In this episode, a June 2026 realtor.com housing report gets dismantled to show how PR framing masks the real state of the market. The headline (asking prices down 2.5% year over year, pending sales up 3.7% for the seventh straight month) reads bullish until absolute numbers are pulled in: pending sales are sitting near GFC-era lows despite a materially larger US population. Active listings hit roughly 1.1 million, a 92.2% increase since June 2022, while the median sale price still ticked to a record just above $400,000.
Key Takeaways:
- Relative percentages hide absolute reality A 3.7% pending sales increase sounds like a recovery until you see the market has been flat at 2008-2009 volume levels for four straight years, worse per capita than the GFC.
- Follow the incentives on every report Realtor.com, Zillow, and Redfin have genuine MLS-grade data, but their revenue depends on an active market, so the framing always leans optimistic.
- Days on market says nothing right now The median home sat 53 days in June 2026, identical to June 2025, with the Midwest and West actually getting slower and only the Northeast improving (by two days).
- New builds are the leading indicator, not existing supply Existing inventory shows 3.5 months of supply thanks to the lock-in effect, while new construction sits north of 10 months, with land-banked lots pushing past two years.
- Affordability is the tell nobody quotes Roughly 75% of potential buyers are priced out nationally, with Miami at 0.4%, LA at 0.5%, and New Orleans at 2.7% of locals able to afford a home on median income (Pittsburgh leads at 54.6%).
Listen to the full episode for the complete metro-by-metro affordability breakdown and the framework for stress-testing any real estate report before you act on it.
(Podcast transcript below)
Welcome to Get Serious, where at Serious Land Capital we have successfully funded over six and a half million dollars worth of land deals with industry leading 41% operating margins. I also serve as an AI consultant for companies cumulatively doing over $50 million in annual revenue. So today I really wanted to dive further into real estate.
macro reports and how to really assess the market. just because there there’s so much spin thrown in here, like it is it it it’s one of the most difficult areas to really grasp, and get an idea on what is actually true or not. Cause some of these reports you can be like, things are really turning around within real estate. Other reports are like, yeah, this is still one of the most difficult, if not most difficult, selling markets.
in the past hundred years in in the US here. I think the evidence is more toward that that latter point here. but you know again we we have to view all the data that comes in through as an objective lens as possible. so I just wanted to dive dive in again we could
Done a whole bunch of podcasts about this, looking into past real estate cycles and and so forth here. so you know, we we can’t dive into every single metric, but I want to clue you in just as far as a statistical overview and how to think, you know, again, more like a scientist. a lot of this I I learned back in my medical career, and trying to apply that from a from a real estate perspective. So
we can understand how to actually sort through the numbers being presented in front of us, where to dig deeper, where to be more skeptical, and where to like really
you know, take a a, you know, more f firmer understanding of or or firmer grasp on particular numbers that that come our way, that might have you know a greater or more solid foundation behind them versus some that you know are potentially a bit f more flimsy when when we dive into it. So and and again we always have to keep in mind like the incentives who is presenting the information
in in front of you. Everybody has some type of bias, some type of incentive, something they’re trying to sell you. like that is just the nature of all information being distributed. I don’t know if there’s any like truly objective source out there. and whenever, so like to me it’s always involved Ravakant Latin phrasing, nullius and verba. don’t take anyone’s word for it.
Including mine. So if you want to dive into any of this additional info, like go ahead and fact check, go ahead and review. Like anytime I’m even searching anything with, you know, doing a AI background research and so forth, like any information that that’s coming in and whether it’s a well renowned podcast guest, whatever, book that’s highly regarded doesn’t matter. Like I have AI automatically.
Fact-checking, okay, where are some of these claims, you know, do they line up with what the actual evidence is? the most gold standard evidence we have available, some that needs to be corroborated further, some like it’s an unclear answer, some that’s like very counter to what the present presenter is saying. So sometimes even when I when I do these podcasts, like I’ll think back to it you know later, later on, or maybe I come across some new information even over the
you know, next couple days like, yep, didn’t quite get that. So just just keep in mind everybody has some fallibility here. I try to be as well researched as possible when I’m presenting anything. but that’s just a clue to keep your antenna up when it comes to assessing claims from anybody, including yourself or your past self. So with all that in mind, yeah, I recording this in mid
July twenty twenty six here. Some of you all might have seen some of these reports that come over like the PR newswires and so forth. Again, they’re you you you have to like anytime you see news reports like this, again we we know this is this is public relations, right? So that that shouldn’t influence you. Hey, this is going to have some bias behind it. So
You know, in in this case, it was a June housing report by by realtor.com. so yeah, realtor.com, right? You just see within the name there. you know, I really like the the sites, you know, realtor.com, Redfin, Zillow. I I do think they have a lot of quality data behind them. Obviously, like they import raw MLS data, which is
Some of the best quality data you could ever ask for when it comes to you know real trends within within real estate here. but keep in mind that they are websites that are really oriented towards on market listings and the realtors that and brokerages that are representing those listings. So you have to assume there’s again.
Incentives in play to potentially influence reporting that would encourage a more optimistic, or at least not like overly pessimistic view of the real estate market. Because again, like their livelihoods depend on it. even the you know technical and engineering teams behind these technology platforms like Zillow.
They’re not going to get as many hits on their website and you know, incur revenue if if the real estate market is not as active. So that’s what I would really want to continue to key in here as we go through this. but you know, critically, in this particular report, the there’s a whole bunch of data here. And sometimes like it’s hard to parse through all of this. So I’m I’m gonna try to do my best to like.
point out again where exactly you should be focusing on. But the headline here was asking prices over the entire country. fell two and a half percent over the past year.
Whereas pending sales actually rose 3.7% year over year. And they’re noting this was the seventh straight month of growth. so that that’s kind of the headline there. Keeping in mind
Well, yeah. They we we have to we have to address the consideration of how long this data has actually been recorded here. So for this realtor.com data, it looks like they had started recording all of this since twenty seventeen. So almost ten years of data, like a pretty solid sample. but you know, keep in mind you’re not gonna be having the great
Or gl global financial crisis, you know, the 08 period, or early two thousands and so forth here. So you’re missing a whole bunch of other markets that were highly influential when it comes to significant market adjustments here. But you know, 10 years of data here, like we we’ve seen a lot of changes, all all of us can can agree on that with a fairly balanced market. pretty bullish, I would say, in the last you know, the the end of the twentyens.
then extremely bullish for the first few years post-COVID. And then it got really nasty as far as having more sellers versus buyers, really since mid-2022. so looking at this takeaway again here, if we see just the face value of this asking prices decreasing, pending sales increasing, it’s like, okay, we are starting to top out the market here. we’re we’re finally
starting to soften on some of the pricing. People are more encouraged to come back into the market and start making some purchases here. Yeah. Looking at that, it’s like, okay, yeah, really, you know, positive sign here. Maybe you know that this is the time to really start trying to trying to sell more inventory when when when you’re looking at that. however
Looking closer at the data here, well, actually I I want to go a bit more peace. I don’t I don’t want to jump off those couple of numbers right off the the bat here. First, whenever I’m looking at reports like this, and this is the same like if I’m looking in other statistical studies for you know peer-reviewed medical research, anything like that.
see I don’t know, for example, like a 30% decrease in breast cancer i incidence, something like that. And this is the difference between relative relative changes in in numbers for versus absolute. So the relative is percentage here, whereas absolute is the you know true number that has actually changed. So
You know, if we had pending sales, like let’s just use round numbers here. Let let’s say we only had a hundred pending sales. I know that’s like super low, but do again, this is just an example. A hundred pending sales a year ago in the month of June, and then 3.7% increase, which when you look at it, it’s like, okay, this is like pretty substantial.
when when we’re looking at the the numbers here, certainly trending in the right direction. But from an absolute perspective, like that would only be an increase to like just below four additional sales. So like a a very minor amount in absolute terms, that diminishes the relative increase in you know the the actual
you know, total number of of sales that that have gone pending within the national market. so obviously that that’s not the correct numbers, but e even if we expand that out much more significantly, when when you do look at those absolute numbers and you know total amount of pending sales and you look at the number of sellers on the market versus buyers on the market, like the it has been historically low.
over the past four years. and Reventure has data that’ll often look at it. And just looking at you know total pending sales, we’re we’re basically at a nader. Like it it is, it is as bad and as low from an absolute number perspective as it was like in the peak of the global financial crisis, the GFC. so we’re we’re looking at like eight, nine levels
of where pending sales are at currently. And critically here, I know this is something I’ve noted on before and written about before, is that like we’ve been stuck in this you know, depression or real really this valley for like four straight years. There have been like no noticeable changes in pending sales, like flat for for four, four years at this point, whereas during the GFC, it actually bounced back a a bit quicker.
you know, I don’t have the data immediately in front of me, but I want to say like it didn’t last more than 18 months roughly, before you started to see a bump back. so when you have something like that in mind, now all of a sudden, okay, a pending sales increase of 3.7% year over year, which again, like we we we want to applaud that. Like that is a better like I would rather have pending sales even if it increased 0.1%.
o over a period of time, like that’s better than going in the other direction. But we have to keep in mind, like, we are still at a historic low, where you know, all all the alarm bells should be going off as far as, you know, lower amount of pending sales actually happening. And it’s probably actually worse in comparison with the GFC because our population in the country was lower in in that period of time. I don’t know, yeah.
I think we have in the US like somewhere around 330-ish million people or something. you know, you go back almost 20 years, I want to say it’s closer to like 300 million. So yeah, again, don’t fully quote me on that one. I I don’t have that data in front, but like you that this is another cue. hey, you could look at this yourself if you wanted to. But assuredly, the population of the US is without a doubt higher than it was you know, eight eighteen some odd years ago.
when when we would look at the data. So that makes it even worse if the absolute number of pending sales is lower or as low as it was during the GFC because of the increase in population. So that just means like percentage wise there there’s even less pending sales happening as a total a total population is concerned.
So that’s what I really want to throw out there because like they’re the th this realtor dot com report is like really pinging in on that. yeah, I’m just going to
Yeah, so
You know, just the way they were phrasing this, again, sometimes you just have to like parse through the PR speaker. It’s like, you know, a headline, buyers keep responding, pending sales rise for the seventh straight month. Again, like you could look at that headline number. That’s what a lot of people will attach on, but like I just broke it down for you why it’s not nearly telling the whole story when we’re when we’re looking at the true situation of what we’re looking at.
And so it’s saying, you know, pending status, the or the stock of listings and pending status has, you know, extended the growth streak to seven consecutive months, which we mentioned. the longest such runs since December 2020 through June 2021. So, like that’s even cueing the reader of like, yeah, that was like a really bullish time in the real estate market. So I guess are we like trending in that direction again? and you know, I’ll I’ll credit them to saying, like, hey.
He let’s steel man this argument a little bit. Like there’s no sign that rising pending sales are masking a wave of broken deals, like contract cancellations in April and May came in at almost 7% of pending sales, modestly below the 7.3% rate a year ago. so taken together, this data pushes back on the concern that rising pending sales are masking a w wave of deals.
falling apart. Homes are going under contract and they are staying there. Like that that that is a good con note there.
So again, like they’re starting to attempt to steal man their their argument a bit here. but you know, again, not really going into, hey, this is like still maybe the worst time in US history in in terms of you know pending sales in relation to the total population. So have to to keep that in mind.
Yeah, they they all also note that time on market and a twenty-six month streak of you know, months in which homes sold more slowly than the prior year. Again, like that’s that’s good to note. and they do note okay, median homes spent fifty-three days on the market, which is actually identical to the the same month a year ago. So like again, it’s like not not the
W when you really break that down, first you’re gonna be looking like, wow, like twenty-six month streak, you know, days on market kept getting slower here, but you know, i is it really that different when we’re looking at year over year data here and we’re looking at June 2025, where the median home was on for fifty-three days and now it’s fifty-three days again in twenty twenty six. So very in in my opinion, like
limited in terms of the utility of of that data. and you know that that’s telling me as well, like, okay, days ticking up, how how much is it really changing? they they don’t mention across the entire nation, but they do break down the northeast and midwest, west, and the and the south. And it’s like very minute
changes here. So like if we’re looking at the Northeast, where we know some of the best performing markets are for for actually moving inventory, it’s like minus two days, right? Like hard to really build in a a stronger trend looking at that. Okay, Midwest is actually plus three days. That’s actually a note, a little bit more negative than you’d expect for a stronger market in the Midwest, plus two days in the West and flat in the South.
So again, it really doesn’t it really doesn’t tell you anything. and if we’re breaking it down from a you know, 26 month streak, where the median home’s on for 53 days, but we’re seeing okay, in two of the markets, the Midwest and the West, it actually got longer. The south was exactly the same, and the northeast was just slightly less. So
That’s probably saying that there was more activity in the Northeast. So that actually decreased the total days on market here. So that’s telling us, okay, Northeast still a bit of a stronger market here. Everywhere else is a bit worse. and maybe even more worse than the data is telling us because the the time on market is
Yeah, not n not even being able to outpace one one fourth of the US roughly in terms of you know geographical b breakdown, that that’s driving most of that decrease on time and market, whereas everything else was, you know, stable or going up here. So that still to me is like a more negative view on that that particular metric. So
Yeah, like I I I could point out a lot more of this, like these are fairly data heavy reports here, but th this is to give you an example on like, okay, what do each of these numbers actually mean? what what decisions can you can you arrive at when when we’re looking at this? That this is this is the key thing about looking critical. And you could you could throw this into AI and ask like how how how do I avoid the spin?
you know, associated with this particular data. I mean maybe you can even create a prompt on on how to look at that, but that that’s something that that I would consider doing. And so again, you can really double check the claims. What what does this actually mean? How do I corroborate this? but you also have to keep in mind that with AI, it might be pulling in a lot more other reports that are like these PR news wires. And so like it
it it has to be guided to figure out okay what what’s the story behind these numbers. and why again you still have to have that ability to think critically and realize, hmm, i is there still something that that might be missing here, e even if you do parse through AI and try to look for for for the guidance in in the data out there. Because remember it it only has a access to anything on the internet.
And it’s not able to think beyond that. So noting that, I’ll jump in through a few other examples here. One is just to note that you know even though you know listing price had asking prices had fallen two and a half percent and the pending sales technically increased, it it still didn’t change the fact that.
the the median sale price was a a record high. that
that that the national housing market actually hit just like a tick over $400,000. so okay, listing prices decrease slightly, but yeah, sales prices still up from that. And it’s like, how how do you kind of square that data here? Where again, like we think this is like the most difficult housing market maybe ever to sell anything. But how is the sales price still keep going up? And to me, it’s
probably pushed up a lot more when we are considering more of that k-shaped economy and looking at you know the significant number of you know million dollar plus homes that are bumping up the average more and that that is a key difference to keep in mind is like
Okay, you’re you’re looking at the median versus the mean price. So if we remember back to you know math class from elementary school or middle school whenever we learned this, like the mean probably would be even higher because that that’s the average, and you’re gonna get those massive outliers. like I don’t know, I saw a sports fan, I saw like Anthony Davis’ LA home sold for
$30 million or something, like just massive. whereas like you can only go closer to zero, like that you you’re you’re not gonna get as much of a extreme range on the lower end, just because you like that there’s not as much room to move. But you know, houses, there’s you know, a hundred million dollar houses out there that could you know significantly bump the mean when when you account for them. but e even a tangent off that, like in in that luxury market, like
Beautiful Bel Air home that this this NBA player Anthony Davis had. And you know, he actually had a listing price it took like nine months to sell, something like that. It was around like $39 million, which was according to Zillow, like 30-ish percent above the market value of the home. And selling for 30 million, it was actually like 25-ish percent below market value. So it’s e even showing there in the ultra luxury.
market, mm, can you really get the listing price or even like the market value that that’s expected? Maybe that is softening a bit a as well. but yeah, you’re you’re accounting for like the the mean is going to be driving up those numbers.
Yeah, if we’re u using the mean, the average, it gets wrecked by outliers. but the median doesn’t care about that because that’s just the middle value when all sales are sorted from cheapest to most expensive. Yeah, so that’s right here.
I was trying to remember how we did this back in middle school again. Like the way you would sort out the median. say you have like 10 numbers and you just start crossing out from each range. Like if I have numbers one through 10 whatever. So I’m I’m crossing out one, I’m crossing out ten, I’m crossing out two, crossing out nine. And I just keep crossing out one after another on each end until I arrive in the middle here. So that’s why.
Yeah, you’re not gonna get wrecked by as many outliers, like the thirty million dollar type of sales here. Same thing with like super distress trades either. but it really tells, okay, that this is the actual middle to to arrive at. nevertheless, like still important to note because to me that’s still telling like
K shaped economy, you’re you’re still getting much higher price properties that are moving that’s still pushing up that median sales price even higher than expected. and maybe like the only people actually able to close on properties are those who are more well to do, anyway. And so like that can just tell you a a measure of the economy at at the moment.
As as well here. also there was one other key piece of data. Yeah, when I’m looking at the active listings, it’s like around 11 or 1.1 million in June of of this year here, which is like roughly equivalent to where we were pre-pandemic. but it’s a change of ninety-two.
point two percent. So almost almost a doubling since June of 2022, which again, we could think of that generally as like the shift from that super bullish market to a much cooler market here. Like that is a massive number to to account for. To where it was like, yeah, we you just there was like no inventory available. Everybody was bumping up prices four years ago here. And now there’s a
doubling in in inventory. that that to me is like an extremely telling number when when I was parsing through all of this data. Like, okay, yeah, so many people are just not able to move properties anymore. or it was like a lagging indicator. They they got in too late once the interest rate started bumping up higher, and now they can’t really move their properties. So that that’s another piece to
consider here. And some people might look at like the, you know, I’m looking at some redfin data now, that was also from June of 2026. And it’s it’s showing the months of supply at like three and a half months. And so you might look at that as like, that’s actually a good seller’s market. but it it’s so heavily biased from the existing inventory, where again, there’s still so many people who are more in the lock in effect or not really trying to move from their properties. But if you look at new builds, the
Months of supply is like north of ten 10 months, something like that. And I think that’s averaged all across, you know, full fully homes that are complete, ones that are, you know, lots available versus like l land banked properties. And it gets higher, like that month of supply is like way higher for the those latter two. Like some something outrageous. Like I think that the when we’re accounting for land land bank properties.
Like that became such a boon of an industry over the past five years. But it it’s something like twenty I th I want to say it’s like more than two years of total inventory. Like the sky high numbers that we’ve never seen before since this started being recorded here. So like we have to keep that in mind. What again, how how to read into these numbers more thoroughly and also account for, yeah, new builds are you know a fraction of existing inventory when it
when it comes to homes. So that’s why like the existing homes are you know driving down that month of supply number compared to new builds. But I would view the new builds as more of a leading indicator to where the housing market is heading. for for a number of reasons. So that is another piece to to note here.
And you know, a a handful of other things here before we wrap up. just looking at some of the metros with the biggest year on year year-year increases in median sales price. First off, San Francisco is just crushing it at almost eleven percent, which you know, when we’re looking at it, it’s like, yeah, all the benefits from the AI boom are like, yeah, heading back to the Bay Area. So you’re getting the anthropic, the open I open AI, SpaceX IPOs.
the these big AI booms and yeah it it’s it’s solidifying around you know the primary housing market. But interestingly, San Jose, right around the bay, is actually the second worst metro in the entire country as far as year over year decreases in in median sales price. So that to me is a pretty interesting note. it’s not the entire Bay Area, but you know, specific to SF in and of itself.
and also noting that West Palm Beach is actually the second highest biggest year over year increase, again, almost 11%. and even though Florida has been, you know, getting kicked in the teeth in in regard to reduced sales volumes, you know, we we think of the cert you know K-shaped economy again, like West Palm Beach, a lot of you know older, richer folks moving down there and you know, very limited space in which to build.
or or have real estate. like that that’s why it’s trending on in in in that higher direction. So something to note on that end
And I’m actually looking, I I’m seeing some of the like roughly four months worth of data on the pending home sales tick up. And so we we can actually see over roughly four weeks.
what what what the total pending home sales actually is. So, you know, I was naming like a thousand or a hundred homes as the actual amount. So like over roughly four weeks or so, you’re getting about three hundred, three hundred thousand homes. This does not really make sense. So that this is like interesting. I’m looking at this data and it’s not totally making
making sense to me because if we have
1.1 active listings in June. We’re getting new listings, like 400, some odd. So are we really getting 300 300,000 pending homes a every single month here? I I would look into that. and when I do this over the newsletter, I’ll be able to answer that more thoroughly. But I I did I even want you to hear my live thinking sometimes on this of like, okay, I’m looking at these graphs.
How do I really interpret these to ensure that I’m seeing the correct numbers here? nevertheless, regardless of whether that’s four weeks, three weeks, or you know, even over the course of the whole year, you know, we’re looking at pending sales pre you know, spring, you know, seasonal bump, like in February of 2026, it was at like, you know, 305,000, 310,000 pending home sales. And who?
The absolute peak that it hit was in late May for like 340, but now sitting in June, it it was sitting around like 325,000. So it’s like it’s really not that much of a difference. E even at like the lowest part of the year to the most active part of the year. you know, I’m just running these numbers now, like 305 divided by 325. It’s six or seven percent difference from lowest part of the year to
you know, kind of the peak of the year. it’s like not not a massive change. So just again, kind of something to to keep in mind. Where in this case we were actually looking at the absolute numbers and it seemed like, yeah, it’s a bigger trend here, but we’re looking at the relative, it’s actually not that much. that’s kind of driving real activity here. last piece to comment on, and I’ll go quicker as we got tied into so many of these, is that
you know, an article that was noting you know, just American’s dream of home ownership, which is still like a huge dream. Like almost half of Americans, like when we consider the American dream, most Americans consider owning their own home to be like the number one factor when it comes to living the American dream, like more than getting married or having kids, whatever, getting college degree and and any of that. Like owning a home is still a big piece of what people desire and
even as high as these home prices are, like most people within the country would prefer to own a home versus continue to rent. However, it just makes a lot more mathematical sense at the moment to continue to rent and you know people aren’t getting pushed into home o ownership. and when you look at this, you know, this is at end of 2025, still like pretty relevant data. the average American we’re looking at a median or you know a localized median household income
Like 75% of potential home buyers are priced out of the market. we we would be anticipating, okay, what’s what’s more average. yeah, if you can be closer to like obviously it would be you know, the best case scenario, like the all ultimate economic dream is like a hundred percent of people can afford h homes in the market, but obviously supply and demand would rebalance that out over time and
sellers of homes would be looking to you know bump the price. So, you know, a balanced market would be roughly 50% of the market could afford a a home in their area. But w when it’s at 75%, like the obviously that is prices so many people out. and
I was looking at this map of where it’s kind of saying share of affordable homes. And it was going all across a whole bunch of metros in in the US here. and I thought it was like I I hadn’t seen this data before, like really i i interesting to note because like there’s there’s really only a handful of cities that are close to balance. Like it’s really St. Louis, Missouri, that’s at like 49.7% on affordability. you get Cincinnati.
At about 40%, Louisville, about 35%, Detroit around 42%. Pittsburgh is actually maybe the most affordable in the country at 54.6%. that that’s actually the number three market in the country as far as median sales price, though, too. So maybe that’s not gonna hold up for quite as long. because now people are just trying to push in in that area. And so that might actually make it more expensive. and then we look at
Man, some of these like really major metros like Boston, 4.8% of people local to the area can can afford New York City, 4.9%. I mean, no surprise there. but just down the turnpike, Philadelphia is about 30%. like big difference compared to to New York. and then you would think about some of these more boom, post-COVID boom markets like Charlotte, only about 20, 24% of people.
could could afford homes in that area. Atlanta, only about 30, 31%. Birmingham’s a bit better, closer to 41%. Miami, I think that’s the lowest here. 0.4% of people local to Miami can actually afford a home. Tampa’s eleven percent, Orlando’s eleven. New Orleans, you would think Louisiana, you know, a poorer state, more affordable on by a lot of metrics. Only two point seven percent of people local in New Orleans can afford a a home.
according to their local median income. Texas, you would think again, generally, I know there’s a bigger boom town, but you know, still more affordable. No. Dallas, twelve percent. Houston, fifteen percent. It doesn’t have Austin on here, probably pretty low too, still. San Antonio, twenty two percent. So again, not not great. and then you go over to the West Coast, even worse. Phoenix, sixteen percent. Las Vegas, fourteen percent.
LA 0.5%, San Diego, 1.6%. That’s actually even worse than San Francisco. San Francisco, at least 7.3% people can can afford. Salt Lake, 16%, Denver, 16%. Portland, only about 10%, Seattle, about 9%. and e even in the Midwest here, like still not tremendous. Minneapolis, about 31%, Chicago, only about a quarter of people, 26%. So like you saw, I I named
most of the major metros within the US and like y you could kind of run the numbers. We were saying, yeah, about seventy-five percent of people are priced out of the market and about out of all those cities, about seventy-five percent of them were like way down the list as far as affordability. Like no wonder people are feeling stressed or only are only a able to rent and not able to afford homes. w w within those particular metros. So I thought that was really interesting.
data, something I had not seen mapped out before. so just wanted to to mention that as well. So again, in summary here, I really hope this gives you an idea on how to think like a statistician, really dive into the numbers and realize when you’re being sold a certain story, how to use your critical thinking to determine when you need to go deeper into certain numbers
you know, how how to interpret you know, relative values versus absolute values and relate them back back to each other. and again, biggest takeaway, asking more questions. What’s the real story here? So hopefully all these examples I went in in kind of gave you a better idea on on what to look at on on your own terms. Yeah, you can fact check any anything that that I mentioned here as well.
on your own, how to utilize AI to help check claims as well, but also knowing when to push back on AI, knowing that it it’s gonna be pulling from biased resources as well. so, you know, it’s a constant judgment cycle, it’s a constant critical thinking. And, you know, the the people who are able to succeed, like you have to know when to zag when a lot of people are zigging.
And if you get people who are just too optimistic about real estate thinking it just goes up forever. It’s just not it’s just not necessarily the case. and they they were actually running some math here. Like if you just took somebody who’s just renting, you know, a average rent versus, you know, getting a mortgage on a on a home, kind of average home in the US, like we look at retirement accounts later in life and the the renter like vastly outperforms the the homeowner here, which you know.
To me, yeah, primary residence, I really wouldn’t consider that to be a in investment when you’re paying all the property taxes, et cetera. like you’re always gonna need a place to live, but thinking of it as like a core part of your net worth is to me a a dangerous line of thinking. especially if you have a a heavier mortgage.
on the property limited equity but even if you have like full cash buy equity in a house yeah you could use a HELOC to to pull pull out and borrow against your house. but as far as like true liquidity I just wouldn’t view it as much like a a a very solid investment asset. I I don’t think my own house in i in that regard certainly so additional food for thought here
On the US real estate market. Hopefully this one was interesting to you all. Let me know in in the comments or you know, DM me if anything was confusing, or if you want to hear more content like this, I’m always open for feedback. again, you can always submit deals for us to review, seriousland.capital, or look out for our co-work plugin for pricing out land deals, the SLC chat co-work plugin coming out down the line. And if you want to
Work with me to implement more AI within your business. I’m taking on a very small number of clients to work with. again, currently I’m consulting for over our companies with revenue of over $50 million in total on an annualized basis here. So those are the bona fides to to keep in mind. with that, subscribe and share, everybody. Looking forward to next time. Bye.
