Crazy. I recently sold a condo to Opendoor for significantly more than I would have even thought to list it for. When I negotiated with Opendoor after their initial offer, I pointed out a recently sold condo (days before, in similar condition, layout and finishes) in the same complex that sold for much higher than Opendoor offered. Within hours Opendoor came back matching that same selling price. The kicker? It was a unit that Zillow bought.
The algorithms are fooling themselves... Opendoor matches Zillow who matches Opendoor and that's how you get ever increasing offers.
Edit: oh, and now Zillow has that unit on the market, priced 14% lower than they paid for it, after 3 price cuts so far.
Very much like the $5000 books on Amazon where the algorithms are anticipating flipping an existing listing. Congrats on winning this round! The next step might be interesting which would be to go back and re-purchase the Condo once the price corrects to the 'real' price and bank the difference.
I have read this article and the one before it and it sounds very much like some folks who fell in love with their own idea and got early feedback that it was "working", went all in and never checked to see if it was still working.
The lesson should have been, "When you perturb an emergent system, never assume that the current state is the new steady state."
The most interesting thing for me back when I was in college was a discussion on of the professors on feedback systems gave on LA's freeway systems. There are three major interconnected freeways, 405, 110, and 10 which at the time formed a triangle. Now there is the 105 which cuts off the tip so perhaps a smaller triangle. The professor shared a paper that tracked "brake waves" which were aggressive braking maneuvers that would "propagate" backwards on crowded freeways. The paper showed that at the right time of day, an aggressive braking on any of these three segments could result in your own braking wave to "lap around" and hit you again. Sort of a ringing of the system.
This sort of effect can be present in any system that isn't centrally organized but is instead a result of the interactions within the system. Buying and selling real estate is such a system, especially when you are a 'market maker' in that system.
There are a lot of papers on how HFT trading algorithms interfere (both constructively and destructively) with each other on wall street exchanges. Just interesting stuff in my opinion.
I knew about the brake wave back in 1980, as I could see it on I405 on my way home from work. Due to a curve in the highway, I could see about 3 miles ahead. The wave heading towards me was pretty obvious.
I found I could "break" the wave by letting a gap grow in front of me that would absorb the wave, and I wouldn't have to brake to a stop (and so my clutch would last longer).
It never occurred to me to write a paper about it :-)
That's what I thought too until I started practicing this. Probably 75% of the time no one comes into the lane. It takes some practice to find the correct gap size.
Besides saving your clutch, you can do this type of brake-early maneuver at stoplights. Decelerating early and coasting at a lower speed means you don't have to stop and can increase your gas mileage significantly.
I sometimes do what the gp said - let a gap grow in front of me if I'm in stop-and-drive traffic and get annoyed when someone selfishly rushes to fill the gap in front of me only to have to break 60 seconds later.
On further reflection, that's not necessarily selfishness, more that they don't understand what I am trying to do, but there's no way to communicate complex information car to car on a highway.
I started a job in Fresno in 2013, driving up from LA on Sunday and back down on Friday.
Bluetooth had started to become standard in all cars, and as I was working on a train project, the idea occurred that if we could link all the freeway cars in series, and treat it as one long train, then I would essentially just have to steer, and we all would avoid brake-waves.
One car only needs to be able to talk to the one car in front of and the one car behind itself.
"by letting a gap grow in front of me that would absorb the wave" would cause the freeway to carry fewer cars if everyone does it. My oldest one used to argue with me on this point when I asked him to keep a bigger gap from the car in the front for safety reasons.
According to analysis from engineers, or Esther from a guy I used to work with who studied break waves for the state transportation board, less cars with larger gaps is better. That's why you see semaphores on highway entering ramps sometimes, ie 101 around SV or certain European big city inner highways.
This is a problem that can probably be solved someday with self driving cars collaborating to make highways huge coordinated conveyor belts.
Actually, this is a problem that is already solved by smart motorways in the UK (Europe too maybe?). They have a variable speed limit that dynamically changes according to traffic that stop brake waves happening.
If my experience with smart motorways is anything to go by they seem to increase brake waves because there are often times that speeds get reduced significantly for arbitrary reasons that not everyone chooses to follow. You then get larger closing speeds which causes people to slam on the brakes.
Additionally the removal of hard shoulders is just dangerous.
Seattle adjusts the speed limit on one of their highways down to 45 or 35 during rush hour which increases the throughput as the cars can be closer together. Not sure if that has been picked up by other cities.
You should read about the "Fundamental diagram of traffic flow" and it's corresponding diagram. It's very well explained and shows that throughput can increase when having fewer cars on the road
Ever since driving an electric car, I have come to believe that a gas-throttle car’s laggy response during stop and go traffic may be responsible for the elasticity of the delay propagation. From zero, a piston pumper goes through a complicated series of windups which seems like days compared to an electric motor.
Throttles have only become drive by wire over the last 15 years, prior to that it was cable actuated and was instantaneous. Like a lawnmower. One could argue carburetor cars were even (a fraction of a second) more responsive.
Also if you WOT a modern car you get the instant response without the ecu calculating pedal angle, comparing to accelerator history, humidity factors etc etc but kiss fuel efficiency bye bye. There are mods and tunes that reprogram the fuel map to cut out this processing time
I also drive a big turbo family sedan and am used to saying 2 Mississippi before the engine pulls at full boar
Though drive-by-wire throttles absolutely do modify and potentially hold back your throttle input for reasons of both economy, comfort and enforced driveline sympathy, there is also an inherent response difference between petrol and electric engines and also slop in the driveline system. That difference varies on the engine and transmission type.
Unfortunately I cannot find an easy good reference on what exactly that difference is quantifiably. Also many of the Electric cars right now are higher end even sporty vehicles, and more likely to have a throttle mapping that is more direct.
Brake waves happen because people brake harder than they accelerate afterwards. If you have enough following distance to brake gently, then hit the gas hard afterwards, and if everyone did this, then the waves would never appear.
I will see if I can find it, not all papers published in the 80's are online. (and I just looked the professor is emeritus at USC now but still around so I'll send him the question too)
Okay, so I'm pretty sure it was done by G.F. Newell (UC Berkeley) I haven't found the paper we discussed in '82 but he went on to publish a 3 part description of traffic dynamics called "A simplified theory of kinetic waves in highway traffic" and reading through the abstracts for those it covers the same territory we were discussing in the systems class I was taking at the time.
So Dr. Kuehl reminded me that he didn't teach me Linear Systems, he was teaching Electromagnetics at the time. (And no I don't know how I could confuse the two)
I believe the paper's author was Newell, but the USC professor was Dr. Kuehl (Dr. Cool :-). He was teaching Linear Systems when I was there and always had some really great "real world" applications of the stuff we were learning.
This is an interesting lesson in algo trading run wild. Roughly, house prices have a fundamental ceiling, and it is determined by the size of the monthly payment that banks will allow the typical homebuyer to assume when approving a loan.
If Zillow was the only iBuyer in a particular market, then that ceiling would likely have held, as all other non-zillow sales would still be operating under the loan approval constraint, and that would get reflected in the comps. But in a market with multiple ibuyers, none of which are capital constrained, it would make sense that they run up the prices against each other, past what the local homebuyers can afford.
Not sure how much that actually played a role here. But could be fun to do some back of the napkin math to see if that was the case in some of these markets.
> house prices have a fundamental ceiling, and it is determined by the size of the monthly payment that banks will allow the typical homebuyer to assume when approving a loan.
In the more irrationally-hot markets, why assume that housing is even being purchased on a mortgage by your average home-buyer, rather than being purchased cash-in-hand by a private or corporate investor looking to park wealth they've already generated? (Even if that isn't the majority of houses in those markets, the sales like that that do happen would still have an impact on property values in the affected neighbourhoods.)
Because the real estate sector is like 30-40 trillion. 2007 was the result of a massive infusion of debt by unsophisticated retail "investors" who bid prices up far higher than even their rental value. Lending standards dont allow this today.
If big institutional money is going to cause a frenzy it would need to be irrational money managers that somehow clear their purchases through a panel and none of them say anything. Some point out that blackrock is on the other side of this zillow unloading but they have trillions in assets and only 60 billion in real estate. This is the largest money manager in the world and thats all the exposure they have.
According to this article[1], large investment companies accounted to 16.1% of all single family home sales in the US in Q2. I'm not an analyst. But, I would think that would be plenty of extra demand to influence the price?
Perhaps. Unlike in 2008 though, those buyers aren’t typically hoping to sell those houses for a short term profit, most of those investors are hoping to turn them into rent income. This could easily distort prices, and have pernicious social effects, but might not be an asset bubble. After all, if those investors manage to actually charge enough rent to make a profit, is the asset really over priced then?
Investment companies are far less likely to lead a speculative bubble than retail buyers. They are professional investors who go through a valuation process. They have also always been part of the market.
History indicates the opposite. The largest speculative bubbles in history are typically driven by professional investors or high-net-worth individuals, not retail buyers.
Your fund managers make their money in short term win or lose. So they really do not have option to just sit on money, but have to look someplace to invest. Even if it doesn't work out in long term.
Where is this data coming from? Almost nothing you said is true or perhaps you don't actually understand what retail traders are. Retail traders, essentially by definition, do not have sufficient capital to cause large asset bubbles. Once an individual's net worth exceeds a threshold (generally enough to where their purchases or sales affect the spreads and liquidity of the underlying market) they are not considered "retail" by definition.
Even now, with retail being the most powerful they've ever been in human history, they might be able to squeeze a single, small or mid cap equity (GME being the most famous example) but they cannot move sectors of markets, much less create a generalized bubble in ANY asset class.
Crypto 2017 is the only "bubble" which you might claim was retail-driven (even then, you'd need to provide evidence for such a claim), and even that had institutional money such as Grayscale, high-net-worth speculators, and algotrading from high-net-worth speculators driving the bubble. Not to mention that was a tiny bubble relative to any equity market bubbles.
It's well-known Tech bubble 2001 was driven by investment banks. It's even more well known that the 2008 bubble was driven by investment banks, hedge funds, and derivatives trading. The current $2.5T+ market cap crypto bubble has been formed by large institutional buyers, high net worth individuals, and corporations pumping money.
Dutch Tulips, South Sea Trading Company stocks, 90s Japan were all from institutions or high-net-worth individuals (nobles, royalty, corporations, etc) as well. Your post really couldn't be further away from reality. The historic bond bubbles have all been inflated by institutions and governments. Making a claim that even one bubble, much less "most" bubbles are caused by retail, is an outrageous claim which requires extraordinary evidence that you would need to provide.
Im sorry but everything you wrote is just incorrect. The notion that retail cannot and has not caused bubbles in the past is asinine and your explanations of past bubbles are just factually wrong. Anyone in 2001 remembers their barber telling them which tech stocks they were invested in. The housing market was clear cut retail debt in 2007. And the entire crypto thing is retail. Blackrock is not invested in Bitcoin. You sound so confident but are just so wrong.
You need to read your last sentence out loud, to yourself, while looking in the mirror. You gave... an anecdote of a barber as proof? 2001 was caused by investment banks, venture capitalists, and changes in overnight repo lending. Not some folks each with an extra twenty grand chatting with his barber.
You're embarrassing yourself at this point between the barber and stating housing was "clear cut retail debt" in 2007 when it was actually a trillion dollar derivatives market that caused the bubble/crash, significantly driven by predatory/abusive from the mortgage lending side? Where do you think retail got all the money for the houses? "the entire crypto _thing_ is retail" uh, no, it's not. Tesla bought over a billion in bitcoin earlier this year, and large investment banks opened crypto desks early this year. And bringing up companies like Blackrock(?) which I didn't mention, oh my you are all over the place. Grayscale is not Blackrock... Can you present any evidence at all that retail has caused historical asset bubbles?
Sorry, you're just straight making things up and have a very poor or nonexistent understanding of markets. I won't waste my time here any longer.
Well you’re very dramatic and passionate but still very incorrect. The underlying housing market rise and collapse was from retail speculation, period. Sure they borrowed from banks but they still did the borrowing and actions. And who cares what the derivatives did in terms of diagnosing the underlying cause which was retail speculation. Wall street had a hand in causing the severity of the collapse theres no doubt about that, but they didnt drive the foundational bubble directly, only indirectly. The point is retail stupidity causes foundational bubbles. Derivatives made things worse but they were...derivatives, they're called that for a reason dimwit. And who cares about relatively small tesla position and “crypto trading desks” which have no permanent exposure. Thats absolutely nothing in the 2 trillion retail crypto environment. Crypto is retail driven regardless if its a big or small investor. Its not proper institutions buying. Please get real on this because you sound like a clown. I think part of the issue is you cant distinguish between retail and institutions. Retail doesnt become institutional just because they have a lot of cash/assets, rich people are still retail unless its a formal family office of which most people do not have (and even then Id say it more of a formality and still retail).
No, you're wrong on this and basically every single other statement you made. High net worth individuals are typically considered separate from retail traders, and yes, just because they have a lot of cash/assets. Part of the reason I kept saying [institutions OR high-net-worth individuals]. I didn't think that was such a challenging concept.
> Derivatives made things worse but they were...derivatives, they're called that for a reason dimwit.
>Please get real on this because you sound like a clown.
Real classy. Well at least I know now you were here just to be pompous and find a way to broadcast your lack of understanding of the market.
Nevertheless they are not buying houses for emotional reasons, but for the income stream.
FYI, the reason this is happening is that interest rates are so low that people are desperate for yield, and rental yield fits the bill.
There are a lot of benefits:
- professionally managed properties. Most small time landlords are incompetent -- the horror stories you see about landlords being petty or vindictive is from the small time landlord, not the professional manager.
- lower rental prices for properties people want to own. Institutional investors can move funds more quickly to increase rental stock where it is most in demand. Here, too, the yield will fall, which is another way of saying lower rents.
Moreover despite the moral panic by journalists that ordinary households are being priced out, this doesn't actually happen because most institutional investors operate in unconstrained areas, where home prices track construction costs, at most with a small delay. In these areas, an increase in renter demand will result in more property built much more quickly if the institutional investors participate. This actually drives down prices over the long term by increasing supply.
However in constrained areas, this would drive up prices for SFHs. But I thought people weren't supposed to buy SFHs in constrained areas - and institutional investors have been in the multi-unit market for over a century.
Yes, the correlation is not necessarily causation, but we can add some other data points -- for example the size of new construction has been steadily growing at roughly 2%, which does not suggest any kind of odd explosion in house size as a result of the price going up. Of course ultimately, ability to pay determines the price of housing and also house size.
> Because the real estate sector is like 30-40 trillion. 2007 was the result of a massive infusion of debt by unsophisticated retail "investors" who bid prices up far higher than even their rental value. Lending standards dont allow this today.
lol.
2007 was the end of a long road, paved by unsophisticated "money managers" and doubly unsophisticated "bank regulators" and even more unsophisticated "politicians" since WW2.
There are people buying houses for more than their rental value right now where I live. Because there's one crime-ridden trailer park maintained on the freeway nearby to make them all within a certain distance of a "disadvantaged zone" and thus every former manufacturing country factory boss looking to move to the US only has to lose $400-$500 dollars a month to buy his way to the top of the green card list.
> Under regulations ... an EB-5 investor would need to invest ... a minimum of $1 million normally or $500,000 in economically disadvantaged areas...
> You'll need to plan on having your money tied up in the business for several years. When you first get your green card, your permanent resident status will be conditional for two years. During the 90-day period before the end of the two-year conditional residency, you'll need to submit a petition to remove the conditions—to show you invested the required amount and created ten jobs. These two years and government processing times result in your money being parked until you finally get your unconditional permanent residency.
So practically it's pretty cheap to get yourself to the top of the list for permanent residency. All you have to do is buy a couple of $500k houses, rent them for whatever rent you can get for them, claim you created 10 jobs by hiring maintenance guys and landscapers and whatever else to maintain them, and then when you've got your paper from the US government you can turn around and sell them for what you paid for them (or even a little less, who cares, you bought your American residency).
The rules were changed from the original law to not only allow properties in economically disadvantaged areas but near them.
As I said, that's why there's a trailer park which resembles some "third world" country slums right on the freeway in the wealthier north Dallas suburbs where I live. All of those realtors selling rental houses to Chinese factory bosses, Russian mobsters' children, South American cartel finance guys, etc need them to be near the trailer park to qualify for the program. Similarly, via a ridiculous string of foot paths and bike lanes, Hudson Yards in NYC was determined to be economically disadvantage due to its proximity to Harlem, so they could also sell apartments that no one else wanted to Chinese factory bosses, children of Russian mobsters, South American cartel finance guys, etc.
If the current value of something is over a "fundamental ceiling" it means that it's already inflated. Why would an investor park their wealth in such an asset?
A large part of the "foreign ownership" plaguing west-coast cities like Vancouver and Seattle is capital flight from China. In this case, real estate has the valuable property of being harder for a foreign government (who happens to be the government to which the homeowner is subject) to confiscate+liquidate than other assets, so said government will prioritize softer targets. Real estate as an investment class here is acting like a club on a car steering wheel—de-prioritizing theft, rather than inhibiting it.
Sometimes there's just no good alternative. And real estate has less strict AML/KYC laws than other asset classes so we have some shady foreign money coming in.
Of course, taxes and regulations complicated this discussion.
It doesn't complicate the discussion, it is the discussion. Basically the only reason foreign investors are buying real estate in North America is because of issues directly related to regulations and taxes.
P/E ratios of much of the S&P500 would indicate prices/values far over the fundamental value, yet investors continue to flock to large-cap equities in droves.
It's a bubble but it's hard to fight it. US runs a trade deficit vs other nations meaning the trade surplus nations have too many dollars which they send into the financial markets of the US. They most likely buy international companies that have a presence in their own country.
Not the same thing though. The ceiling here is about affordability, not the value of the asset. A house is a need for the individual buyer, not an investment.
The iBuyers[0] are also capable of accidentally cornering a small market to weird consequences. When that happens, prices can temporarily spike and buyers can decide to defer their purchase/move until prices come down more.
This is particularly pernicious because while there is a ton of housing, very few actual units in a city are ever on the market at once, making it easier for a well capitalized buyer to corner. My small city (pop ~1mil) only has 638 units for sale according to Zillow, which is pretty small all considered.
0 - What an unfortunate name we’ve settled on. Reminds me of the era where every cheap infomercial product had to ape Apple naming conventions.
They do have a 'natural' ceiling, but with bold enough policy there is no ceiling in practice. Prices could still rise significantly with the use of negative interest rate mortgages (which exist in Europe), or simply direct financial subsidy to buyers (e.g. the UK's "help to buy" scheme), while maintaining reasonable monthly payments.
I spent a lot of time doing quant models for financial products. Two lessons:
- It's easy to get wrong. If you see a lot of opportunity all the time, it's your model that's wrong, not the market. Very trivial things can mess up your model, like not understanding what the input data means.
- Good trades are hard to get, common rule of thumb that your boss will tell you. Someone selling a house too cheaply? Either there's lots of other buyers or there's something about the house that you didn't think of.
I remember seeing an FX volatility model that almost never traded. It always said "the market is right, plus minus costs". Now and again it would ding and we'd carefully try to get it done in the market, you wouldn't do like Zillow and surprise all the sellers with a massive payday.
I also wrote an arbitrage bot from Bitstamp to MtGox once. I looked at it, didn't turn it on. Percentage wise it was a massive arb, but you couldn't see this in the raw numbers: credit risk on one of the legs. It just shows you that you still need to understand how things actually work. The model is only a calculator for quantifying opportunities that you understand.
This is perhaps the oddest thing about this story. Zillow must have run into several situations where they were paying more than what's sensible, and their staff must have reported this? Surely at the start of an algo buying program, you are vigilant to evidence that the program is wrong?
> Percentage wise it was a massive arb, but you couldn't see this in the raw numbers...
Counterparty risk, that is where the profit came from. I did the same thing, but went into it knowing what the exposure was and how to mitigate it: don't leave crypto in an exchange's hot wallet any longer than it takes to execute a trade and take profit only on exchanges that you could legally pursue in the event that they fail to execute a USD transfer. I also anticipated the debanking that followed... as far as I know I'm still blacklisted by one bank and two money transfer services. What I didn't anticipate was how many exchanges would get hacked and what that would look like to anybody who aggregated the transactions: I get cold called by actual financial institutions a few times a year, always looking to bulk up their dark pools - they somehow have it in their heads that I'm sitting on billions of dollars in BTC. They likely don't have enough of the puzzle to put together the fact that arbitrage doesn't take much when you only need three confirmation blocks - USD wire transfers were the bottleneck.
The issue with that arbitrage is that it was always one-sided. If you're arbing 2 equivalent markets (e.g. name trading on two different US exchanges), you'd expect to buy and sell on both markets in equal amounts, on average.
Bitstamp vs Mt Gox arb required traders to always buy BTC on Mt Gox and sell on Bitstamp (which is a strong indicator of cp risk). This makes inventory management very difficult - especially towards the end of Mt Gox where fund withdrawal times were of the order of months.
My favorite story of algorithmic pricing gone mad was discovered by a postdoc in my grad school lab, leading to an out of print book being listed on Amazon for over $23 million: https://www.michaeleisen.org/blog/?p=358
I worked on software that did algorithmic pricing. It was a race to the bottom because some bozo wanted to be on the first page of sellers. So they’d price it one penny under the lowest price. The next seller would match it. Before you knew it, the product was worth dollars or cents. We also had people do it on purpose (we called it price bombing), but that was easy to negate since we filtered out competitors with low ratings. But there went that bozo, price matching and beating the price by a penny…
It was madness trying to code around people not thinking about their effects on the market and still turn a profit. Spoiler: we never did turn a profit on bozo powered listings, because at some point, it’s better to free the inventory space instead of waiting for the bozo to sell their items and let the price climb back up over the course of months or years.
Why does pricing competitively to appear in the front page earn the label “bozo”? Should they prioritise the effects on the market ahead of their own profits or goals?
It sounds like a really interesting story that’s missing a few steps due to space - it’d make a great blog post in detail!
I think it is probably a great illustration of how merchants actually think. The idealized vision of a market induces a seller to act as you say, in reality there is probably a lot of indirect collusion, where people don't undercut each other too much, to not "damage the market", even without explicitly communicating with each other.
There has to be a floor. This is the point where no one is making any money, ever. You can sell below the floor when you’re just trying to make some inventory space because the things you can replace that space with is more profitable. But “bozos” were people who would irrationally price one penny less, even below the floor. Once a couple of them got in the same listing, the value of the item would drop pretty slowly over the course of days or weeks. Especially if their inventory was in the 10-40 range (yeah, we had a way to guess other people’s inventory) and the velocity of the item was 1-2 per week. With the value of the item dropping by a penny every day, we could work out how long we had. Sometimes we would just outright buy their entire inventory just to get rid of them and get the price under control for high value items. People pricing competitively above the floor was fun to write software for. It was the irrational actors that could seriously damage things for everyone.
They make a killing on that shipping too, you’re paying retail rates for shipping, but you better believe they have contracts with DHL, USPS, etc. that is well below retail cost.
Whenever I see items like that, all I can think is embezzlement or tax evasion - but then again you'd think they would do that on less unique items (like $1200 for playstations).
I don't know how many people remember the Lean Startup movement and Steve Blank's book "Four Steps to the Epiphany" which is about how to take one's product hypotheses and rigorously validate them before scaling up. But somewhere there's a side note that basically said, "If we end up in another bubble, ignore all of this, because in a bubble being careful and capital-efficient isn't a great strategy."
I think about that a lot these days given the absolute oceans of capital sloshing around. I'm glad you got a piece of it! But this is a really weird way to redistribute excess wealth.
I suspect the 'AI software' running these companies is using linear regression to predict housing prices and one of the inputs is the price of similar houses nearby.
I recall in one of the previous crashes it turned out a firm had a model that couldn't handle homes going down in value. A linear model is superior to that.
There was a Kaggle Competition in case you missed it. At least here you can see what kind of features they are using and what models people employed. See https://www.kaggle.com/c/zillow-prize-1
Could be stale information. I talked to them a while back. Still, transacting at the Zestimate price doesn't mean they're privy to the Zestimate algorithms.
Human/realtor appraisals are often very poor. They will take 3-4 nearby & similar homes and basically add/subtract the differences from the home they are comparing. Then they basically just average the adjusted sale prices. They might add a bit onto that price since prices go up over time.
So this has some obvious issues:
* Areas without a ton of very similar houses that have also sold recently will basically have no 'comps' to use.
* It's really easy to keep identifying differences (pros/cons) until the adjusted prices equal each other but it's hard to know if all of the meaningful differences have actually been identified.
* It gives average homes and average buyers a huge advantage. This model assumes that the housing market is hot but not hot enough that someone will pay 10-15% more for some specific feature. Anything unique to a home/property is only going to be worth a fraction of the time & money it would cost to add. Anything super common (kitchen remodel, finished basement, etc.) can actually add 100% or more of it's cost to the houses value because the buyer is paying with 5x or more leverage so paying a bit extra to have it included. This is also why it's often better to fix a few things as the seller than give a discount on the sale price - the buyer will often pay a premium to get things move-in ready since it doesn't impact their monthly costs significantly.
A Broker Price Opinion (BPO) is typically set by appraisal, comparable sales and comparable listings. Depending on how cookie cutter the neighborhood is, there are many different levels of "appraisal" from drive by photos to a deep inspection.
Maybe some reinforcement learning algorithm running as well, where the maximum reward is winning the bid. Hence the algorithm just goes and lays waste on other bidders. Gotta get that infinite reward!
One thing I don’t understand is that many people who buy houses in Phoenix believe in Global Warming getting worse in the short term (source: lived in Phoenix for a year, considered buying a house there, and spoke with many folks who just moved or were about to move).
Hot and dry is not that bad from a global warming standpoint. Evaporative cooling is very effective and efficient so it's actually less energy intensive heating in colder locations. The plentiful amount of space and days of sun makes solar energy very practical. The nights can get pretty cold so it means that certain evening hours are actually very comfortable.
If local real estate agents and developers can manage to manipulate the "Zestimate", and I'm pretty sure they are at least trying, you can imagine the payoff.
I wonder how much of our economy, that alternately humming along and collapsing around us, is simply algorithms talking to eachother? How much economic movement is being generated by arbitrage ( https://www.ecomcrew.com/amazon-arbitrage/ ) ? How much online traffic is generated by advertising bots interacting with each-other? How much are housing prices being juiced by algorithms?
I think the environmental crisis is already effecting the supply chain, I don't think we humans can see it yet. Are we Soviet Russia circa 1931, pretending like everything is going swimmingly while an enormous amount of us are about to starve?
Well, first of all, an unequal food supply chain has generated survival diets close to civilization, spreading new diseases to the entire world (hi Covid!, next door to bird flu).
Second, there are droughts popping up all around the world, our fisheries are collapsing but our supply chain might be absorbing the problems of it until suddenly it doesn't anymore.
That is my deep worry -- that we are seeing the start of a generalized system collapse.
That doesn't sound like an algorithm mistake, just like a policy to match sales nearby at the same price because of the assumption that prices will just keep going up coupled with the stupidity of not tracking what you've bought so far - yikes! Oh, on second thought, I guess it could be algo as that previously bought nearby condo could have been priced using some crazy algorithm.
"Prices will keep going up" was a key belief that triggered the 2008 real estate crash. They keep going up until they don't, and then the house-flippers who weren't careful enough and the lenders that approved "liar loans" get burned badly.
> the lenders that approved "liar loans" get burned badly.
the lenders "knew" of the bad loans, but because these lenders are going to on-sell the loan to some other investor, they didn't care as they profit off the sale, rather than the loan repayments. It's a moral hazard.
The loans were also bundled into opaque securities and the “low-risk” tranches were rated and priced for a typical rate of uncorrelated defaults, not a widespread crash.
Official #1: Btw (by the way) that deal is ridiculous.
Official #2: I know right...model def (definitely) does not capture half the risk.
Official #1: We should not be rating it.
Official #2: We rate every deal. It could be structured by cows and we would rate it.
And the parts that were so junky they couldn't be rated got remixed into another deal to get rated.
It stems from the idea that multiple junk bonds can be combined together to form a higher quality bond than otherwise. This is actually not true, but was the unquestioned underlying assumption.
Its definitely wrong to make this assumption, but the people who got paid are all incentivized to turn a blind eye.
> multiple junk bonds can be combined together to form a higher quality bond than otherwise.
Well it's obviously true. Take your good bond to get paid first from 1000 junk bonds. Then your 999 worse bonds get paid last. Even during the mortgage crisis, not all of the junk bonds returned zero. So there is some number of junk bonds that can be combined into a good bond and worse bonds.
The problem is that people estimated that number to be lower than it actually was. It was a quantitative failure.
They keep going up until they don't, and then the Fed quantitatively eases the losses. Sounds like Zillow's problem was they didn't sink enough money into their scheme.
I've been noticing lots of "new lower price" emails from Zillow; I think the market has cooled off - but how much of it being hot was this investor competition?
price reductions are seasonal in real estate. Peak new listings are around Super Bowl Sunday and Labor Day. There are very few price reductions in that period. The best quality homes at attractive prices sell first. By late October, the total number of listings on the market starts to decline, and price reductions become common.
It's also the last rush of sales before things slow down for the holidays. There's also a chance that interest rates will be higher next year. That would bring home prices down.
A lot of people were jumping in with their rundown old houses asking rediculous (lose your ass) prices and I'm seeing them all revise as of late. This was seen mostly in rural areas--Im looking for a farm.
I saw quite a few houses that sold a few years prior for much lower prices. The disparity in estimated values and previous sales versus the list price was astronomical in most cases. The banks will happily give you a loan for whatever price so there is no check on the runaway prices except for your own personal knowledge of the historical market demand in an area.
I'm not sure I follow your logic; if you're concerned with buying a house now, then prices from years ago are irrelevant. You can speculate that prices have risen too quickly and that they'll revert back to their earlier level, but that's ultimately just speculation. Comparable sale prices from the past few months are the thing to look at, to determine an offer that's likely to be accepted.
One thing to keep in mind about list prices: if the sellers do a good job of estimating the current market price, then the house will sell quickly. If you're checking listings infrequently, there's going to be some sampling bias in the listings you see; overpriced houses that aren't selling will be disproportionately represented in active listings.
They could have charged a review fee to have an appraiser visit & make accurate price estimates & then let the homeowner keep the Zillow certified valuation label if they don't sell it to Zillow.
it was purely about marketing driving up its own value via poorly considered metrics that invariably included positive reenforcement loops. eg, yahoo sells an ad for a company which sells ads on yahoo.
Is Opendoor an MLS/appraiser that also got into the flipping market? It looks like they are just another MLS service but the article states "It will be interesting to see how Opendoor reacts."
I think it’s a bit like when Amazon bots would occasionally drive up the cost of some random book into the millions, except they managed to fool each other into actually buying the damned thing.
In addition to back testing models like this, it’s always worth running forward simulations of what would happen if some/most/all agents in the simulation shared your new strategy.
reminds me of some bots on amazon someone pointed out a while back. Basically the only two sellers of some obscure book are two bots with competing algorithms that keep slowly increasing the price.
The algorithms are fooling themselves... Opendoor matches Zillow who matches Opendoor and that's how you get ever increasing offers.
Edit: oh, and now Zillow has that unit on the market, priced 14% lower than they paid for it, after 3 price cuts so far.
Edit 2: Phoenix/Scottsdale AZ market