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*****Thank you so much for listening to the Making Money in Multifamily Real Estate Show! This show covers everything to do with Multifamily Real Estate Investing to help you, the listener, become an expert in your real estate ventures. The host, Dave Morgia, brings on guests who are already experts in their respective fields to discuss what principles and practices they follow that have helped them achieve their success so far.
Stefan's Background:
In this episode we cover:
Connect with Stefan:
Connect with Dave:
Other ways to listen/watch:
Follow or Subscribe:
If you enjoyed this episode or like the show, please subscribe and leave a review! It is a huge help for just a little effort
*****Thank you so much for listening to the Making Money in Multifamily Real Estate Show! This show covers everything to do with Multifamily Real Estate Investing to help you, the listener, become an expert in your real estate ventures. The host, Dave Morgia, brings on guests who are already experts in their respective fields to discuss what principles and practices they follow that have helped them achieve their success so far.
Welcome to the Making Money in Multifamily Show, where we discuss everything to do with multifamily real estate investing. We believe it's the best way to gain financial freedom and build lasting wealth. This is where you'll find it the best information and practices to help you succeed in your real estate business, whether you're already experienced or just starting out. Here's your host, Dave Morgia.
Dave Morgia:Hello listener and welcome to the show. I'm your host, Dave Morgia. And with me today is Stefan Tsvetkov Stefan is the founder of Realty quant, which is a company that brings data driven and quantitative techniques to the real estate industry. He is also a multifamily investor, speaker and webinar hosts. He has a extensive background in finance engineering, graduated from Columbia University and manage 90 billion in derivatives jointly with his colleagues. And like I mentioned getting into multifamily. And just a large background in the kind of data driven analytics and, and really just what kind of drives decision making to be able to invest properly. So. So yeah, I appreciate you coming on the show. Stefan, if you want to just, you know, say hi, and kind of give the listener a little bit more of your background if I missed anything.
Stefan Tsvetkov:Yeah, everyone. So thanks, Dave, for having actually, it's a pleasure to be here. Yeah, like you mentioned, I have a financial engineering background. So I came here 22, like, Eastern European, I came at 22 for my Master's at Columbia, like you mentioned, and then I worked on worked in finance for about a decade, and in the recent couple of years have been a real estate investor. So doing different strategies, like utilizing data and searching marketing efficiency. So condominium conversions in the New York City area, like various other like discounted properties, like predominantly in New York City area, and more recently, I've been switching entirely to the commercial space in the Midwest. And I can get in more detail as to like my approach for like searching for deals, and so forth.
Dave Morgia:Yeah, so let's get let's start there. Because you mentioned, we just spoke kind of offline before the show, you know, we were on a meet up here in the city. And, you know, the New York market is very different from darn near every market in the country. You mentioned targeting the Midwest. So how did you narrow in on the Midwest? And then from there, you know, how did you narrow in on the markets that you further identified from there? Just how did it work for
Stefan Tsvetkov:you? Yeah, well, that's a great question. I mean, so my company Realtek wants one of the data set, kind of like, we do have like a single product that's currently released to the to the public, which is a market data product. And so it's really, really what it does is like always, like which markets are overvalued compared to their like income, population, housing supply fundamentals. And so and in a way that that metric has been, like, statistically predictive of declines as the global financial crisis. And so it's actually kind of like, verified in a way, like, it's not all just something is overvalued, and it kind of thrown the sentence in the air, it's actually Well, that's what was most statistically predictive at the time, we could have a different scenario now. But it's in theory, such as if we do not experience a full correction scenario like it was then. But this is one like this one piece of information that feeds like my market selection, if you will. And I mean, then it's like the respective risk tolerance, I go with weather storms they have and that's why ends up with Midwest like considering that data. And then, like forecast, another thing that I do agree with the quantities like forecasting appreciation for the different markets and clarify, like, that's something they have there for, like 2700 us counties. And so focusing appreciation, like there's different models, you know, to do that there's Facebook profit, and like, there's different different ways to do it. It tends to work while the trend persists, does work and then kind of breaks apart. So but it's, you know, so So that's a very, that's another thing that kind of feeds like how I pick markets. So I kind of combined like, appreciate very statistical appreciation forecasting, with what is also statistically predictive downside risk. And so the downside risk part is like really, I feel I don't want to say it's unique, but I feel like it's not really practiced enough in the industry because so how is like the first part typically, we have like let's say syndicator, investment manager investor, how do they pick market so they pick like by job growth, population growth, and all those factors and okay, they will good and then maybe sort of a little bit by crease and then the market and you know, you like also the market and so forth. But, but then a nick, for example, one study did it robotic ones, instead of a statistical study where if you do if you look at all the fundamental straight forecasts down to one year ahead or whatever, and then forecast the prices of that. You're committing like a five times bigger error, like forecasting those prices, than if you were actually just to pay the prices themselves. Extremely simple thing to take the prices of sells and just forecasts the prices themselves. So this is just one observation just to throw out there. It's actually in the reason for that is in most like markets, real estate markets, there's lots of momentum. So there's lots of like, you know, last year prices are growing well, this year they continue to grow. There's Alaska is an exception, you know, there aren't that many of us invested in Alaska, right. So if we take some like Florida, we're even Massachusetts and so forth. There's like, pretty high autocorrelation. In fact, close to 80%. In those, and so so that's kind of like what they're so this like one part of the selection. And then downside risk, like I mentioned, is based on what predicted the regional like county and state level declines as the global financial crisis. And yeah, yeah, and I can get more into that. And on the property sales. Yeah, well,
Dave Morgia:I guess, I guess, on the, you mentioned a couple things, I think we are in kind of a very, whatever you want to call it fluid, transitory, whatever the term may be period, a lot of fluctuation and you know, a lot of rent growth, a lot of kind of interest rates are beginning to change. And you mentioned downside risk. So how do you kind of factor in, like the short term market and kind of take that puzzle piece? And then also add on the long term, you know, the historical data where you're talking, you know, 1020 year trends of multifamily or commercial or whatever you're looking at? How do you kind of piece those two together to paint the whole picture?
Stefan Tsvetkov:Yeah, well, that's a great question. I mean, first of all, the first part is like, because you mentioned like commercial and so for the first part is actually not so easy. Like perfectly even you have like this, you have costar subscription, and you use that data and your various other like, bits and pieces from Costa and other vendors, it's not so easy to model the market side based on commercial data, there just isn't that good of a data there, like that good data there. And so it's really, that side is really like very residential. Now if we look at, you know, but then like, we did also study, okay, component costars index versus, like, FHFA, for residential, and like, over the long run, there's kind of like 91% Price correlation. So they kind of do converge. But I mean, you know, how you short and of course, they will deviate, and, you know, your asset is, you know, valued in a different way, fundamentally, the assets are the same, right? Fundamentally, it's still a multifamily that's multifamily, where people need to live. And it's driven by income population housing supply. Now, the valuation method is different that causes like short term deviation between the two, and so forth. But it's really my personal choice for modeling the market side has been actually to model the residential side. And so it's actually not so bad, because residential market changes tend to be a bit of a leading indicator for commercial. So that's actually also a little bit helpful. Like Single Family Housing typically is, is a is a leading indicator. And so, so that has been like the approach they're like, again, like for, you know, lack of perfect, amazing commercial data for like, every single county in the country or something like this. And in that now, but you mentioned, like interest rates and those changes. So there was a, like, yield curve inversion, right? Use of inversion, that was, you know, happened like recently, and it happened before in 2019. Right, and so like, people that got like, really worried, okay, what's your version, you know, kind of leads to recession. And that's kind of drew right through, right, and probably made me with some of your audience saw, like, the articles, okay, it's like two thirds probability of a recession within 12 months and in the 98%,
Dave Morgia:relation,
Stefan Tsvetkov:like 98%, within 24 months or something. So it's like, okay, so it seems like, I mean, kind of some kind of recession, even if it's a super short one seems very likely. Now, the question is, Is there gonna, is there gonna be like a super short recession that kind of does nothing, you know, like, with COVID, COVID, to real estate, or is is going to like longer run. And even if there is a recession, recession is not so highly correlated with real estate drops, though, because sometimes in many recessions, real estate didn't drop. And so that's another, that's another thing. But this is an interesting thing there. And, you know, people have been super worried about like interest rates rising with inflation. That's actually an interesting question. Because the trend that we saw in 2018, when the Fed was hiking rates, and it was still a trader in finance at the time, was, okay, fairly high rates, then the, you know, the Treasury yields the 10 year Treasury yield spikes and mortgage rates, mortgage rates are a function of 10 year Treasury yield, by the way, you could sit there 30 years, but people don't hold their mortgages for 30 years. So they're really kind of tied to the 10 year treasury. Right. And so then your return rate spiked, and then we have then the curve inverted. And then suddenly, okay. The then basically, there was a bond rally kind of like people buying more bonds and interest rates actually went down. And at the time when there was when interest rates were actually super sharply going down. That's when actually at least my job when you Okay, we are in a recession just not measured yet. But there's like a huge bond rally. So that's like just one thing to come up with people like worried about rising interest rates, rising mortgage rates, well, okay, the only The challenge to predicting this current case is well, it seems like it's stagflation kind of thing, the recession plus inflation, right, okay. But then, so the inflationary impact is not going to be very certain. But otherwise, in virtually every recession, the interest rates kind of plummet, you know, that kind of when one goes up or down, and that was the case, you know, the COVID, recession, you know, core COVID, very short recession. And so that was the trend that we were then in. And so generally, I would expect to be perhaps the same trend, just kind of as a base, and nobody can predict interest rates actually kind of hard. But generally, okay, interest rates tend to kind of really plummet into a recession at the end. So this is just a kind of uncommon there on like people concerned with cap rates, compressing and interest rates going up and down, essentially, there's no spread whatsoever and cannot execute your value add model, right? So there's, there's nothing you can really do that much with, you know, with when if the spread is zero, or maybe perhaps negative, and, and so forth. But this kind of an observation, but were they. So my company, like what we do for downside risk is actually a little different. So it's not predicting timing in any way, we just measure the magnitude of downside risk. So that's it. So there's no, there's no like, bullish or bearish view whatsoever. And so what do I see? So for example, it's the peak of the global financial crisis, there were like four states, if we speak abroad states, like we had, we had counted 34 states, California, Nevada, Arizona, and Florida at the time were formed around like 40 to 60% in this kind of fundamentals, deviation COVID, overbought reduction. And so and so they were like, in the in the drop, like 40 to 56 percentage. So it's like, quite interesting. So it was like, very much in line. And then they were like, Oh, the under but then in the opposite camps. That comparison. At the time there were like all these undervalued states over even Texas was underwater at the time about 5%. Underwater in this this
Dave Morgia:measure, and what time is this measured by? What's the what's the
Stefan Tsvetkov:reference here? I mean, this just a comparison, like global financial crisis, the peak, where's the where valuation metrics declines that happen afterwards, sort of like to get like, and so yeah, so like the four states like California or Arizona, Nevada, Florida, super over about 40 to 60%, their decline in line with that, like 40 to 56% impact, and the 10 states that are under words, like Texas at the time, North Dakota, Iowa, you know, a few others, they had an hour drop off only 4% actually. So nothing happened there. And there was like, for example, you know, like Vinnie, Vinnie Chopra. So he did like his first syndication at the time. And so he was at my webinar, he mentioned, okay, I did my first indication in 2008, and did really well with her, like, the super high IRR, and why it was an undervalued County, in the undervalued state of Texas. And so the market had no, there was no effect whatsoever, even though, you know, like other investors were virtually wiped out in, you know, in some of the other states and sort of like losing all their network. And so that was like an observation. So where's this measure now? So at the beginning of 2021, us real estate seemed to be fairly valued. So even through Q first quarter, Now, some people may, maybe we'll maybe surprise you, that's quite interesting. And that was actually quite consistent. That was the same in Bloomberg economics publishes a study on different countries in the USA, right around the hundreds, you know, like quite paranoid about it. And so, even though like many properties may appear over Waldeck specific properties, or to see like bidding wars, and one gets this kind of a bit like noisy optical perception, but if you look at like fundamentals, and kind of the big picture, it was fairly, fairly valued. And there was an exception since the beginning of COVID. Already, there was an exception of Idaho, for example, and I was going to like some events, and I was saying, okay, Idaho is only your source is fairly well, but I was the only place that is actually overbought.
Dave Morgia:Okay, so, so through, like, basically early stage COVID, or I guess, second stage COVID, Idaho was was kind of the one child that stuck out as far as overvalued. That's interesting. Yeah, that's really,
Stefan Tsvetkov:since the like, even like the first quarter of 2020, either who was already overloaded was around 25% in 2020, overload with either is an exception, and then like, go to like, very, let's say, worry that in Texas, and just like speaking broadly of states, and I can speak like cities and counties and that but like, say, like Florida and Texas, we're actually in the like seven to 10% range for a four year period 2017 to 21, very consistent. And then suddenly, in 2021, second, and third quarter, those numbers doubled. So for the indexes, they went to like 17 18% Suddenly, and then through the end of 2021, and they actually still haven't released my data on that. They actually went about 4% higher so perhaps the 21% so it's really 2021 middle of 2000 going forward that we can speak of something of a bubble. That's like the first time and then we can and then that's only in Western states and a little bit solderless. So the trendy wants, it's not a surprise, it's no surprise,
Dave Morgia:essentially, where maybe rents propped up through cover where people spread out to get warmer, and maybe the rents don't stick for the long term, essentially, that's really interesting.
Stefan Tsvetkov:Yeah, it's taking, like, I mean, we all heard the rent growth in Phoenix, okay. And like, people were happy making a ton of money from it. But the reality is, if you take a look at Arizona prices in the first half of 2021, they rose like 17% at the state level, even. And then for Phoenix, you know, even more, right. And but the incomes actually grew on the 1%. So it doesn't actually support it. Now, we see kind of an income, super growth, that's what I was hoping, okay, then that's going to kind of catch up. But then we got the next quarter income didn't catch up. And it's still statistically on the measure that's like tracking the 20 years, and so forth. And that, that 85% correlation at the state level at predicting times before, I would be surprised to be particularly difficult predicting the states, because states are very easy, it seems to predict that much anything, even forecasting prices and silver, it's like very big, very fundamentally driven. Again, small geography gets harder and harder that you go to a county level your correlation drops 10%. If you go to the zip code level than perhaps another 10%, you know, and so forth, it just gets higher,
Dave Morgia:it gets very niche at that point. Yeah. That's smaller data set you have right, so yeah, so
Stefan Tsvetkov:like when people say, and I'm sorry, like, just maybe going too long. But that, you know, when people say, Oh, Curiosity is hyperlocal, I agree, it's hyper local, but the business of what is your likelihood of getting it right, that hyper local level, so you can get, you can get state super, right, you can get counties somewhat right as well. And then it gets like harder and harder. Now, then you need like, diverse, perhaps, like social media signals, like various machine learning, neighborhood predictors, and so forth for that, but that was kind of the interesting thing there. That's so so it's really like, so what I saw, calculate is this, okay, now the five western states like Idaho, Idaho, Utah, or Arizona or Nevada, Colorado, those are I would say, sharply kind of sharper, overvalued, you know, above 20%, for all of them, either, who is like nearing, I think it was near near 50%. In this measure, and that's an exception. If you take on the opposite end of the spectrum, the northeast, New Jersey is still underwater and underwater. I mean, just to clarify, this is under overborrowed. It sounds like good in some way predict depreciation. It doesn't actually say Do you like this kind of test is gonna predict depreciation? Like 12%? Okay, it's like it's a positive one, you know, but it's not a it's not much. It's not much. So it's like, just, it's not a good predictor of appreciation. So if something is undervalued, it doesn't mean it's gonna appreciate it just means it's protected from a
Dave Morgia:downturn, just basically for risk adjusted. It's a good deal, essentially. Yeah. Well, not a good deal necessarily, but risk adjusted. Yeah, it's it's above average, right? Is that
Stefan Tsvetkov:my understanding? Nothing, my risk adjusted risk adjusted is actually not even that because risk adjusted is you can have something like West Virginia and I could very depressed state. or something, it's kind of like relatively poor states where prices don't go much higher. But volatility is also really low, and it might appear fine risk adjusted terms, it's not so much about that, it's just more of just your downside risk is, it's like an insurance policy you can make if you invest there, you're not gonna get much appreciation, probably, but you it could have been a situation where earlier in the cycle, even at the beginning of COVID, for example, Utah was fairly well still, and youth is now at the cutting edge on probably around 25 30% or something over borrowed it just over a very short period of time. There was actually I think, around 4%, or even beginning of 2020. And then also Denver like Denver, Colorado was had experienced huge appreciation in the first about
Dave Morgia:these Western States starting are up to seven but what about these western states make make it like, that seems, you know, it's relatively regionalised over there. And, and I wouldn't, it wouldn't to me, like Idaho would pop off to me as an overvalued state, per that model, or just in general to me, I wouldn't call Idaho Valley but per that model, it's saying it is so so what is it you know, what's the kind of logic or behind the numbers explanation to that?
Stefan Tsvetkov:I mean, again, the logic is just like what is your what predicted the exit post GFC decline? So I looked at foreclosure rates I worked at what you mentioned, risk adjusted returns, I looked at volatility so these kind of like all these like different studies, like foreclosure rates is a leading indicator, for example, another predictor. So let's say we can say this now like New Jersey is the top four quarter state in the country like consistently almost every year and the downside there is no scenario there's going to be very well there because it's just like, undervalued compared to its income just price didn't appreciate it wasn't like that then then it was more like more like 25% overvalued or something like that and kind of actually did drop. So it's it's just that What is your interest? Like? If you try to answer the question, what is the best way to predict kind of like a decline and in magnitudes, and then that's kind of that is, that seems to be the best way because the best one because they can mention that you will do like utility and understand correlation is just not particularly high. And if you take in on what's the simple way to proxy this, so this is like population income housing supply. Now, if you want to proxy it in a really simple way, anyone can can do this. If you take pricing price income ratios is like affordability, right? So home prices divided by, you know, the personal income in different regions. If you take affordability, and you take deviations from affordability on a moving average window, you will have predicted that post GFC declines in magnitude to the very big to a very acceptable again at like around a 5% correlation. So that's very
Dave Morgia:high correlating. Yeah. Wow. That's
Stefan Tsvetkov:crazy. Yeah, exactly. No, yeah. And it's kind of interesting. And I think the reason for that is, if we think of what you're actually doing there, then some people start thinking, okay, affordability in itself means something. But no, actually, because if you take something like San Francisco, it has like super high affordability index in the sense like wall affordability, right? Let's see, like, the prices are many times I don't know what that's it's 15. That's the price, they're 15 times incomes, I don't know the exact number, let's say 12. And then you go to somewhere in Nevada, and maybe that's just five or six or, or something like this, right? But then it doesn't mean that San Francisco is overwhelmed, because that ratio has been built. Like over the years, that same perhaps San Francisco was at 555 X on the five times a price or five times incomes, that's in the 50s. And then it's developed housing shortage. So population housing, squatter ratios, kind of build up into that. And then it kind of grows. And then at some point, that's how you get like all those big cities to be like, very not affordable, right? But then, okay, you have this like, not affordable San Francisco at the time, but it was it's undervalued. Actually, it wasn't there at the beginning of COVID. And now went further underwater. And that's not a surprise, because we know the issues that San Francisco has, it's not a trendy place. I mean, there's all the policies also in California, and so on and so forth. And so yes, it has a high affordability. And people say invest in Nevada, or something has a I mean sort of a Whoa, affordability high affordability index, invest in something like Nevada has a low affordability index, but it's not how it works, because now nibble is overbought, California is not in California is actually the only fairly valued state in the West. And so it's very much that
Dave Morgia:just like so yeah, that's just so backwards to what the way most people would address it. But I think that's that goes to the point that people would talk about, like you're saying, like people will look at like rent to income people will look at all these measurements to be able to decide if this is places rentable and I can afford to buy a place here to rent out. And yeah, nominally prices might be high, but like you say, it kind of doesn't paint the whole picture. So that's a really, really interesting kind of way to look at it from a different lens. We mentioned all these states out in the west, and and you mentioned jersey, as a good state. Where not Not good, not good. Sorry. Yeah.
Stefan Tsvetkov:Above. I actually think quite the opposite to be honest. No, it's just like protected from a downside risk. You've got it. My appreciation predictor is actually highest in Idaho. So and it's also downside tonight just to clarify
Dave Morgia:so it's just a big it's just a risk tolerance game at that point.
Stefan Tsvetkov:We see you know, like Boise or again like to canter up but like if we take like boys you know, if you some audiences they listen to Neil Bauer, right so okay, he mentioned speak sometimes boys is like the best performing market this market cycle which is true that's just price history. It's easy to see like you bro the prices are it's the highest depreciation is Boise, Idaho. And then it's but it also happens to be kind of overwhelmed and actually spoken voice already. The beginning of COVID was like super overwhelmed, but then it appreciates a lot because that's not what's driving appreciation appreciation is driven by momentum, sentiment. Yeah, momentum. Prices still continue going. But then the question is, at some point, if the market cycle reverses, then you carry downside risk employees. So that's kind of I think that's kind of my point. So it's not there's no like labeling of like good or bad markets.
Dave Morgia:As a put that as a poor word. It's essentially what what is your upside compared to the downside for like, what's your what's your actual risk profile? So so for you Sivan, what I'm like, what, where do you see yourself investing based on that? Are you looking for, you know, places with less appreciation at this point, but less downside risk, because we're potentially heading in that direction with we talked about the inverted yield curve. What kind of states are you looking at what profiles today that they have these days?
Stefan Tsvetkov:Yeah, great. Great question. Yeah, myself. And again, like you mentioned, skills to restore. So it's not even discouraging people to invest in anything in Phoenix. You know, they can make like a ton of money. I don't know what the timing is. Gonna be to that right and so forth. So it's, it's definitely a Phoenix would likely appreciate enormously, you know, over the time until it reaches peak of sci fi and and then it could have carried some downside rates. So again, just like you mentioned, just requesting based on my personal opinion, is investment managers perhaps should be a little bit allocating new acquisitions towards the Midwest. And I don't want to say the northeast, which is even undervalued because the Northeast has all these policies like not favorable policies, issues, and so Okay, nobody wants to be there in that sense, but definitely the Midwest, which is fairly valued, broadly speaking. And so that would be like significant from a portfolio perspective, you know, that would be kind of reduction in risk, where you don't enter, like some of the super high valuations in Western markets. That's what I would do. And actually, I did a lecture for a private equity fund on this and like they were, that's exactly what they did. So they have very low risk tolerance, what they said, We're going to be investing on the secondary and tertiary markets in the Midwest. And so that's actually I thought that's like the on the first reaction I saw to something in the market where that's like, extremely conservative, because the Midwest is brought the parents borrowed. Now, if you've got secondary and tertiary markets in the Midwest, that that's gonna be okay. You know, that's actually going to be okay, like smoking, that's not the kind of guy that's going to have like a 4% decline by by incomes, you know, that's what happened like before, like post GFC. In some of the Third Kind of regions, that will be just my personal view. I think it's just a matter cap portfolio occasion, just a few, it's more the time and again, no tiny relative because even if we have a recession, it's a small one, let's say that doesn't do anything, perhaps to real estate, or maybe it's gonna be further down the road, like more years ahead. It's hard to say. So it's unknown. But my personal sense is year two, considering the differential inflation, differential asset inflation over income, for example, that we experienced, which the Nick everybody said, Okay, buy hard assets, like buy hard assets, because hard assets are good. They do well, with inflation. Yes, but then it's driving remarket overwhelmed after this, and then carriers Down syndrome, there's sort of lawsuits, right. So that kind of considering this kind of situation where everybody kind of bought assets on inflation, and, you know, that drove the prices, but the mentors, as of now at least seem to have not really caught up and, you know, so so that will be just my personal advice, kind of. So that's why that's what they do. So I can't focus, okay, we'll get my last bid was 48 unit in, in Iowa was like, By the morning, I'm not specifically promoting the market against just because of like, very risk protective kind of attitude where it gets relatively healthy measure from appreciation. It's not it's doing, it's doing decent in appreciation, but it was also 2%, undervalued in this in this measure. So it's that kind of micro market, because I just said don't want to carry the, I don't want to carry that downside risk. But again, it depends on risk tolerance, I could go in something for that. And your reason, okay, I have, you know, perhaps among around 20%, downside risk, something like that, but maybe less, I don't know, but something is, but okay, but then I would, but it's not terrible. It's not like, you know, it's not like Idaho, it's not even like Arizona, it's kind of okay, and so, so maybe I could go there and then you know, kind of keep tracking because you can actually make them a reality quant we like once you let's say whoever signs up for daily kind of get it like lifetime like lifetime updates.
Dave Morgia:You can train you can train the actual the actual risk. Yeah.
Stefan Tsvetkov:Yeah, it's kind of like free updates, you know, so it's like every single quarter so you actually kind of track it. So that's kind of what they do so in a way, like, you know, you could, once you're aware then you keep tracking it and maybe you like it, it's a little hard sometimes to get the timing right. But But still, you know, maybe you exit at some point and but that's kind of like just just I think the message is not like so much. I don't think it's like either like a bullish or bearish message. It's just like, it's the same. I currently have like no stocks. It's no great thing since the stock market did really well. Okay. So let's say what is one reason like for me, it's just because I don't I don't know market valuation in the stock market. So I ended up on a mature investor. I can just from the market standpoint, I'm on how mature is just like guessing is the market highs it will where is it? And in in that's because okay, there's so much technology, there's technology sector there, it's hard to you'd have to run a
Dave Morgia:mortgage. That's a completely different animal than real estate when you're talking about hard assets. Right? So
Stefan Tsvetkov:in real estate, we're actually super fortunate right and real estate first you know, property valuation even this automated valuation models, okay, like with machine learning even that but you know, let's say professional appraiser property which you can find in efficiency, you can find discounted properties that's useful, right? You know, the valuation of property, but also like what I've been kind of like on that side, like arguing it's okay, when you can know, to some extent to some varying correlation depending on how deep you go on the region's, you know, varying correlation, you can know, also market valuations. And the reason is, it's just it's a fundamental asset. It's not that complex, you know? And so if somebody tells me Okay, well, now the market is different from the global financial crisis were widened, it's probably the burden than this burden is on you to figure out why what is different, what is different, it's in the end, it's just reversal. It's still driven by income, and so on. And so when there was all the financial, kind of Novo financial products, then excessive lending, and so on, and then the quiet declines were still predicted by fundamental analysis, if you will, that's kind of like
Dave Morgia:perspective, I think you're completely right. It's, it's a bunch of different levels of what you're evaluating on the macro level, I think you need to understand whatever region state etc, you're picking the risk tolerance that you are stepping into when you go there, then I think from there, you just got to be understanding that you agreed to kind of get into this market with this type of profile. And now you have to just do well by your investors to make sure that, essentially, if you're taking x amount of risk that your reward is, you know, basically, commensurate to that, and it's gonna exceed that over the long term. So you can actually can actually make sure that you're, you're doing well by your investors and not getting into markets that are too risky for the return, you can get them. Because if you're looking at, you know, delay in dob, and there'll be in a much more risky market, and they both return the same reward, then you're not really kind of doing the the best diligence for investors. So definitely, definitely important to note that so yeah,
Stefan Tsvetkov:yeah. And they know, like, sometimes, like, this kind of stuff sounds a bit general on the market side, because, you know, I know this invest in myself, like properties is what is the most important, I think we didn't have time to touch on that, actually, I am guessing, but, you know, actually, on the property modeling, and that's because that's actually what's taking most of my time, to be honest. The properties that takes most of the time, but in, you know, to no surprise, right, but but it's just on the property side, like they feel like many like investors if you okay, if you buy the say like, Okay, if you buy try to buy a discounted property, and you're gonna be fine. Well, it's true. But now, if you bought the discounted property at the peak before the financial crisis, now it would have, you know, it kind of going to wait, at least it's gonna wipe out all your labor, let's say that you put in finding that deal, right, which is sort of the source of your labor expense, if you will, right. That's, that's all that we do. Right? We just try to find the deal. And that's what we're, essentially that's where our compensation comes from. Right. And that's where it's contained. And so it's kind of going to wipe out your, you know, your that perspective, so it's still not desirable. And, yeah, just kind of, like, be aware of aware of that is a portfolio manager, you know, that's kind of where they've been, you know, pointing to
Dave Morgia:Yeah, it ultimately, like you say, you can, if you're talking, you're investing for 3040 years long term, you can get into any market you want. But if you're if you're looking at that type of thesis, you should be kind of selecting your markets with some intention. So definitely, definitely appreciate those sentiments. And as Stefan I just like to get to these five key questions, I think if you're if you're ready for them. Absolutely. So first one here is if you can only pick one trait that explains your success. What is that trait? And why?
Stefan Tsvetkov:Analytical I guess? Yeah, yeah, that's the main one.
Dave Morgia:And then, what is the most uncharacteristic thing you have done in your business? Whether it was Realty quant or the real estate and why did you do it?
Stefan Tsvetkov:Oh, that's an interesting question. For the most Socrates, you think actually, I myself as an intrapreneur, everybody has different approach I don't, I don't so much consume content or how to say or study the industry like it may sound weird since the day I have my own webinar. I have learned a lot from it, indeed. But i i I have not read a single real estate book for example. And so first up to my anchor anchors, anchors characteristic approach or theme that I have done in my business is actually kind of trying to shy away from how other people in the industry do their stuff I notice it they try to a little bit worrying from it, but they don't want to get to him for influence and get in a way like producer healthy because then you cannot be normal and you cannot come up with your own ideas. And so I'm always really really cautious about that. So I tried to there is this trade off of consuming content and then you are going to end up like everybody else or you try to a little bit kind of get it and so I really that's the most I feel this the most interesting characteristic actually shy away from too much. Too much industry content since I just don't want to get build up kind of prejudice, if you will, or something is that just that's for
Dave Morgia:me? At least now, that's interesting, you put that box around yourself, right? And it's just like you kind of just put yourself in that box that everyone operates the same way. And then it's, um, you know, you stop thinking creatively, or is there a better way or those types of things? So yeah, that's, that's really neat. That's really, really neat. And then Stefan, can you name a time where you felt like you weren't going to be successful? And how did you overcome that fear?
Stefan Tsvetkov:Yeah, that's a great question. Well, I've dealt for example, like when one I have property in New Jersey, for condominium conversion that I've dealt with, like some pretty, pretty serious, if you will, sort of municipal level kind of policies, you know, where like, you go to meetings with the mayor about all kinds of stuff, and you're dealing with, like, some kind of serious, northeast regulatory stuff. And how that was for me, like, kind of where I thought I can perhaps is, that's gonna be like, perhaps the first deal that I'm gonna, it's gonna fail or something, we're not going to well, you know, just due to sort of like, excessive kind of extreme socialist, if you like, kind of policies or like, in an optical kind of political kind of way. And so yeah, so how do they overcome that thing? Honestly, I think I didn't, I just kind of suffered through it. And kind of just like, got through, and it recently got got got a resolution that is in our favor, it just kind of took a pretty long time.
Dave Morgia:Yeah, thank you learn more through those types of events than the ones that go easy. So hopefully, hopefully, you got a couple of lessons out of that one, but glad it's working out now.
Stefan Tsvetkov:Yeah. your earlier point? Is New Jersey a good state?
Dave Morgia:No. It's not, it's not just the one measuring you got to put them all together to paint the big picture. And then flip to that, can you name a time or something in your business went perfectly? And what did you do to make that a reality?
Stefan Tsvetkov:Yeah, great question. Oh, just another property example. So I purchased like a four unit upstate that happened to have like an additional like studio unit. And then I didn't know we're not touching the property whatsoever. And just like, are they like a smoke detector is something that 50 generate and work with the town to make illegal and, and so it kind of played on like residential versus commercial appraisals. And so the appraisal, so that was, I would say, like the, it's not the biggest return, but just like the easiest were like doing nothing and sort of literally nothing and just like double the bottom
Dave Morgia:of the property. That is a wonderful way to pull out equity right there. Yeah, so that's really nice. Went from a comp to to kind of noi evaluation that's really interesting.
Stefan Tsvetkov:In the game. Absolutely. That's kind of not the biggest return, though. But because it's just, you know, like a four Plex, you know, upstate. Yeah,
Dave Morgia:not necessarily repeatable, but very cool. But
Stefan Tsvetkov:they kind of do a phone call. It's kind of fluid, since I was sort of a little bit working with data, like for this kind of opportunity. And so it was not entirely entirely work. There was some some bases there.
Dave Morgia:Now, that's awesome. And then the last one here, what have you been focusing on lately? I mean, I think we touched on it, but what have you been focused on lately to improve yourself or your business?
Stefan Tsvetkov:Great question. I've been focusing on like building my processes better. I've been searching for acquisitions, analysts to kind of join me and like work with, like, some of them, like you're writing code or spied on scripts and stuff to discover deals to model like commercial multifamily and all that. And it kind of worked together with those systems. But you know, that can't provide the human component. And still, like underwriting since a few I am not like, very good at kind of doing it consistently. I kind of get bored. Like, you know, I coordinate underwrite deals all the time. And so that's one thing that I've been focusing on improving in, in the business. And in myself, I would say, Yeah, consistency and prioritization. So
Dave Morgia:now, that's amazing. I think, obviously, you have a very data driven background. So just to hear that you're working on, you know, scripts and stuff like that, to get the deal sourcing on that's super, super interesting. Probably Probably an entirely different show with to be honest. But yeah,
Stefan Tsvetkov:that's, that's really the other. That's sort of the bigger part of that is you're learning investing.
Dave Morgia:Well, yeah, Stefan just wanted to thank you for the time I know we really kind of niche them to like, just taking a holistic picture of a market and kind of applying datasets to it and applying you know, different types of risk to it and looking at reward. A lot of really useful stuff I think everyone should be considering when starting to address which market or sub market etc. You should be kind of addressing or focusing on investing in. But yeah, just for the listener if they wanted to reach out do you want to let them know how they can reach it today?
Stefan Tsvetkov:Yeah, absolutely. Realistic. ones.com is my website. And they have a YouTube channel finance Mitsuyo estate on YouTube. Awesome.
Dave Morgia:Stefan, thank you so much for the time today was
180 video:awesome.
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