RG 302 – How to Invest in the Right Deals with the Power of Data with Stefan Tsvetkov

Join us in welcoming a very special guest to our show, a financial engineer turned multifamily investor—Stefan Tsvetkov of RealtyQuant!

Stefan moved here to the U.S. at 22 from Bulgaria. He started out as a financial engineer and managed over $90 billion in derivatives in portfolios. Then, he transferred his skills to the real estate field and founded RealtyQuant, a company that brings data-driven and quantitative strategies to the real estate industry.

Stefan has been featured in over 30 podcasts and webinar events to date. Today, we have the privilege of having him on the Investing in the US podcast to talk about what goes into investing with quantitative techniques. Some of the topics we touch on include: the sustainability of the recent valuation jump in real estate, forecasting city performances, applying correlations in the market, and so much more.

Interested in becoming an Investor with Reed? Click here to join his Investor email list.

From market fluctuations to home valuations, there is so much data available for analysis in the real estate space. But the problem is that we often don’t know what to do with that data. Stefan is here to shed light on applying quantitative techniques to such a data-rich industry as real estate, and how doing so can help you invest in the most profitable deals.

So, don’t miss out on strategies that can help YOU seal the right deals. Click that ‘Play’ button now!

Key Takeaways

• Don’t invest in a market where you don’t know its value.

• Real estate is a predictable industry where data is easy to extract; you just have to know what to do with the data that you get.

• Prices in weaker markets have less exposure to downturn.

• Markets that are doing well are still going to do well; it all boils down to the measure of downside risk.

LINKS
https://www.linkedin.com/in/stefantsvetkov/
https://www.realtyquant.com/

Be Bold, Be Brave and Go Give Life a Crack!

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Reed Goossens (00:00):

Good day, good day guys. Now, before we dive into today’s show, I want to let you know that some of you maybe aware that over the past eight years, I have built a substantial multi-family real estate portfolio here in the US worth over half a billion dollars. And in that time, my passive investors have received fantastic double digit returns. And now you too can invest directly into my deals for as little as $50,000. So if you’re an interested investor, head over to Reedgoossens.com to find out more that’s Reedgoossens.com. Now back into the show,

Stefan Tsvetkov (00:41):

Don’t invest in a market just cause it’s hot or it’s trendy, but know it’s exact valuation, have a percentage, whichever way you derived it in your own approach, have a percentage assigned to it. Know its valuation, know why that matters. Where has that percentage been in before the global financial crisis, how that has affected like subsequent declines, etcetera. So, so yes, just have a measure of market. Valuation is my advice.

Speaker 3 (01:18):

Welcome to investing in the US a podcast for real state investors, business owners, and aspiring entrepreneurs looking to break into the US market, join Reed as he interviews go-geters risk takers and the best in the business about their journey towards financial freedom and the sheer joy of creating something from nothing.

Reed Goossens (01:39):

Good day ladies and gentlemen, and welcome to another cracking edition of investing in new us podcast from Los Angeles. I’m your host reed goossens good as always Abby with us on the show. Now I’m glad that you’ve all tuned to learn from my incredible guests and each and every one of them are the cream or the crop here in the United States. When it comes to real estate, investing, business, investing and entrepreneurship, each show, I try and tease out their incredible stories of how they have successfully created their businesses here in the us, how they’ve created financial freedom, massive amounts of cash, and ultimately created extraordinary lives for themselves and their families life by design. As I like to say, hopefully these guests will inspire all of my cracking listeners, which are you guys to get off the couch and get, go and take massive amounts of action.

Reed Goossens (02:26):

If these guys can do it. So can you now, as you know, I’m all about sharing the knowledge with my loyal listeners, which is you guys, and there’s absolutely no BS on this show, just straight into the nuts and bolts. Now, if you do like to show the easiest way to give back is to give us a review on iTunes and you can follow me on Facebook and Twitter by at reedgoossens. You can find the show, every podcast on iTunes, SoundCloud, Stitcher, and Google play, but you can also find these episodes up on my YouTube channel. So head over to reedgoossens.com, click on the video link, and it’ll take you to the video recordings of these podcasts, where you can see my ugly mug, but the beautiful faces of my guests each and every week. All right, enough outta me, let’s get cracking and into today’s show.

Reed Goossens (03:13):

Today’s the show. I have the pleasure of speaking with Stefan Tsvetkov Stefan is the founder of RealtyQuant, a company that brings data driven and quantitative techniques to the real estate industry. He’s on a mission to add massive industry value through education, investment technology and analytics. He’s a financial engineer, turned multifamily investor. He’s an analytics speaker and he’s a live webinar host. And he holds a master’s degree in financial engineer, nearing from Columbia university and during his finance career, he managed over 90 billion in derivatives in portfolios. I’m really excited and pumped to have him on the show today to share his incredible insight and experience with us, but enough outta me, let’s get him out here. Okay, good AFA. Welcome to the show. How to, to mate.

Stefan Tsvetkov (03:55):

Yeah, here he, thanks for having me,

Reed Goossens (03:57):

Mate. My pleasure. Great to have you on the show. I was on your show a little bit earlier in the year. Maybe it was even last year. It was really good to see you again, my friend, before we get into your background, can you also, what you are passionate about, I should say. Can you tell us how you made your first ever dollar as a kid? I ask all my guests this question, and it really helps sets the stage for how you grew up in, in and around becoming an entrepreneur.

Stefan Tsvetkov (04:25):

You know, that would be like in college, you know, that would be that, that wouldn’t be even as a kid. Like I, yeah, I probably kind of, I, I went to Columbia in New York and I, like, I rented like an apartment and I kind of, I was living kind of rent free from basically renting to my roommates. It was kind of a silly thing to do at the time, but I thought it’s, you know, there’s a difference I thought in the market rates between. And so I think that was actually the first like check that I collected. So it was kind of was actually, I mean, coincidentally, I didn’t, it wasn’t in real estate for like 10 years after at all, but, uh, but it just coincident was actually a real estate trip.

Reed Goossens (05:03):

And that was through house hacking your rooms in the unit that you lived in.

Stefan Tsvetkov (05:06):

That was kind of, yeah, that was just kind of being a, like the master person on the lease and kind of right. Roommates,

Reed Goossens (05:13):

Subletting,

Stefan Tsvetkov (05:15):

Subletting. It’s not, yeah. It’s um, you, I don’t recommend it for people. I was, I was 22 didn’t I didn’t even know if it’s permitted or not permitted to do, but that was, I remember actually collected like my first check, if somebody actually, or somebody actually pay that actually helps, you know, my rent and whatever. And it’s like, uh, you know, that was the worst business income.

Reed Goossens (05:37):

That’s, that’s incredible. Walk us through your background. Cause clearly you, you have where you’re from, you’re not from this country like me, you’ve got a weird accent. So walk us through your upbringing and then the sort of the coming to America story.

Stefan Tsvetkov (05:49):

Yeah, yeah. Right. Yeah. So, so I’m Eastern European Bulgarian specifically. Um, they came to the states of 22. So I came for my masters. Um, like I did financial engineering masters, you know, I kind of like pretty routine. I continued into a finance career, um, you know, for about a decade. So, so, so that’s how, I mean, I, I wouldn’t say I immigra per se here. I was kind of like, I was looking at different schools, you know, I wanted to study in the UK or he or Switzer was kind of like working between different places and just was more like a choice of okay. The school that accept me. Okay. Maybe that’s gonna be the best choice. So that’s, that’s what I did at the time.

Reed Goossens (06:26):

Awesome. And what, what has been you, we talk about financial engineering in your introduction. So what does that even mean? Like for those people out there, like I, I’m an engineer, I’m a structural engineer. That’s my, my, my background. I can put things together. I can build things. There’s there, there there’s mechanical engineering. They put, you know, cars together and make things turn, but financial engineering. What, what, what the hell is that?

Stefan Tsvetkov (06:47):

Well, um, I mean, if you think of like, like some of these schools, they have like know things like operations research departments, and there’s like people studying this and that, or like industrial engineering departments. And so they use like certain mathematics methods, if you will, that are somewhat more applicable to finance. And so if you think like things drawing out of operations research, like spastic processes and stuff like that. And I know like most of the audience probably that would sound, would be new to them, um, in a way, um, it’s really any ma and coding and technology that was found applicable to finance through the decades. Things like option pricing and the most famous thing, like black show equation for pricing options. So it’s kind of like what’s driving like some of the financial industry and, um, it’s just quantitative, like MAs applied in finance basically.

Reed Goossens (07:38):

Interesting. And can you break it down for the listeners into what it means? What do you do on a day to day basis? Clearly you are very good with maths. You are good with, with numbers. How are you looking at numbers in a way that helps other businesses break it down into its parts to say, yes, this is, this is what you should avoid, or, or maybe just give a, an overview of what your day looks like in, in the financial, uh, engineering world. Sure.

Stefan Tsvetkov (08:04):

Yeah. And just to clarify, read I, uh, so that was like, that was my prior career. So I came out of financial engineering background and I’m a full-time real estate investor now. Uh, so, uh, so that’s what I’ve been doing now, but in the, in my finance career, it was just, um, you know, we have a portfolio like derivatives portfolio and like for tier audience derivatives that will do like options, futures, you know, like different contracts written on top of like the stock market or bond market and, and that, so, so it just had like a, you know, finance job, like managing the portfolio together with colleagues and it’s kind of a very market role, you know, very close to the markets, you know, you have a Bloomberg screen, whatever, you know, like things like that. So it was just like a very market finance job, but I didn’t want to, I always wanted to be like an investor myself and kind of like person my own thing.

Stefan Tsvetkov (08:54):

And, and I liked, uh, real estate for that. And, and so first they kind of bought a Plex, you know, like the usual house hacking, that’s now the real house hacking kind of house hacking story of like buy a Plex or other multifamily live in one unit in Toronto, the others. And I thought it’s nice. And it was here in the New York city. I, um, I live in New York and so I told you it’s, uh, it’s, it always is great. You know, there’s leverage, you have cashflow, you can get some inefficiency in the price as well. So it always really good. So I started looking into how I can utilize my skills, like use data and kind of, um, apply my skills to the real estate industry.

Reed Goossens (09:28):

Awesome. Awesome. And, and, and how has that been that transition into what you do today at your company, which, uh, you know, is, is Realty quant and, and, and, and around, cause we spoke a little bit before we press record here, how you are using that financial engineering background in Realty quant to help invest, make smart decisions in and around whether markets are overvalued, which is a really important thing as you need to understand what’s overvalued and what’s not. And, and, and then, so maybe you can walk us through the Genesis of Realty quant and how it became to exist in order to help the market make better decisions.

Stefan Tsvetkov (10:08):

Yes, yes. Great question. And the Genesis was myself as an private investor in the residential space, and I’ve been like transitioning more to commercial, like building on like a syndication now and so forth. Um, but generally an investor in the residential space, in the New York city area doing kind of short term projects, like kind of flips, let’s say like I would buy like, um, fourplex in downtown Jersey kinda like expensive, relatively expensive markets and kind of do like condominium conversions on those, those projects and things like that. And how do you discover like some of those deals with data? And so that was my goal. So I would write like, you know, write my Python scripts, you know, like Python is like one of the languages like program just for your audience. And so, and so I would write my Python scripts, you know, kind of find deals and could be on market of market, you know, things like that.

Stefan Tsvetkov (10:56):

And then once I got my webinar, okay. Now write even like some of those scripts to, for marketing purposes, you know, like to get like various, um, you know, information online that could be useful, uh, for marketing. And so, and, and so really the approach was, and the Genesis was just to how to make my daily life and kind of make it more scalable and more productive. So that was, that was the approach. And it started out in the residential space and then I’ve done like some modeling and commercial it’s for over overall the markets. That’s actually quite an interesting story. So like, like at the beginning of COVID, so I was concerned with, uh, you know, like it are, you know, what if the market takes it down, that’s kind of what many investors have this kind. So I went on, I workeded on like, what things have been done.

Stefan Tsvetkov (11:42):

And I found like, you know, Ingle wins at local market monitor is like something, a new bowel uses, for example, like their, their service. And I walked up Bloomberg economics and like a few other sources. And, and so what they did is they built like a, a model myself that was, uh, just pretty simple, really a linear regression model based on fundamentals of population income and housing supply, and kind of think plays a pretty key role. So I just, the goal was okay, where should, where should prices be based on fun where they’re now, do we have like, is the real estate market over while to try to answer this question in a, in a, in a relatively rigorous manner. And what I think I did a little bit further than some of the other guys, for some reason, they never were quoting the predictive power of this thing such as how will they predict, for example, the downturns cause the goal of financial crisis.

Stefan Tsvetkov (12:33):

And so that’s what they did. So I did actually a model that served to work at like, where should the real estate price be and how well did it predict the, the go of financial crisis drops in the us? You know, we not, we work at it, it was like Nevada, California, and like broad like states and then like specific markets within them were the ones that dropped very much. And so I did a study that, okay, they dropped like 40, 50%. And then on, they were overvalued on, let’s say affordability, deviations versus moving our, which is a very, the simplest model of all. And from there, it build like other ones, but even in those terms, they were like overed by similar percentage, actually 40 to 60% know overboard. And their joke was quite in line with that. And I was like stunned and like, uh, and the correlation, in fact at the state level was, was about 85%, like 83 to 87% balance source.

Stefan Tsvetkov (13:26):

And so it was quite interesting to me okay. That people before the go financial crisis have interviewed syn indicators and like other investors and some of them who were around at the time and they were always saying, okay, you cannot predict it and so forth. And yeah, sure. You cannot predict the magnitude of that. But to diagnose like the, an over evaluation is actually, uh, quite statistically fundamental kind of invalid and in doable. And the reason is real estate is fundamental asset. It’s driven by population income and health in point high level speaking and so on is able to do it. And so that’s what they did. So it had like, it showed that, okay, the very over overall states in this framework, um, dropped dramatically over a period of four years after the states like Texas at the time, Texas was 5% under in this framework, barely dropped, had a 4% drop drop.

Stefan Tsvetkov (14:16):

And I was, um, you know, saying to people, okay, it’s like actually like the, um, places that were under borrowed. And again, I’m speaking of states just gonna have this for 2,700 us counties, and one can do it at zip code level, etcetera. But, uh, but really, um, you know, just like high level discussion. And so they were like 10 states at the time that were under borrowed. And, um, they dropped only 4% during GU I found this is crazy. Cause I always thought, okay, that’s like a big crash in real estate. It’s like the biggest crash in us university history, but actually no, it’s the only places that got overboard, they dropped and they dropped according to their overvaluation. And so real estate is a very stable thing. It seems that has like a different downside risk profile than finance. And so it only drops if it can enters a bubble and otherwise you can stay the same.

Stefan Tsvetkov (15:00):

And like some examples of that are like, um, you know, some of the poor states like West Virginia or Obama, Mississippi, where, okay, they’re not strong markets, but they’re or markets, they are not strong, but they actually have very little downside risk and they barely ever drop. And so, so that’s like quite interesting to see, cause it’s a different dynamic in finance where we have penny stocks, you know, kinda undesirable stocks, let’s say they’ll have very high volatility, but it’s not the case in university cuz that’s people’s housing, you know, they don’t just sell their homes if something happens. And, and, and so that was an interesting observation. So UN valid states didn’t really drop. And so then this was one study I, I did. And so this is one product. Um, we have at my company quant, which is like market valuations data. Cause then what I wanted to do is okay, investors, they pick their markets based on, you know, population, etcetera, like whichever growth factors they wanna use to pick their markets, but nobody has a downside risk measure.

Stefan Tsvetkov (15:52):

And you thought, okay, I should put out a downside risk measure that has statistical validity. Um, I mean like correlation on county level, like for 2,700 counts was like around 75%, which is less strong than the states, much harder to predict smaller geographies, you know, but, but still pretty strong and you know, and pretty valid. And so, so that’s one thing I did. And from there, like I was kind of kept, started tracking it. So that was at the beginning of COVID and I started tracking okay. Quarter by quarter, quarter, where is it evolving? And us USA was really fairly evaluat at the time.

Reed Goossens (16:25):

In COVID you mean?

Stefan Tsvetkov (16:26):

Yeah. At the beginning of COVID. So if one computed let’s say like in simplest terms like pricing con deviations, you know, or did like some of these other, like other approaches, um, and you can list them out, but sort of it’s just really like fundamental the question prices be based on fundamentals, how much are they deviating off relative to that and, and just testing it actually and testing it and seeing what has been predictive for cause we have this great, I mean it’s a negative event of the growth financial crisis, but can help us see a, somewhat of a worst case scenario. You know, what, if there was no drop drop at all, there’s like nothing to calibrate three, two in a way. And so that’s kind of like a useful precedent if you will, for at least for a correction scenario, maybe a correction is not gonna happen, but it’s kind of like useful to have.

Reed Goossens (17:09):

So let’s talk about those, those basic things. We just, we mentioned it about how to you, you quantify an overvalued market, you mentioned a couple of things there, population income. What was the other one? You mentioned housing.

Stefan Tsvetkov (17:22):

Supply

Reed Goossens (17:23):

Housing supply. Okay. They’re the three, they’re the basis of what you then deem to be the, the base level, right? So you can then compare different states, different these different cities. So now let’s go fast forward to where we are today, right? So we’re using this, we’ve got this baseline data. We’ve, we’ve looked back at 2008. Now we’re in 2022, we’ve had a huge increase in valuation of properties, both single family and multifamily and you know, industrial massive on the, just on the multifamily side, I’m seeing, you know, doubling in prices compared to pre COVID pricing on, on a, on a price per square foot or a price per pound price, price per unit. You know, and I use the analogy all the time. I just sold a deal. I bought it five years ago for $80,000. I predicted it would get to 1 25. So 50% value over five years, I sold it for one forty eight, a hundred forty $8,000 a door just recently like, like two weeks ago, I’ve seen deals in other markets where pre COVID two early, late, 20 sold $90,000 a door. Now they’re selling for $190,000 a door what’s happening because you talk about these markets, Phoenix, uh, Austin, Dallas, Raleigh, Tampa, all these markets, Denver, can you quantify what’s happening? And do you, my, my, my big question is, do you see this valuation jump as sustainable? Or do you see it that there’s some, there’s something going on that we may have a recession or, you know, a recession at some point in the future.

Reed Goossens (19:06):

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Stefan Tsvetkov (19:43):

Yeah. That those are great questions. And actually like, just to certainly agree, I mean, your you’ve seen, let’s say like your asset, like grow like double in like per unit, uh, per door volume, let’s say. Right. And I mean, and now, you know, there was like very higher end growth. And so, you know, I’m sure for your specific acid, is it rent growth? Is it ate compression that’s causing it or like’s right. It makes a boat that, so that’s, what’s like, let’s say superficial or healthy or like, uh, that’s what’s driving it. So there has been compression. We know that now, why is that happening? Right. So let’s say, um, so with the, you know, like we talk about like money printing and inflation, kinda like some of the asset inflation that’s causing. So what I see on the, what in this framework, the market generation relative to fundamentals is the follow.

Stefan Tsvetkov (20:28):

So what that costing, we know what it’s costing price based. We know it has exploded the value of assets, like kind of your comment. And that has like different effect in the residential space. I’m sure in different commercial and understand, like there are different valuation methods, commercial multifamily and residential amount frame are not the same. Right. That’s understandable. Even though they have like relatively high price correlation, by the way, like what 91%, like over the one grand, but, but generally they’re not the same thing. And in the short term, they’re not the same thing, but so what’s causing it like, so if we look at like us, the asset inflation that happen, let’s it with the printing. So what does ONEC um, in valuation space? So not in price space in Valu. So what I saw in valuation space in the second and third quarter of 2021 is that US state went from what was a fairly valued, broadly speaking, fairly valued across the us. And that was actually the narrative of Bloomberg economics as well. Like they were posting like their articles for different countries. And they’re showing us is fairly valid in Canada over no Australia. I think like Australia and New Zealand were actually over borrowed in real estate,

Reed Goossens (21:32):

Always overvalued.

Stefan Tsvetkov (21:34):

Okay. So they were like kind of encounter like a pretty pronounced bubble, by the way, that’s been since 2019. So, uh, as far as, and then the UK to some extent and then scan. So that was that’s Bloomberg economics. That’s like near Russia publishing. And that was since 2019 and their study until even the believe they published it at the beginning of 2021 was still the same. Us USA is relatively, fairly valid. And that’s what I was seeing as well. So it was fairly valid and there was either when I would go to, um, you know, to, to an event and I would say, okay, Ida, who is over 25, that’s the only one, you know, it’s the only one that’s actually like kind of pronounced and like some others who like Carrie only at like 15%, like mild over motivation, but you know, nothing major.

Stefan Tsvetkov (22:17):

And so what I saw, um, is that in the second, third quarter of 2021, some of those numbers kind of doubled where they were very consistent before. So for example, like market generations in Texas and Florida, that they were at like eight to 10%, slightly over bottle range, you know, eight to 10% in there’s obviously like booming states, you know, tons of, um, you know, investor demand, etcetera. But they were staying every quarter would be kind of even like lazy to look at it cause can hold the same. You know, it’s always the same eight to 10% and now suddenly, and that’s just, just to kind of to report now in the second and third quarter of those numbers, dub number double. So Florida and Texas from eight, 10%, they went to like 17, 18%. So it’s not a major bubble, but this kind of change indicates, like I feel entering a slightly, a regime of this kind now that can take many years to, that can take many to, to stay like this or, or to resolve.

Stefan Tsvetkov (23:11):

And, and actually, if we look at, before the go of financial crisis, us USA state in 2002 was super, fairly divided in 2001, 2002, like four out like 0%. And by 2005 from fairly divided between 2002, 2000 had gone into like a bubble, like crazy one where some of the states went to like 40, 50% over borrowed. And so, and so that was, and then specific cities, you know, like even more and so forth. So that took like about three years. And then this go with Babo, you know, like kind of burst like only two years later. So it can take a while, but what I see myself, like with some of the discussion of inflation, like some of what you are saying, okay, like you see like per door price is kind of double in the commercial space. And we’ve seen that a lot in the commercial space recently with like some really, um, high end high, uh, return exits, you know, and, and which is, which is amazing. So, so that’s amazing. But, but, uh, what it really means is us inflation is exceeding the fundamentals and it really means that okay, some of the mini money printing resulted in asset inflation, but, but wage inflation wasn’t quite there. Cuz if we take like Arizona, so the reason why, um, like I said, that some markets kind of doubled innovation. If we take Arizona example, was that 15% for, for years before. And then suddenly second and third quarter now like 31% over about.

Reed Goossens (24:30):

Wow. Oay. So, so just to recap, you’re saying historically these markets have been slightly over overvalued and you’re saying slightly being eight to 10%, but now you’re seeing Arizona’s strong

Stefan Tsvetkov (24:42):

Ones. The strong ones were safety. Yes. The strong, um, like for in Texas. Yeah. They were eight to 10 for four years before they went to 17, 18 and the end of third quarter of last year. And I haven’t updated an year yet. The governmental debt is super slow and that, but, uh, but you know, yeah. So, you know, like it’s kind of like a quarter are back or like several months back. That is what, you know, that, that is what, what, what is there either? It’s not like everywhere. No. The mid Northeast is still underworld is still under, under doesn’t mean it’s going to do well. It’s just depressed. You know, it’s just depressed. It’s just the, some of the strong areas that also, um, I mean, let, let me put it like this. I also run like forecasts. I use like things like Facebook profit and like different models to like forecast prices.

Stefan Tsvetkov (25:34):

So if I was to forecast based on the trend that is, and try to forecast which place they’re gonna do best, they’re gonna be the same ones. I’m not like dooms see about Arizona. So like, do you know which, so which city comes out at the very quick, if by forecast 2020 to price appreciation, that’s gonna do the best Boise, Idaho. Why? Because that has been the trend and that’s the city that has done the best. And some people, if they listen to new Obama, it speaks to different events. What’s the best performing city like this market cycles, Boise, Idaho, and then we have Phoenix and then, you know, and so forth and then Denver over auto, etcetera. And so what’s the best, the highest price appreciation forecast Boise. What is at the same time simultaneously the most over price that has the biggest downside risk, uh, sub subject to the market cycle ending Boise again.

Stefan Tsvetkov (26:24):

So it’s, so it’s simultaneously true. It’s not always that the market is very strong is going to over, over, over in fact at the beginning of COVID Denver, Colorado was at 0%. Valuation was fairly valid and it had extremely bold. It was a top, um, top five performing city in the states, uh, like out of the big 100 cities. And yet, uh, it was fairly valid, so it doesn’t have to be, it doesn’t have to be, it’s just, it does tend to be at this point in the cycle, relatively later points, I can go for four more years, like I said, right. Don’t know I have no information for timing, but again, like being already 10 years into price growth, um, you know, cycle, uh, it does tend to correlate that the very well performing markets at some point might become over, especially if there’s things like money printing and so forth.

Stefan Tsvetkov (27:13):

And so people tell me like, okay, if there’s money printing, you know, like you hear the article, it’s good for hard assets. Yeah, of course. It’s good for hard assets. It’s, it’s, it’s true. It’ll be, we’re gonna make a lot of money right now, which is amazing, but there is this perspective to keep on the back end to know like for the end of the cycle. So, so it’s not, again, like I would invest now in Florida or in Texas, I would just kind of try to manage my horizon and track those metrics quarterly and see if they go totally out of work or something like this.

Reed Goossens (27:44):

And what, what do you mean by track those, um, metrics quarterly?

Stefan Tsvetkov (27:48):

So at every point of time you can have a price where real estate should be like, based on its fundamentals. Like, like I said, this regression based study, so you can have, and, and then what is the over valuation under fair, over valuation relative to that? What percentage is relative? So tracking this quarterly is, um, is, you know, basically think like what is useful in my opinion for, um, for investors, because it, it can change. So it can go into a very different regime. It kind of like some of the comment in 2021 kinda things entering a little bit different. It’s not so bad not saying it’s it is, but, uh, but it’s just in some of the Western markets, um, you know, specifically either hon Nevada, Utah, or Arizona, and Corra, those are, I would say the five, that kind of things started entering a little bit of a, a little bit of an artificial regime.

Stefan Tsvetkov (28:36):

It seems. And it’s also cuz wage growth didn’t really didn’t match that thing. Know there’s a code of money printing the result in asset growth, but it didn’t result in wage growth, wage growth in the first half of 2021 in Arizona was 1% actually. So now I’m actually hoping that maybe that’s gonna change. So if wage growth, you know, was to, um, you know, to, to SP those with inflation, to some extent, you know, it could kind of come down a little bit. And I, I’m actually kind of hoping for that. I hope that some of this is a little bit of a short of short term spike, but yeah. And you know, really for cities, like I can mention like, I mean voices, like the one that is kind of very pronounced, I’ve spoken at that since already since 2020, kind of like about voice, it’s kind of funny. Cause it sounds like, you know, like some of those Doy things, but it’s really, you know, like I said, it’s also at the top of my appreci price appreciation and forecast. It’s just a question of where, which is the cycle going end or not.

Reed Goossens (29:30):

And where do you think the cycle is right now?

Stefan Tsvetkov (29:33):

I don’t know. I have no information for that. That’s like him saying, have no information it’s for timing. But one thing I can say is that, cuz you said like, can some of those markets that are doing so well then maybe that they stop doing so well. Cause it’s just like too much and, and whatever, it doesn’t seem like this kind of dynamic, I don’t seem the date. It seems that there’s strength. So like I, I looked at like different states and markets and O two and there’s like O two correlations, one of the measures for like week four market efficient kind of trend and momentum. And so like all correlation correlation this year, price growth versus last year price growth in places like only four abroad. And they’re different in specific like cities, there’s like 77%. And then in Texas it’s like a thing around 63% still relatively strong.

Stefan Tsvetkov (30:19):

So there is a world of momentum estate. So markets that do well, they will continue doing well. And another study I did is um, until the market cycle ends though. And so you just need, like, it’s not like a measure, your measure of downside risk is gonna tell you not to invest there. I don’t think so. Those are gonna be the same markets are gonna do really well. Again, it’s just that this is your measure of down risk after this. You just can, you know, that’s depend on your risk tolerance, you know, do you wanna, you know, kind of risk go for two years, are you very much over the one ground in a, on a seven year investment, 10 year investment five, etcetera, just a kind of like your risk tolerance from there, but that’s, uh, you know, this is just kind of an analysis to do.

Stefan Tsvetkov (31:00):

And so, um, for one thing I did for price appreciation, since, you know, like investors, they often like look at different fundamentals, like population, etcetera, I’m just gonna share for your audience. Like maybe it, it would be interesting for them in their market selection is so they did a study where, okay, did like predicted population. Like they took the population growth time series, you know, and kind of predicted and took the income growth taxes and can predicted and took the housing supply kind of predict and then predicted prices of that. And then compared that to just predicting the prices themselves and the error was five times bigger. Hmm. For predicting forecasting prices to your head, like 2018 and 2019 prices based on the whole price history before that, which is kind of was a, an easy year to predict kind of a very simple trend.

Stefan Tsvetkov (31:47):

Right. But, um, but let’s say, uh, but the error was actually just like 1.4%. If you just predict the price in this kind of normal trend and once the trend, they were just, you cannot predict anything and it’s different, right. That’s actually in 2021 happened to extent the error increased. But, um, but yes, but so five times bigger error for actually doing the fundamental, which is inherent. If you think about whatever investor does, he looks up, looks up, income growth, looks up all that. And then in, in force, you know that, okay, prices are gonna do well. But if you take, let’s say that, um, population growth has been very strong over the past decade or so forth and that specific market, it, well, it’s already reflected in the price, but there are more things that are reflected in the price. And by modeling the, the input vari variables, you kind of miss on that and you end up with a bigger error. So that’s kind of a study. If you wanna actually try technically to forecast prices, you have a five times bigger error by looking at kind of whatever investor does in a way. Right. It’s quite interesting. So it’s the, the outcome of this is how say such a simple thing. You actually can just look at price time series and you would have done better and predict the things better, which is quite interesting.

Reed Goossens (32:56):

Um, price time series is, might be something that a lot of people listeners wouldn’t understand, but, but, but that’s, that’s okay. I, I think we we’re understanding that what you are, we’re trying to get at is that if you are looking at these markets right now, as they’ve been strong historically, right through recessions, that they should continue to be resilient for a downside risk. Is that what I’m hearing you say?

Stefan Tsvetkov (33:27):

Um,

Reed Goossens (33:28):

Like, like take your Denver, take your, Austins take your Charlottes that they’ve seen. Well, because that’s really the fundamental question here, right? No,

Stefan Tsvetkov (33:36):

No. Not, not like that. No, actually, no, because you are saying, um, you’re saying the ones that are on the price appreciation strong that they would be resilient on the downside risk.

Reed Goossens (33:46):

Correct.

Stefan Tsvetkov (33:47):

This is, I know. Yeah. This is kind of, that’s not what I see in the data. You know, one could think intuitively that that could be the case. No, it’s actually in fact the opposite it. And in fact, some of the strongest markets at this moment, they carry the biggest downside risk at the same time. Mm. And they have, like I said, this, the strongest price appreciation forecast too, because again, and that comes down to like, to the earlier discussion of real estate dynamic on the downside of, for example, in very poor state, like to observe this one can look at a place like West Virginia, right? So it’s kinda the poorest state in the country. It never has any downside risk. It didn’t have before the world. It doesn’t have now. So it doesn’t drop like prices in weaker markets have less exposure to downturn.

Stefan Tsvetkov (34:36):

And that is the real estate specific, a few dynamic that’s different from the stock market, where in the stock market, you actually have like a, of those weak companies, they sort of carry bigger risk. They’re more volatile. And in real estate in that sense, it’s not. And that can be seen in another way. Like I used to like look at like volatility in different real estate markets. And that’s one of the ways I was trying to predict actually this kind of downside risk. And I worked at for closure rates and other for closures. And other thing that doesn’t and predict by the way, the kind of like leading foreclosure rates also don’t predict like downturn. Cause for example, a very big foreclosure state is the state of New Jersey, but it’s very undervalue right now and it’s just not going anywhere. Those prices cannot drop cuz it’s, nobody wants to invest in New Jersey.

Stefan Tsvetkov (35:19):

And, and so, and yet it has the, the highest foreclosure rates, you know, in the country. So it’s not a leading predictor. And it’s also like for quarter is they’re very whoa when you’re at a very favorable market cycle point like now, so they’re like, okay, it’s the highest stone, but it is very low for quarter it’s over overall. So it might shuffle, you know, and change later. Um, but really it’s not a predictor in distance. So yeah. So volatility like I worked at. And so like even places like those poor states that don’t perform out, they may look good in risk adjusted terms. You know, like when the way in finance people would look at like price returns and then scale returns by volatility, they might look some favorable, but that’s Aus really, that’s not useful. I think in a genuine sense, every investor knows intuitively, which have been the strong markets, the markets to the west and the markets to the south and in, you know, this market cycle.

Stefan Tsvetkov (36:10):

But, and so, and so volatility and this kind of risk perspective and downside in university is quite an interesting and no, unfortunately it’s, it’s, it’s the strong, you know, like strong performing markets that are exposed. Some of them may not be very exposed. And even like, you know, at Georgia is, is a strong market. It’s not over while that was actually fairly valid, the latest, um, whether some other, I mean kind of average strong market that’s somewhat popular with something, something like Ville Kentuckys was, I think we got slightly underworld was still fair or underworld. So there, there are places that are, there are places that still are working okay. In valuations we take like something like the state of Indiana, it has done performed well in price terms, this market cycle. Now not as good as the Western markets of course, but has got healthy appreciation, healthy, you know, not like stagnant appreciation.

Stefan Tsvetkov (37:03):

And, and so, and the is so that’s like another example. Um, so, so it’s not like super many or super attractive markets that at this point have left, you know, have a war hanging fruit, you know, to pick, I would say they’re kind of, and they’re like not so, you know, not so exciting in a way it’s like more like those average ones, but it becomes like this risk selection of you want, you wanna have downside, like how do you get downside protection? For example, if you are in an undervalue county and an undervalue state, your prices are basically not gonna drop. So that was the case. If you look at like Viro was at my webinar, he bought like his first indication in 2008. So his indication had a crazy IR of like 45% apparently was a great deal. Okay. That’s separate. The deal was great.

Stefan Tsvetkov (37:50):

Okay. Had like a very, very, very good deal. But he bought it in 2008, the peak, I mean, there are so many people who, um, purchased at the, around the time and um, you know, like, you know, like rod Cleve, he has like his lecture about losing 50 million and then gaining 50 million. Right. You know, this kinda thing. And there were many people like that who was like the majority of their network during that time. But they were not in Texas. They were not in Texas. They were in Florida that they were in, you know, uh, perhaps Arizona or, or in other places. And so we operation buying in 2008 that didn’t hurt him at all. Cause there was no drop at all. There was like, I mean about 4%, like with incomes, cause incomes dropped 4% and so forth, but it was negligible. And if you bought an asset, that’s under borrow, that’s gonna perform well, you’re not even gonna see it in your P or, or anything.

Stefan Tsvetkov (38:38):

And so that’s quite interesting. And so it depends again, risk tolerance. So, so if one wants, cause again like the strong markets are gonna be the same one. It’s gonna be again, the markets to the west. It’s gonna be the markets to the south, but now, and they’re even probably gonna be even stronger now with all the momentum kind of building up and just a selection of, okay, do you want to capture like these like crazy returns for several years, unknown how many years or how much time, but simultaneously carry the downside risk during this time or maybe going kind of middle ground, you know, in places like the Midwest, like Indiana, Kentucky, Ohio kind of, you know, kind of places got it. Um, or yeah. Or you wanna even go if you’re like crazy risk work or you wanna go in something crazy under vault, you know, like the Northeast where okay. Your price appreciation is gonna be weak, but you also have carry like no downside risk whatsoever. Cause pricers don’t go anywhere. So it’s just like from theres, but it’s just like an additional variable to be aware of. And so, yeah, so I’ve been kind of like, um, building, like adding, like I feel like adding to like the investor a now in a way, like

Reed Goossens (39:44):

It, it’s a very interesting space you are in and clearly you’re passionate about what you do. And so as we come to the end of the show, I, I wanna give you an opportunity to give one piece of advice to investors today as they’re entering the market, what would that advice be in and around observing certain trends.

Stefan Tsvetkov (40:06):

Yeah. Yeah. Uh, so yeah, so in and around that, uh, so I would say to pick their markets based on, so to, to, to pieces of advice, except based on the, mm, appreciation, not looking at like, oh the message. Just looking at the prices themselves, it sounds silly, but that’s actually more accurate for predicting appreciation. And then two, they can come to like my company real one.com or they can compute themselves, use governmental data, like run, I don’t know, do like simple cos of pricing commercials and other stuff. And they can like get, um, get a sense of some kind of numerical measure of, of valuation and track that. And so it’s kind of like a really urge, like my advice is to don’t invest in a market. If you don’t know where it’s borrowed, like I don’t invest in the stock market now myself.

Stefan Tsvetkov (40:54):

Cause you know, don’t know it’s valuation. I don’t know if it’s overed just the, the high statements it’s over borrowed, but, but I would say the same in 2020 and I don’t actually know the reason why I don’t know is it cannot, I don’t know how to value technology companies, but in real estate you have the incredible opportunity. It’s a simple from the mental asset. That’s not, that’s not the technology sector. It’s actually easy. And so I feel like we, people have this skepticism that, oh, you, you know, how are you gonna predict anything? You know? And they have this kind of thing, like from finance that, oh, we should just give up on the whole thing. Like go together, just drop it, you know? But in reality that’s real estate is not the place to drop it. It’s the opposite. It’s kind of like utility stocks or something. They’re easy to predict. And so, and so, yeah, so the kind, my advice is don’t invest in a market just cause it’s hot or it’s trendy, but know it’s exact valuation have a percentage, whichever way you derive it in your own approach, have a percentage assigned to it. No it’s evaluation. Know why that matters. Where has that percentage been in before the global financial crisis, how that has affected like subsequent decline, etcetera. So, so yes, just have a measure of market evaluation is my advice.

Reed Goossens (42:08):

Awesome. Awesome stuff. Uh, Stefan, I wanna thank you so much for jumping on the show today. Where do people go? They want to jump on your website, they wanna understand the valuation. Maybe you do it for people. Um, if you know, you got some charts that you can come on your website and have a look at where will they go? Yeah,

Stefan Tsvetkov (42:24):

Absolutely. Yeah. So this data is actually published@riotyone.com for like 2,700 us counties. Um, so yeah, so they can look it up there. Um, I do it like pretty much as a service to the community in a big extent, honestly. So it’s uh, uh, so yeah, rcon.com. They can, can also look up my YouTube channel, finance me estate on YouTube and they can work me up on LinkedIn as well.

Reed Goossens (42:50):

That’s awesome. That’s awesome, mate. Well, I wanna thank you so much for jumping on the show today. I just wanna reflect some of the things that I took away from today’s show. Firstly, is that you’re extremely knowledgeable about, you know, geeking out on the engineering part of the financing side and bringing that financial engineering meets real estate. I think that is super important to break down and look at historical trends about where we’ve come from to get a sense of maybe where we’re going. But it also to your, to what you were saying before, how to protect your downside, right? If you are in certain markets, you’re gonna have certain downside risk versus other markets and understanding where the valuation of those markets are relative to history is really, really important to, to, to make your educated decision on whether you venture into that market. So I highly encourage everyone to head over to Realty quant. That’s QUANT.com. Check out everything state found is doing over there because he is crushing it and it’s all relatively accessible, right? You you’re giving out this data for free. So get over there, check it out. And um, anything else you wanna add before we wrap?

Stefan Tsvetkov (43:55):

Uh, no, that’s this? No, thanks for hosting. It was great.

Reed Goossens (43:58):

Awesome stuff. My friend. Well look, thanks again for jumping on today’s show. Enjoy the rest of your week and your weekend and we’ll catch up very, very soon. Well, there you have another cracking episode jam pack with some incredible advice from stay fund. If you want to get over to his website, go to Realtyquant.com to check out all the market evaluation across. I think he’s had over 200 different counties across the United States. Uh, I wanna thank you all again for tuning in to continue to grow your financial IQ because that’s, we’re all about here on this show. And if you do like this show, the easiest way to give back is to give us a Fivestar review on iTunes and we’re gonna do it all again. Next week’s remember, be bold, be brave and go give life a.