. That’s how much they dropped pretty much. There was a full correction because the economy was weak so incomes didn’t perform well. That growth was not there over the next four years. They ended up with a very big correction.

In 1990, there was a very big income growth afterward. In whichever markets, states, or counties that are overvalued end up with 1/3 of the overvaluation’s correction. It comes down to forecasting fundamentals and the economy. That’s the hard part. I don’t think it’s a question of prices or incredibly stochastic or uncertain things as far as if something is overvalued, what’s going to happen to that? The overvaluation will resolve.

If there are stronger fundamentals, we will resolve with a smaller correction. If they’re weaker fundamentals, we will resolve with a bigger correction but it always in the end goes to zero. It’s very interesting. It doesn’t only go to zero. It goes to a little bit negative. Following a recession takes years. For instance, after GFC, the correction took 4 years and 1 quarter on average.

After 1990, which is not even considered, there was no decline in broad US real estate but in specific states which were overvalued at the time, it took five years to correct. It takes a long time generally most of the time. I don’t think it’s something quick in that sense but it could be if the economy continues very strong. It could be a very small correction, which they think is what most people hope for or expect that we get a smaller correction.

I’m understanding the concept of overvaluation. When a certain region is overvalued and that has been proven by multiple sources, there’s a 70% plus chance that that is the case. That is a correct assessment that is overvalued but at what juncture does it become factual? Let’s say Boise is overvalued at 53%.

A lot of different groups including yours say, “Yes, it is overvalued,” but at what point does it have to go through a correction for you to say, “Yes, we were right?” Regarding the other 30% or approximately 30%, was it that they weren’t as overvalued as much as anticipated or did it go the opposite way? Did it go from overvalued to undervalued? Have those swings ever happened?

In the first part, it’s whenever the economy slows down. That’s the short answer.

It’s like the litmus test of overvaluation that can an overvalued region survive an economic downturn.

It’s all to an extent limited history but what I do is work at those past recessions. In the past recessions, it’s been the case. That stuff that was overvalued after a recession took 4 or 5 years. For some regions, it could be shorter. For some, it could be very long like over eight years. Following an economic slowdown, overvalued regions typically change direction. You see the evaluation quarter after quarter goes down. That’s been the least for the past recessions.

That’s what I would expect to see. If there is a stronger recovery so to say, then the correction ends up being the residual amount of how big the recovery is in fundamentals and then the prices and the recovery meet at some point a few years into the future. That’s what I think generally happens. It is extremely complicated in the stock market to do this kind of analysis.

In the stock market, you have earnings. Earnings are uncertain. You don’t know what earnings are. You have so many drivers. If you look at all the different measures in the stock market of how valued the stock market is like Tobin’s Q, there are different measures there with price-earnings ratios. They’re not even close to each other. It’s very difficult. In real estate, it’s much easier it seems because you have fundamentals of population income and housing supply driving real estate. It deviates from that. Usually, it resolves into the future mean or reverse. That’s to that question.

If something was undervalued to go then undervalued, yes. It’s like the GFC. I worked in 2,700 counties. Out of 2,700 counties, let’s say many of them, and I don’t remember the percentage that was overvalued at the peak of 2006, declined. Years later, we’re at the bottom of the market. You measure the valuations of those counties. How many are those counties are still overvalued? It’s 11 out of 2,720 counties. It rounds to 0%.

Is that four years after 2006?

Yes. In the end, if somebody thinks, “If something is overvalued, it’s going to stay overvalued in the event of economic slowdown,” I don’t think so. It’s not what I’ve seen in the data. Everything in the end resolves. That resolution can be very soft as we discussed. It could be even 50% overall but it drops only 10% because it has such a booming economy afterward and incomes catch up.

Let’s say four years later, there’s a 10% drop, and the increase in incomes for instance matches. That’s possible. I don’t have some doomsday discussion that something is over or it’s super negative but it’s a consideration where it’s going to need stronger fundamentals and it’s something that is super overvalued. That’s why I’ve been worrying about Idaho the most. If something is to such an extent overvalued, it could decline very little but you have a state in that case that has been declining for 8 years at 14% and all the other states increased 50% in the meantime, or some of them.

The Hawaii case study is the perfect one that I mentioned. That’s a significant underperformance. I do expect if there’s an economic slowdown to see some of the very booming places. If they’re overvalued, they will underperform. It happens then. In the next cycle, we’re going to see, “Which are the ones that emerge?” That’s hard to predict in that sense but it’s a good question. If something’s overvalued, it also always goes to zero at some point. It could take a long time. Undervalued markets usually are weak. They’re undervalued for a reason. It’s risky to invest in them but in the end, they also go to zero. It’s a constant ebb and fall.

Any correlation between undervaluation and cap rates?

In this analysis, there isn’t such good commercial data for me. You can use CoStar but I cannot do it for every single market. This is very important to know. This is Just US Housing. This is not a commercial multifamily. I did a simple study that showed a 91% price correlation over the one grant between the CoStar Commercial Multifamily Index and Just Housing.

Over the one grant, they have a strong correlation but as you know, it’s different. You will have a different effect. Commercial multifamily could drop much less but it could also go the other way. It’s harder to gauge that. As far as cap rates, it is a measure of price in commercial or multifamily in a way. I haven’t done this study so much.

Reality Point

Last question on this and we’re going to move on here. If an investor wants to know about the valuation of the region, and for example, you’re talking about the counties that get granular to the point of the county as far as overvaluation or undervaluation, what is the fastest way they could see if the region they’re looking to invest in is overvalued or undervalued?

The fastest way is through the website RealtyQuant.com. We have the data.

I have a question for you about RealtyQuant.com. Is it a subscription that somebody would have to pay to get the data?

It’s like buying the data one time and then you get lifetime free updates. You get updated every quarter. It’s quite nice because if it is something that’s fairly valued now, it could change in the future so you get on our email list and keep getting updated if it changes or something like that.

Could groups like us, the real estate investment firms, retain your services to give a report about a certain region we’re looking to invest in and even more focus on a certain asset so that we can use that as part of our presentation to our investors and why we believe so strongly about this asset in this region?

I am a financial engineer in my prior career so I do the equivalent of consulting and that would be in finance. I advise groups sometimes ad hoc on market analytics, property analytics, and so forth. If they’re interested, they can reach out to me as far as advisory services of sorts.

Our conversation took a different or unexpected road. Is there anything else that you would like to share? Do we have some time for you to share any of those?

It’s okay.

Tell us what else. I’d love to learn more.

What else can you share with us? Before we go to the next segment of our show, is there anything else you want to add?

We covered quite a bit.

Fair enough. It sounds good.

I learned a lot from you, Stefan. Thank you.

We want to have you on again. Let’s do this. It’s the next statement of our show.

Ten Championship rounds to Financial Freedom

It’s the Ten Championship Rounds to Financial Freedom. It’s whatever comes top of mind. The first question is going to be who was the most influential person in your life?

It’s a non-conventional answer. It’s my daughter.

What is the number one book you’d recommend?

I don’t read many books, to be honest. When I was an undergrad, I enjoyed the book called When Genius Failed. It’s about the Russian debt crisis and the hedge fund called Long-Term Capital Management.

When Genius Failed: The Rise and Fall of Long-Term Capital Management

If you had the opportunity to travel back in time, what advice would you give your younger self?

It’s to get into private markets sooner.

Wouldn’t we all wish that we could have started it sooner? Whatever it is, we should have started sooner but that’s okay. That’s life. Stefan, what’s the best investment you’ve ever made?

The best investment has been my education and technical skills. When I was an undergrad, I was always like, “Should I go the more technical route? I’m pretty sociable. Should I do something more with people skills and so forth?” However, I feel it went well that I did that so I studied Math at the time and then went into financial engineering. It was hard for me to in a way go that route at the time since I had other personalities but that was the best investment.

It was an investment in yourself.

I would say technical skills. I’m Eastern European. I’m a fan of technical skills. I like hard skills. Otherwise, it’s just noise and talking in a way.

What’s the worst investment you’ve ever made? What lessons did you learn from it?

My Master’s was very expensive. Studying in the US is expensive. It’s also good in some ways but many people pay so much for tuition that they regret it a little bit at least.

Can we call it overeducation?

Overeducation was the worst but the best thing you’ve ever made. The next question is how much would you need in the bank to retire now? What’s your number?

I don’t know. I haven’t thought about it. I don’t want to retire. $10 million maybe is fine or something like that.

It’s probably the most common answer we get.

If you could have dinner with someone dead or alive, who would it be?

Elon Musk perhaps.

You will learn a lot from him. That would be fun.

He parties hard so you might be pretty wobbly by the time you leave that dinner.

The next question is if you weren’t doing what you’re doing now, what would you be doing now?

If I was retired, I would be writing. I would be a writer or something.

What types of books?

Nonfiction like Philosophy. I’ve done it a little bit but just as a hobby.

Stefan, book smarts or street smarts?

I’m technical but I don’t read many books. I’m not a big reader so I guess street smarts.

The last question is if you had $1 million cash and you had to make one investment, what would it be?

It would be real estate. That’s pretty obvious. Own real estate that you control yourself. That’s what it is.

He knows the best places to invest in. He knows all the unicorns out there so he knows exactly where to do that. He is like, “I got it all right here.” We appreciate you taking the time to be here with us. We wanted to keep asking and asking.

I learned a lot. Thank you. We can’t wait to have you back.

One last thing is we always talk about a lot of the KPIs and metrics we follow, job growth, population growth, income growth, and rent growth. The overvaluation is going to be another metric that we’re going to aggressively look at next time we make an investment into a region. Thank you for that. I appreciate that. The last item is what’s the best way people can reach out to you and what you’re offering. If it’s a website or however else, please let us know.

It’s RealtyQuant.com. That’s my website. They can also reach me on LinkedIn and I have a YouTube channel Finance Meets Real Estate on YouTube.

We appreciate you being here. Thank you.

Thanks, Stefan.

Thank you so much.