[HN Gopher] Zillow lost money because they weren't willing to lo...
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Zillow lost money because they weren't willing to lose money
Author : mjmayank
Score : 367 points
Date : 2021-11-24 18:19 UTC (3 days ago)
(HTM) web link (www.stevenbuccini.com)
(TXT) w3m dump (www.stevenbuccini.com)
| ridaj wrote:
| This is a good take, but
|
| > A machine learning organization thinks of risk entirely
| differently than an automated risk underwriting organization.
|
| It's possible and maybe even advisable to use machine learning in
| the automated risk underwriting business, but it _is_ a different
| setup / set of objectives.
|
| As the author notes, IMO the adversarial and antifraud aspect of
| risk underwriting turns it less into a straight-up estimation
| problem and much more into a game theory type of problem. ML
| models can assist in evaluating risk, but you do indeed have to
| be preocuppied by your risk as a party to the transaction in the
| first place, and not just trying to predict prices as a third
| party observer (which by itself is pretty riskless).
| ezconnect wrote:
| They lost money because they were gaming their own system for
| their own profit.
| jdross wrote:
| I think some reasons Zillow lost were that their pricing and risk
| processes were terribly underdeveloped in order to scale fast,
| their models were obviously inaccurate, and they didn't
| understand the difference between an acquisition cohort and
| resale cohort, and specifically how much the tail sales of an
| acquisition cohort determines profitability.
| gcanyon wrote:
| If the assumption is that you're going to lose half your money up
| front, then my plan would be to make sure "my money" is as little
| as possible: learn based on smaller bets. It sounds like Zillow
| built the Sea Dragon first, when they should have started with
| the Redstone and moved toward the Saturn V.
|
| If Zillow thought they had all the data they needed, there would
| have been little harm starting with $100 million in properties --
| if the loss there ended up being $5 million, they would have
| known immediately something was up and that they had work to do.
| droopyEyelids wrote:
| In the original Foundation books by Asimov, the conceit of
| "Psychohistory" was similar to the concept of machine learning
| for pricing: The future can be predicted _if people aren't aware
| of the prediction to change their behavior in relation to it_
|
| This is similar to 'adverse selection' in real life & in Zillow's
| model. The article makes a nod to this, but seems to imply that
| if you train your model on that adverse selection, you can come
| out ahead after paying to learn about it.
|
| To me that kind of misses the point. Adverse Selection isn't a
| static feature of the landscape you can identify and avoid, it is
| people understanding what you understand, adapting, and
| responding. Train your model with adversaries trying to beat it,
| then you'll maybe counter the specific first round strategies
| they use, and they'll learn new ones and beat your new model with
| their 2nd round strategies. It's a continuous game. Your
| requirement to gather a corpus of training data will keep you in
| the 2nd turn of a game where the wins are biased to whoever has
| the 1st move.
| JKCalhoun wrote:
| I'm reminded always of the Hunt brothers that tried (and
| failed) to corner the silver market in the 70's/80's:
|
| https://en.wikipedia.org/wiki/Silver_Thursday
| skinnymuch wrote:
| I don't get it. Wiki only says they failed because of the
| other institution changing the rules because of them. What's
| the analogy to housing or Zillow?
|
| Sure they failed. But the only data we have is that they
| failed because of something very specific which doesn't
| relate to much else.
| JanisL wrote:
| Basically the COMEX changed the rules explicitly to
| disadvantage the Hunt Brothers. The changes made to margin
| requirements is what made the difference here. I don't think
| anyone could claim that the silver market is an entirely free
| market, I remember last year a press release where the COMEX
| said they weren't sure how much they actually had in their
| vaults in eligible and registered, with a plus/minus 50%
| figure being given on their estimates. I can't think of any
| other major market where someone would come out and say they
| didn't know how much inventory they had and that their best
| estimate could be 50% off. And the participants in the silver
| market are still rather ridiculous to this day:
| https://www.reuters.com/business/finance/jpmorgan-
| pay-60-mln...
| skinnymuch wrote:
| Would some cryptocurrency stuff count? We have no idea how
| much a handful of whales control Bitcoin or Eth. The tether
| thing seems really shaky too with how much they actually
| have in reserves. Same with a number of exchanges or major
| market players.
|
| Cryptocurrency is also a bit wonky because of always
| including forever lost access to a solid percentage of the
| currency. Bitcoin is the most notable.
| Ekaros wrote:
| Bitcoin is best example. Somehow currency we aren't sure
| how much is reachable anymore should come some sort of
| gold standard... Like at any moment significant fraction
| of it could be dumped on market. Probably won't, but it
| is not entirely certain...
| musingsole wrote:
| > It's a continuous game.
|
| This is what most profit seeking strategies can miss. Their
| designers (consciously or not) can't help but to stop thinking
| through their plan at the profit step and just assume "rinse
| and repeat" forever after.
| m3kw9 wrote:
| Buying assets using models, I've seen that in stocks, but people
| usually don't go all in with how hard it is to predict the
| economy
| NoblePublius wrote:
| Buy low, sell high. You need "data science" to do this? $VNQ is
| up 33% since 2016. Do you realize how dumb and bad you have to be
| to lose money on real estate in this time? I imagine randomly
| picking homes off the MLS would have yielded better returns in
| the last five years than whatever Tableau-powered nonsense the
| biz ops analysts at Zillow used. The entire iBuying concept is a
| farce, completely divorced from basic fundamental analysis.
| goatherders wrote:
| This is really well written. Thanks for sharing.
| wiradikusuma wrote:
| Does anyone know where Zillow get its dataset from? I reckon it's
| essentially sale price? Can a "hobbyist" investor do the same?
| [deleted]
| andromeda-brain wrote:
| There's a lot of information that is only available to MLS
| members. Zillow used to not have access to this information,
| but they slowly brokered deals with MLSes around the country to
| get it.
|
| One example: The MLS in Austin, TX recently banned publicly
| sharing a home's sold price. https://www.zillow.com/austin-
| tx-78701/sold/
| MisterBastahrd wrote:
| Yeah, each MLS org has its own data set which is a giant pain
| in the ass for the newspapers who are publishing listings for
| the MLSes in their areas. I don't know if they ever
| standardized it, but I know that one of the first tasks I had
| as a new dev for a newspaper back in the early 00s was to
| build a tool to take the data and normalize it into a single
| CSV.
| JKCalhoun wrote:
| > At a high level, the story of Zillow Offers is a story of our
| industry at its best.
|
| Not in my book. All I see is the price of real estate being
| driven up by corporate greed and the individual home-buyer being
| shut out of the market.
|
| Is it wrong of me to hate "flippers" (be they corporate or
| private)? Pure capitalists will tell me that every property sold
| went to the highest bidder -- in the case of a flipper winning
| they were willing (able) to risk the capital to hopefully turn a
| profit on the flip.
|
| I suspect if you dig deeper you might find sales going to
| flippers because they had 100% cash offers, because they are
| better at "the game". I see no reason to punish prospective
| first-time home owners in this sort of market.
|
| But I don't know what the answer is either.
| chii wrote:
| flippers make the real estate market more liquid, in the same
| way high-frequency trading does for stocks.
|
| Flippers take the risk of the market falling while they're
| flipping - that's the price they pay for their profits.
| [deleted]
| JKCalhoun wrote:
| You'll have to educate me then: is _more liquid_ better for
| the buyers or sellers?
| loeg wrote:
| Liquidity is good for both buyers and sellers.
| perpetualpatzer wrote:
| Arguably, it's good for both. Buyers have more quality
| inventory to choose from and can purchase a home with lower
| risk of getting trapped in it permanently. Sellers get
| faster sales with a higher floor on prices.
| loeg wrote:
| What's even arguable about it? Liquidity is good for
| market participants, period.
| igammarays wrote:
| Liquidity is NOT good in a dire-necessity supply-
| constrained market like housing, because it invites
| capital which could've been spent elsewhere to lock up
| unnecessary housing units (houses are empty while being
| flipped), further constraining supply of a critical
| resource.
|
| Imagine if drinking water was treated as a speculative
| asset, with large percentages of a countries water supply
| being stored in tanks and sold back-and-forth on paper
| between capital-rich investors instead of actually being
| pumped to where it was needed through pipes.
| javert wrote:
| Both. In an illiquid market, it takes a long time to find
| buyers or sellers. You are incentivized to overprice (if
| selling) or underprice (if buying) and wait a long time to
| see if someone will match you. A liquid housing market
| means people can buy or sell the house at the "right" price
| without waiting many months or years.
|
| As a seller, would you rather wait a year to make a bit
| more money? That wouldn't be good. That would be crappy.
| rswail wrote:
| Sure, but the more important point is that the market
| represents housing. Having housing empty is pointless, so
| market speculation is that is not about the rent from the
| asset but only its capital growth leads to that exact
| outcome, empty housing has lower expenses and
| depreciation in reality, which helps maintain the asset's
| value better than if someone was living in it.
| encoderer wrote:
| Here's a thought experiment: if I told you the market was
| going to be less liquid and you may not be able to easily
| sell the house you're about to buy, wouldn't that change
| your behavior?
|
| I think you've bought into the tik tok narrative that
| somehow it's zillows fault that houses are expensive.
| eropple wrote:
| _> if I told you the market was going to be less liquid
| and you may not be able to easily sell the house you're
| about to buy, wouldn't that change your behavior?_
|
| No. Like a normal person, I bought my house to live in
| and to improve and to stay in for a long period of time.
| It isn't a speculative investment vehicle.
| encoderer wrote:
| It seems like you're presenting a straw man. Being able
| to sell your house and not be tied to one home for life
| is a reasonable desire that has nothing to do with
| speculative investment.
| eropple wrote:
| No, it's that if I need to sell it I've structured my
| finances and my life to be able to take time to do it--
| because I've intentionally made decisions with the
| remodeling in my home to be suboptimal for selling
| _anyway_. I 'd have to put up a wall and reroute a bunch
| of plumbing for my laundry room off my master bedroom so
| I could turn it back into a bedroom because that's what
| the dollar-signs-for-eyes crew values, so why would I be
| worried about selling it in 48 hours?
|
| This is an industry I actually know a teensy bit about.
| Normal people don't need to sell a house in two weeks.
| That is an abnormal condition brought on by stupid,
| disinterested money flooding the market and the idea that
| everyone must be hyper-mobile all the time is one brought
| on by the more deranged, "humans exclusively acting as
| work producing automatons" part of a market economy.
| Solidity and permanence are valuable. I'd go so far as to
| say that when you take into account the benefits of long-
| term residence and ownership--and they are benefits you
| will not see in your ML model, such as a cohesive
| neighborhood where you actually know and _maybe even
| interact with_ the people who live around you--that it
| might even be a positive to discourage market thrash. You
| know. For humans, and not investors.
| encoderer wrote:
| It's clear your approach to housing is consistent with
| your life choices. I think maybe you are just thinking
| your approach is "normal" and the right way to do things.
|
| A lot of people buy starter homes, or homes in areas they
| do not plan to stay 10+ years, or homes they outgrow.
| That's all normal too.
| evan_ wrote:
| > if I told you the market was going to be less liquid
| and you may not be able to easily sell the house you're
| about to buy, wouldn't that change your behavior?
|
| It would not change my physiological need for shelter, no
|
| "Oh I might not be able to sell this for a profit in two
| years, guess I'll die in the street"
| rswail wrote:
| I'm buying housing for myself. It would be a potential
| relevant thing to take into account between choices, but
| I still need a house.
|
| I'm buying a long term asset, so the liquidity of the
| housing market is not relevant to me, unless I'm actually
| buying for a specific short term, like a planned work
| period.
|
| Liquidity of the housing market is only important to the
| agents and the loan originators because they make money
| on the flow.
| igammarays wrote:
| Flippers also reduce the supply of housing units for the time
| they are unoccupied, which could be months or years,
| especially when sold to other flippers. More liquidity is not
| necessarily a good thing for the housing market, as it tends
| to increase the number of speculators on the market,
| contributing to a vicious cycle where more homes are being
| flipped between speculators than actually occupied by people
| who need them.
|
| It pains me to watch people apply simplistic theoretical laws
| of supply and demand to something as complicated as housing.
| The map is not the territory. There are massive costs to
| increasing supply, as well as psychological/community costs
| to moving homes, which are not cleanly captured in any
| Economics 101 textbook.
| mberning wrote:
| People would probably suggest regulation or taxes to "fix" the
| problem but I think the root of the issue is artificially low
| interest rates, freewheeling lenders (again), and the fact that
| there are few other places to deploy your money and get some
| yield. There is also the tax benefits of owning income
| properties which should probably be looked at.
| pontifier wrote:
| The answer is to reduce regulation.
|
| The process of building new structures is filled with so much
| regulatory friction that it is impossible for the average
| person to even consider building their own home.
| skohan wrote:
| Which regulations would you relax? Surely there is some
| unnecessary red tape, but it's not as if building regulations
| have been developed for fun, it's largely in response to
| safety issues and so on.
| loeg wrote:
| Quite a lot of regulations have nothing to do with safety.
| Minimum set-backs, minimum parking requirements, maximum
| building heights, etc. All of these add cost and reduce
| density.
|
| Single-family zoning is another local government policy
| that is absolutely intended to constrain development, not
| improve safety.
| skohan wrote:
| Well as someone who lives in a fairly regulated housing
| market (Berlin) I'm happy about all the regulations
| you've mentioned as they prevent negative externalities
| which would benefit real-estate developers at the cost of
| everyone else. Imo targeting a specific population
| density is within the mandate of local government, as
| too-high density causes all sorts of issues from traffic
| to health and everything in between. If you want to
| unchain developers on density, I invite you to take a
| 10km drive in Delhi or Bangkok and tell me if the cost
| generated on a daily basis in terms of time and stress is
| worth it.
|
| I am in favor of finding ways to encourage more housing,
| but what you're calling for is essentially to invite
| favela housing in the developed world.
| loeg wrote:
| You originally claimed that these regulations were for
| safety:
|
| > it's not as if building regulations have been developed
| for fun, it's largely in response to safety issues and so
| on.
|
| But they're not. As you (now) say, they're for reducing
| development. The original statement about safety was
| substantially incorrect.
| skohan wrote:
| Surely you can grasp that "and so on" implies other
| reasons than the one explicitly stated. Negative
| externalities are another example of a valid target of
| regulation.
| hogFeast wrote:
| Seriously? Berlin's tower blocks are the favelas of the
| developed world.
|
| Also, the reason why Berlin hasn't had the same pressure
| is because it is one of the few cities in the developed
| world that has actually shrunk over a multi-decade
| period. It is very easy to limit population density when
| there is no pressure on housing. And, ofc, the historical
| division of the city meant that it had to develop more
| than one centre. These factors aside, afaik, the
| development of Berlin hasn't been exceptional...they
| built suburbs when there was pressure on housing in the
| early 20th century, built public transport, those suburbs
| eventually integrated into the city...very few cities
| have grown through greater intensity in the centre
| because cost is prohibitive, regardless of regulations.
|
| Nothing to do with regulations, everything to do with
| historical circumstance (also, the guy you replying to is
| quite correct...if you actually look at housing
| regulations in the US, they have been a tool for
| racial/economic segregation...being real, that is why the
| limit on multi-family housing exists, the US has very low
| population density, saying they will become Delhi if they
| reduce regulations is hysterical).
| skohan wrote:
| You've proven my point exactly. Many of the the
| Plattenbauten (GDR-era block housing) could not be built
| in Berlin today _because_ of current regulations. Berlin
| is targeting a moderate population density with mixed-use
| neighbourhood, which is the recommendation of subject-
| matter experts and makes it in general a very nice place
| to live. There 's a _huge_ desire by developers to
| increase density within Berlin and I have no doubt it
| would increase massively if there was no check against
| this.
|
| Nobody is arguing that the entire US would become like
| Delhi, but can you seriously hold the opinion that
| housing deregulation would not result in mass production
| of low-quality housing near major population centers?
|
| There are problems with extremes on both ends. For
| instance the NIMBY-driven housing policy in SF is not
| what is needed to create sustainable housing. But is a
| somewhat unique case, and it doesn't mean an extreme
| swing in the other direction towards deregulation would
| lead to a good outcome. Sensible housing regulation is
| undoubtedly a requirement for sustainable urbanization.
| rswail wrote:
| It's not about safety, it's also about amenity and
| suitability and sustainability. In some areas, density is
| important given the population, in others its not.
|
| Parking requirements are about local traffic management
| as well. Set backs are about ensuring natural light. Some
| local regulation is about NIMBYism or HOAism, that sort
| of thing is where reform might be better addressed.
| loeg wrote:
| Lack of set-back rules do not prevent building houses
| with set-back. Lack of parking law does not prevent
| building parking. Developers will not build density if it
| isn't a profitable use of the land -- i.e., important
| given the population. Rezoning to permit density does not
| immediately replace all existing structures.
|
| Mandating these things _is_ some of that "local
| regulation tied into NIMBYism" you mention.
| skohan wrote:
| Profitability isn't the only important metric here. It
| might be profitable for developers to increase density
| well beyond the point where it causes measurable negative
| externalities towards everyone occupying an over-crowded
| place.
| throwawayboise wrote:
| Cosmetic stuff, square footage requirements, height
| requirements, parking requirements. Basic structural
| engineering, fire safety, etc. requirements of course would
| stay but if local code is more stringent than national you
| might take a look at it (e.g. things like a local code
| requiring copper pipes when PVC is acceptable and much
| cheaper).
| sokoloff wrote:
| (Straight) PVC is not acceptable for hot water supply
| lines.
| loeg wrote:
| GP obviously meant PEX, which is another plastic. (For
| people not familiar with modern plumbing: PEX is used for
| supply; PVC is used for drainage to the sewer.)
| djbusby wrote:
| What are those red and blue plastic lines made of?
| sokoloff wrote:
| PEX (cross-linked polyethylene).
|
| Those are suitable for hot and cold supply.
| rswail wrote:
| Unless there's a need to build to a higher standard with
| longer maintenance periods, so that housing stock can
| have a longer life. Houses exist for decades, better to
| build for that without needing maintenance but perhaps
| costing more initially.
|
| Developers will _always_ attempt to skimp on quality to
| save /make more money. Even people building their own
| home will sometimes try to avoid compliance. That's why
| the regulations are there.
| rvba wrote:
| The Florida buildig collapse showed whqt happrns when
| regulation is "reduced".
| rswail wrote:
| Because there's a societal need to ensure that the housing
| stock is safe and effective. We invest (or should) a lot of
| our taxes into local amenities to ensure that housing is
| provided the best environment. Transport, schooling, roads,
| etc.
|
| That housing should also be up to a similar standard in terms
| of its externalities like pollution and energy efficiency
| etc.
|
| We have regulations for air travel, for car emissions and
| efficiency, why should housing be any different?
| rufus_foreman wrote:
| We have regulations for air travel, and that raises the
| price for air travel, which means some people can't afford
| air travel.
|
| We have regulations for car emissions, and that raises the
| price for cars, which means some people can't afford cars.
|
| We have regulations for housing, and that raises the price
| for housing, which means some people can't afford housing.
|
| How many people should not be able to afford housing? Is
| the number of people who currently can't afford housing too
| low, or too high? Should we increase regulations for
| housing, or decrease them? Are we making the right trade-
| offs?
| abernard1 wrote:
| > Because there's a societal need to ensure that the
| housing stock is safe and effective.
|
| And this is accomplished via building codes, which are
| rigorous and applied almost uniformly in the U.S.
|
| > We invest (or should) a lot of our taxes into local
| amenities to ensure that housing is provided the best
| environment. Transport, schooling, roads, etc.
|
| And this is the model that has made blue cities
| unaffordable for the poor. They're not environmentally
| friendly either, their schools are awful, amenities poor,
| and transportation lacking. It would be hard to find one
| single issue where there is even parity of centrally
| planned quality-of-life concerns in blue cities vs red
| cities.
|
| The question is not "regulations" persay. There is no
| magical regulation slider bar that can be adjusted to
| optimal result. It's what those regulations seek to
| accomplish. In many U.S. urban metros, those regulations
| are targeted to what city policy thinks the owners _should_
| do with their property, and not what they want to do with
| it. It 's not clear those regulations have had their
| intended effect.
| throwhauser wrote:
| The answer is to build houses and print money to buy them with.
|
| If houses were a (much) smaller bet for the buyer, there would
| be more flexibility to build houses where demand exists and a
| faster, lower-drama exit for people who don't like the changing
| nature of their in-demand neighborhood.
|
| The inertia created when people have their life savings tied up
| in their house perpetuates the problem of affordability, by
| making the areas that have the most mismatched supply vs demand
| the least likely to deal with the problem.
| nova22033 wrote:
| _All I see is the price of real estate being driven up_
|
| Who is doing the selling? "Wall St Fat cat Co" or the average
| Joe who saw his house value go up by a LOT?
| evan_ wrote:
| When Conglomocorp sells one of their houses, they just get
| the cash and can realize profits.
|
| When average homeowner Joe sells their house they still have
| to live somewhere. They must immediately use that money for
| another house, which is also inflated. The higher sale price
| doesn't matter.
|
| Average non-homeowner Joe trying to buy a first house is SOL.
| javert wrote:
| Yes, you are wrong to hate flippers. You are wrong to hate
| anyone who is working hard to make an honest living. Yes,
| flipping is hard work.
|
| All successful work probably displaces someone else in some
| way. If you're good at your job, you're "denying" that job to
| someone less skilled. If you work in software, you're
| automating things that would require more labor if done
| manually. Fortunately, humans can pivot.
|
| Either hate everyone, or hate no-one. You can't _just_ hate
| flippers.
| loeg wrote:
| I think there are ways to make money that are socially
| negative value -- e.g., theft is a pretty obvious one, or
| bitcoin mining.
|
| House flipping isn't a social negative. They're doing a
| productive activity and producing value. They aren't long-
| term speculators removing housing stock from the market. It's
| essentially home renovation, done by a 3rd party owner.
| javert wrote:
| Bitcoin people _believe_ it is a moral good (myself
| included), and have extremely strong arguments in favor of
| that view, which are rooted in morality and economics.
| Thus, when you make a snide anti-bitcoin remark without
| actual content, you come across as trying to invalidate
| bitcoin through mere peer pressure, which we all know is
| juvenile.
|
| It's like Trump voters who criticize "libtards." We all
| know it's not a valid way to discuss something.
|
| In fact, the expansion of the fiat money supply enriches
| the wealthy through the Cantillon effect. Then, because the
| value of money is going down, they pile into assets like
| housing. For instance, the US is becoming a nation of
| renters due to this effect. The stock market is similarly
| distorted. We _need_ bitcoin because we need an objective
| form of money. That would allow stocks and houses to stop
| being stores of wealth and reflect their true economic
| value, which would be a huge boon to everybody.
|
| I'm guessing the energy thing is what you think your anti-
| bitcoin argument would be. Bitcoin mining is also such an
| efficient market that in the long run, only the most
| efficient forms of energy--such as nuclear and geothermal--
| will be viable for it. Bitcoin is already helping to
| advance "green" energy. This is abundantly clear to people
| involved in the mining industry.
| beervirus wrote:
| It doesn't even matter if it's hard work. Flippers take
| advantage of a market inefficiency, and just like everyone
| who does that, they make the market less inefficient. That's
| a good thing even when it's easy.
| Peanuts99 wrote:
| That's a pretty binary take on an activity that exists on a
| ethical gradient.
| javert wrote:
| Ethics is what we decide it is. How about not condemning
| practically everybody as some kind of sinner, the way you
| are? That's a counterproductive view that reeks of
| Christianity.
| javert wrote:
| Sorry, my sibling comment came across as a little too harsh
| and accusatory (too late to edit now).
| MisterBastahrd wrote:
| SMEs are smarter than developers in their space.
|
| Always has been that way. Always will be that way. AI is great
| for when you need to tame a firehose and make millisecond
| decisions. But there's a 90 year old in Omaha who is better than
| the best AI.
| tinyhouse wrote:
| If you have a good business with high margins, why not grow that
| business instead of starting a new low margins business of
| flipping houses?
| jdross wrote:
| Because they were having a lot of trouble growing that
| business. See their earnings reports before they entered
| iBuying
| nickkell wrote:
| I love this guy's movies. Finding out he writes so articulately
| to boot? Wow
| jollybean wrote:
| All of this reads like a Dickensian nightmare, where corporations
| have bought up all the water and air.
|
| This is ridiculous, we need much better regulation on this stuff.
|
| I wonder if higher property taxes would help a bit? If you own a
| 'home' then you're going to be paying for the water, school,
| electricity infrastructure whether you use electricity, water, or
| not.
|
| Of course, that would be gamed hard and would have to be strongly
| regulated as well.
|
| But that, and vacant property taxes, limits on some other things,
| and some other adjustments might help.
| mgraczyk wrote:
| I really liked this quote, which is also true of machine learning
| organizations at large tech companies: The most
| valuable data is not social data, ... but your own data because
| every dataset that you're looking at internally describes your
| own process, including your bugs, ... building models from your
| own data is the only way to build a really successful system.
|
| This is one thing that a lot of outsiders do not understand.
| Facebook/Google's data is basically worthless to anybody but
| Facebook/Google. The data has value because it is derived from
| their own processes, which in this case are the requests and
| context of each product surface.
| [deleted]
| ethbr0 wrote:
| It makes sense when you ask the question another way: "What is
| the likelihood that a preexisting assemblage of data contains
| all the nuances for my specific process?"
|
| Some domains are intricately mapped in available data (e.g.
| equity pricing), but most, and especially most _physical_ , are
| not (e.g. freight transportation).
| robbedpeter wrote:
| Yeah, I'm gonna say that romanticizing mass surveillance is a
| bit much. Cambridge Analytica, the five eyes countries,
| Clearview - all these are using Facebook and Google's data to
| great effect.
|
| Facebook and Google's data are not their own. That data is
| comprised of private lives, stripped bare pixel by pixel, bit
| by bit, and it's offensive to frame it as if they're doing
| something alchemical and special with it. Google's search
| dominance came from something special, creating the right
| algorithm and seizing the first mover advantage, but the
| relentless and ruthless invasion of privacy is a rent seeking
| race to the bottom.
|
| All of the ills of the internet and political turmoil in the
| west from algorithmic amplification are the brainchilren of
| Facebook and Google. It turns out that "tailoring search
| results" and "targeted advertisement" are excuses for something
| that can cost far more than a society might want to pay.
| mattcwilson wrote:
| You're totally missing the GP's point.
|
| You're also absolutely right that the social media content:
| the photos, the sentiments, the likes, the connections,
| should not in any way "belong" to FB/G.
|
| The data that does belong to them, and that is useless to
| anyone else, are the outputs from their sentiment analyzer
| service, the weights and trigger conditions for their content
| ranking algorithms, the intermediate outputs of their ML
| evaluations, etc.
|
| GP, and the article, are saying: look there first. Try to
| start by truly understanding "what you already know, but
| aren't paying enough attention to," and don't just treat the
| problem as "needs more data."
| mgraczyk wrote:
| I'm not going to engage in a flame war over this, but suffice
| it to say that this is pretty much exactly the
| misunderstanding I was referring to with that quote.
|
| Most data Facebook collects is of the form (user saw this
| post, user clicked/did not click this post). That data's
| value is tightly coupled to the process Facebook used to
| decide whether or not to cause the user to see that post. The
| data only has value in the context of iterating on that
| process.
| lifeisstillgood wrote:
| >>> you should expect to lose 50% of your capital allocated
| towards underwriting.
|
| How ?
| vasilipupkin wrote:
| "You cannot bootstrap off an existing dataset. Full stop. These
| datasets can contain implicit assumptions or associations that
| you are not aware of. This is the original sin of many a
| algorithmic risk underwriting startup"
|
| False. You can definitely bootstrap and adjust the model as you
| either gather more data yourself or get more outside data. You
| can also build confidence intervals around the model predictions
| and decide how you want to proceed based on that. There is lots
| you can do with that initial model.
| rossdavidh wrote:
| While no doubt Zillow made many of these mistakes, I think the
| reality is more sobering that the author of the article realizes.
| The more grim possibility, is that Zillow got out of the house
| buying business, not because they weren't good enough at it, but
| because they _were_ good enough at it to realize that it was at
| the top.
|
| If buyers want more now for their house, than it can be sold for
| in a few months time (which is necessary for renovations and
| other prep for sale), then there is no ML (and no non-ML) method
| to make money. Either you overpay and lose money, or you don't
| overpay and you don't buy any houses.
|
| In that situation, the only smart play, is to get out of the
| market. Zillow is, no doubt, not perfect. But they have a lot of
| knowledge of the housing market, and they thought it was time to
| get out entirely. I think the author of the article either isn't
| able, or doesn't want, to consider that Zillow might have been
| exactly correct in doing so.
| dsizzle wrote:
| But they lost money last quarter while the market was still
| rising. Seems there was some problem with their prediction
| process.
| rossdavidh wrote:
| Rumor is that they had to put their thumb on the scales (i.e.
| tweak the model) to get enough sellers to sell to them. In
| other words, if paying what their model actually thought was
| the right price, not many people sold to them. Instead of
| saying "our division's whole business model won't work, you
| should fire us", they tried to cut the margin too close,
| resulting in losses which got the CEO's attention to the
| problem.
|
| This kind of thing is difficult to confirm from the outside,
| of course. But that they adjusted the model to pay more
| towards the end is pretty widely known.
| dsizzle wrote:
| Do you have a reference for this? Is part of the rumor that
| not everyone in the organization knew this was happening?
| rossdavidh wrote:
| No, the rumor was just that they put their thumb on the
| scale.
|
| https://ryxcommar.com/2021/11/06/zillow-prophet-time-
| series-...
|
| "Speaking of middle managers, word on the street is that
| Zillow Offers put their thumb on the scale of the
| algorithm to make it engage in more aggressive trades.
| Manually adjusting an algorithm isn't necessarily a bad
| thing, but you need to do it for the right reasons. And
| clearly that didn't end up working out..."
|
| That not everyone in the organization knew that, is just
| me speculating.
| sudosysgen wrote:
| Their plan wasn't to flip homes in a month or two as far as
| I'm aware so that's expected if they get out.
| [deleted]
| axg11 wrote:
| While this sounds plausible, I think there are a couple of
| factors that work against this theory:
|
| 1) Why layoff your data science division if they are predicting
| with accuracy?
|
| 2a) If you have enough conviction to call the top of the
| market, why sell off so much housing at a huge loss? Zillow are
| the only participant in the residential real estate market
| losing money right now.
|
| 2b) If you see signals of a forthcoming housing crash, why not
| short the housing market?
|
| The simplest explanation is that Zillow was poorly run.
| rossdavidh wrote:
| It may have been poorly run, and nonetheless correct that:
|
| - they could not buy houses without overpaying (relative to
| what they could sell them for a few months down the line)
|
| - the housing market would not recover for several years (so
| no need to keep that extra 25% of your labor force,
| especially if you anticipate a decline in revenue from real
| estate agents coming soon)
| initplus wrote:
| Zillow wasn't aiming to build a business making bets on the
| housing market. They wanted to become a market maker for
| housing, profiting off the spread and not caring about the
| underlying price movements. Being a (good) market maker is
| still profitable in a falling market.
|
| The issue is that the housing market is just unsuitable for
| this strategy. Houses aren't fungible, and they are very slow
| to trade. So Zillow ended up in a position where rather than
| clipping the ticket on spread, they were actually quite exposed
| to house price movements.
| rossdavidh wrote:
| You are absolutely correct. But, in a different situation
| where sellers were willing to sell at a price that was likely
| to still look like a good idea in a few months, they would
| not have realized that this wasn't a good idea (yet). It was,
| I think, inevitable that they would get out of this, because
| (as you point out) the housing market is not suitable for a
| market-maker business. But I don't think it was inevitable
| that they got out at the top; they could have held on and
| given in to the inevitable six months or a year after the
| slide had begun. I think it's to the CEO's credit that they
| got out sooner than that.
| asdff wrote:
| It's land, there is no top. It's a finite resource. Buy any
| property in the U.S. and hold for 15 years and I would be
| shocked if you didn't make out even if you had 2008 in between.
| rossdavidh wrote:
| Perhaps, although I suppose there were Japanese property
| buyers who thought so also. But a CEO can't run at a loss for
| 15, 10, or probably even 5 years before getting booted,
| either by the board or a hostile takeover.
| JackFr wrote:
| While the point the article makes is true -- it costs money to
| acquire the real world data, the comparison to credit
| underwriting is misguided. Underwriting credit is fundamentally
| different than predicting house prices.
|
| In particular when you're auto-underwriting credit it's not
| typically an origination-for-sale model. So the value of the loan
| is the present value of the future payments, less the future
| value of defaults, less the cost of acquiring the customer.
|
| Historically those things can be modeled pretty accurately and
| the aspects that can't be modeled accurately can often be hedged
| or eliminated by the law of large numbers. The innovation of the
| new ML underwriting with respect to accuracy is at the margins.
| The real disruption is the speed and cost. (Disclosure: I worked
| at a SMB fin tech and we reran multiple credit models for a
| million customers and past customers every night.)
|
| If Zillow were getting into the rental business, in some ways it
| might have been easier for them. But they needed to model where
| they could sell an illiquid asset which is a much harder and much
| less well understood problem. And yes with enough capital to plow
| through and the appropriate risk attitude they could likely have
| gotten the handle on what their pipeline was really going to look
| like. But it's hardly the same problem as credit underwriting.
| abernard1 wrote:
| > Because when you have a hammer, everything tends to look like a
| nail and when you have TensorFlow, everything tends to look like
| an ML problem.
|
| And if you have billions of dollars in cheap capital, everything
| looks like an investment problem.
|
| Which is ultimately the suggestion of this article: "Why aren't
| you more like Wall Street?"
|
| The implications are exactly the opposite of Zillow being an
| innovative company. If they require billions of dollars in deep
| pockets (nbd) and a restructuring of their org to be more like
| old-school operators, all signs point to existing players as more
| fundamentally correct about the strategy required to succeed in
| the space.
| [deleted]
| 1cvmask wrote:
| The essence of the article is that they underestimated how flawed
| their algorithms are and how hard it is to build a good lasting
| algorithm in a dynamic world.
|
| Many seasoned wall street algorithms have suffered many times
| over 5 decades, and when they fail we call them black swan
| events.
| throwawayboise wrote:
| And wall street algorithms _should_ be easier because
| securities are fungible. One share of AAPL is the same as
| another. Houses are not like that. Real estate is local, local,
| local. Every house has a hundred unique attributes that each
| potential buyer will value differently.
| mjdesa wrote:
| That's not what I read in that article at all. What I read was
| that their data and methodology was flawed, and they weren't
| willing to pay the price to fix it.
| seoaeu wrote:
| Zillow thought they already had enough data and accurate
| enough models to buy and sell houses profitably. The last two
| quarters proved they didn't. In the first quarter they were
| puzzled by making too much money and in the second they lost
| a whole bunch
|
| The author is arguing that they should have pivoted from "we
| already have models" to "we're intentionally gambling
| hundreds of millions of dollars so we can build good models
| over the next few years". That might be a good strategy for a
| startup with loads of VC money and no other products, but it
| makes less sense for a more established company to risk going
| under on that bet
| human wrote:
| Their methodology _might_ have been flawed. The author is
| speculating.
|
| He uses Zillow to explain how datasets - especially the ones
| with money tied-in - can't be trusted blindly. Building a
| high-quality dataset is an expensive endeavour.
| xibalba wrote:
| The article offers no new or inside information, just more
| armchair quarterbacking. I'm surprised that it is getting
| traction on HN. I think it says more about the zeitgeist than it
| does about the (lack of) insightful-ness of the content.
| gwern wrote:
| Yeah, it just repeats the Narrative in a giant post hoc.
| "Zillow uses ML models in some way; Zillow failed; QED, ML
| models are dangerous." Except the reporting by Bloomberg and
| insiders is that Zillow failed because they overrode the models
| predicting lower prices and bought like drunken sailors, and
| it's just a story of yet another marketmaker being run over by
| the market. So sad, too bad, largely irrelevant to the tech
| world, yet, it looks like it's entering the mythology of ML up
| there with Cambridge Analytica or the tank story - unkillable
| by mere facts or tardy reporting.
| adjkant wrote:
| As someone who upvoted but didn't care much for the content, I
| think it's worth mentioning that sometimes/often I upvote for
| the currently occurring conversation to get more eyes, not for
| the link. I haven't seen too many specifics on the Zillow
| collapse and I've learned a nice deal through many of the
| comments here, most not having much at all to do with the
| article.
| flerchin wrote:
| > One of the things that happens for a brand-new launched credit
| card: done right, you lose about 50% of the dollar volume in the
| first several months
|
| What does this mean? 50% of the money is held as debt? Or 50% of
| the money is lost to fraud?
| Petabits wrote:
| Getting people to initially sign up through bonuses causes a
| lot of money to be shed, and are thus not profitable until
| people renew (without the bonus) the second year. I remember
| seeing the CEO of Chase saying he was excited that they lost
| billions in the new sapphire card because it meant they had so
| many members
| zatkin wrote:
| What does 'bootstrap' mean in the context of this article?
| ec109685 wrote:
| In order to actually understand true risk (to create a
| profitable model), you'll actually have to experiment and lose
| money in order to bootstrap your own ML model. Taking data
| acquired elsewhere and hoping it can make your own model
| instantly profitable isn't possible.
| dr_dshiv wrote:
| Is it fair to call this the result of "AI thinking?" Meaning that
| urge to automate away human involvement, because --after all---if
| people are involved in analyzing data and decision making, then
| clearly the AI isn't finished let.
| PaulHoule wrote:
| I can't agree with the article or many of the comments on it.
|
| (A) Both Wall Street and Machine Learning Modelers struggle with
| tail risk. Hedge funds measure performance against
|
| https://en.wikipedia.org/wiki/Sharpe_ratio
|
| which assumes risk is (i) normally distributed and (ii) a source
| of reward. For most people, however, risk looks like Theranos or
| the Fukushima accident or the Challenger distaster.
|
| It's unbelievable that a machine learning model trained to
| predict house prices based on experience would be accurate in the
| face of events like the COVID-19 pandemic or what will happen
| when the Fed raises interest rates. You can model risks like
| that, but to the extent that you're working from experience you
| are working from a database from the 1929 Crash, South Sea
| Bubble, etc.
|
| (B) Mark Levine wrote a good article about how you'd exploit such
| a predictive model. If you consistently gave people low offers, a
| few people would accept them. You would get a high rate of return
| but could invest little capital.
|
| To invest more capital you have to make more offers that get
| accepted, that is, give better prices. Your rate of return goes
| down and if there is shrinkage from errors, accidents, etc. you
| could get a negative return.
|
| It's that "tendency towards a declining rate of profit" that Marx
| warned about.
|
| (C) The analogy with stock market market makers doesn't sound
| good when you consider the differing timescales.
|
| Market makers are isolated from some risk because of the length
| of their holdings. Yet, they make profits by exploiting the
| stochastics of a stationary market (e.g. if you don't like the
| price at time t1, you will usually get a better price at t2) but
| they lose money when markets move definitively in one direction
| or another.
|
| That kind of trader heads for the bathroom when things go South
| and in the interest of being orderly markets impose sanctions on
| market makers who do the natural thing and press the "STOP &
| UNWIND ALL POSITIONS" button when it gets tough.
|
| In the case of Zillow I see holding times that go on for weeks or
| months and all kinds of real world risk like planning to do
| certain renovations but having to delay the work because out of
| 20 things you need from Home Depot they only have 16 of them.
| [deleted]
| wly_cdgr wrote:
| There's something really funny about white collar office worker
| businessmen talking about how it takes balls of steel to do what
| they do. Ok bro, sure. Trackballs of steel maybe
| Animats wrote:
| Well, maybe they just exited because we're going into a recession
| and it's a good time to get out of house-flipping.
| dcposch wrote:
| Framing it as machine learning undersells the problem.
|
| It's a hybrid model trading in an adversarial, real-dollar
| environment. The leverage comes from having a small human team
| trade big volume, much more than they could possibly trade
| directly, by augmenting their human abilities with automation and
| a model. Or seen from the other side, it's a model with human
| oversight.
|
| Any system like that is high risk, high reward. All the
| successful ones started out by losing a lot of money. Paypal lost
| an incredible amount to fraud before they started breaking even.
| OpenDoor lost an incredible amount to mispricing, and took on a
| ton of balance sheet risk, before their business really started
| working.
|
| "To live, you must be willing to die"
|
| - poker legend Amir Vahedi
| dboreham wrote:
| They build an AI that perfectly emulated Wall St masters of the
| universe.
| danielvaughn wrote:
| I think the article makes an interesting point about this being
| the first of many, but I disagree with the initial tone of the
| article. It seemed to paint Zillow as being afraid of loss. On
| the contrary, I viewed Zillow as demonstrating good common sense
| and an ability to make hard decisions. To me it shows that they
| aren't committing the sunken cost fallacy, and are willing to cut
| an entire 25% of the company and take massive losses so they can
| redirect themselves towards better objectives.
| quickthrowman wrote:
| I agree, I think they realized it wouldn't work and made a hard
| decision to save the company.
|
| Zillow realized the only time their ask was hit is when it was
| at a premium to the actual market price. If they used
| competitive offers, they'd never have the winning bid. In a hot
| market where you're offering a premium, you're going to have
| owners of lower quality properties accepting your offer, while
| owners of higher quality properties have more offers to select
| from.
|
| Zillow got left holding a bag of lemons and decided to get out
| before buying the whole lemon grove.
| marcinzm wrote:
| >If they used competitive offers, they'd never have the
| winning bid.
|
| Why do you assume that, seems like a cash buyout would be a
| great deal for many sellers if it was at the appropriate
| price. Issue is I think that Zillow's information was less
| granular than what the buyers/sellers had. Let's say Zillow
| priced two houses near each other at 1million each. However
| one was close to a busy road so would only sell for $900k
| while the other could sell for $1.1. Zillow made the right
| average offer of $1million to both but the buyers/sellers
| actually had more information. So the 1.1m seller didn't take
| Zillow's offer while the 900k seller did. Now Zillow was out
| $100k essentially not counting fees.
| rpvnwnkl wrote:
| They are out 200k. They bought for 100 too much and will
| have to sell for a 100 less than planned.
| sokoloff wrote:
| No, they bought for $1000K and sold for $900K. You can't
| count the spread twice.
| cwilkes wrote:
| The spread kind of can be counted twice: if you tell
| management "we're going to make $100k (10% return) in
| profit this year" and you end up paying $1000k and
| selling for $900k instead of $1100k like you planned ...
| management is going to be less than pleased.
|
| They fronted you $1M with the expectation they would make
| $100k. Now they are losing $100k. So their own
| projections are screwed by $200k.
| marcinzm wrote:
| Not sure I follow. They buy for 1m so they're out 1m.
| Market value is irrelevant when bought. They sell for
| 900k, optimally, so they then get back 900k. In total
| they're out 100k (900k minus 1m). Not counting fees,
| market movement and assuming they sell optimally.
| encoderer wrote:
| I'm not saying you're wrong, but this is an over
| simplification. Sellers are not guaranteed a "market price"
| so there is room to trade a small margin for guarantees and
| hassle free home selling.
|
| The problem seems more that they were not getting "enough"
| houses doing it this way, especially competing against
| Opendoor, and so they had to bid higher and on more
| properties in order to hit "scale". And that lack of
| selectivity is what led to the bad basket of houses they now
| own.
| phire wrote:
| No, that's not the issue.
|
| The issue is that their machine learning model can't
| possibly be 100% accurate, there will be some amount of
| error that is shaped in a normal curve.
|
| If their model overestimates the market value, they end up
| massively overshooting their goal price of "slightly less
| than market value", the seller accepts and they lose money.
| If their model underestimates the market value, they will
| offer way too little and the seller will go elsewhere.
|
| Even if they get their estimates right 99% of the time, the
| 1% of cases where they get it wrong will slowly drain money
| out of the scheme.
| encoderer wrote:
| Sellers don't have perfect information about the value of
| their home. They get a market value estimate from a
| realtor but that is just an estimate.
|
| Of course iBuyers can't perfectly forecast the market but
| that is why they add 3-7% fees, a very large buffer on a
| house purchase.
|
| Again, this is where Zillow ran into problems: they
| reduced or eliminated that fee to win more deals versus
| opendoor.
| hogFeast wrote:
| They didn't eliminate their fees (fee is the wrong term
| to use). Their model was built, maybe this changed, on
| being within 200bps of breakeven. Obviously, they only
| bought when the model would say: this will make money. Or
| are you saying they looked at the model, the model says
| you will lose money, and they decided to do it...that
| makes no sense, even for SV.
|
| Flip this around, are you saying that if the model was
| correct they wouldn't have made money? The problem was
| the model saying something was a good buy when it wasn't.
| The model was bad. Sellers do have good information, at
| least better than Zillow.
|
| Generally, this is a misconception about how things like
| quant investing actually work (this was an attempt to
| apply quant investing to housing). Some people, usually
| people without actual market knowledge, view quant
| systems as providing greater information. In reality,
| most quant systems are just responding to changes in
| liquidity. The amount of actual fundamental information
| these systems provide is very minimal, and will always be
| beaten by a knowledgeable human. The reason why is
| simple: there is a huge amount of private, non-
| quantifiable information with these domains (and this is
| true in investing and property, doing this in resi
| housing is nonsensical).
|
| I have seen fundamental quant investing work but only
| when you combine quantitative work with a knowledgeable
| human. I have seen the same thing in sports betting
| syndicates too (it does vary though, in some games
| quantitative data does capture more of the relevant
| information and machines can beat humans in those
| instances...but if there is substantial private, non-
| quantifiable information then it stops working).
|
| This is hard for people to accept because lots of people
| spend lots of time and effort at university being taught
| that ML is effective. But ML is only as good as the
| information you put in. The demise of value factor
| investing is a perfect example: collect a ton of PHd
| quants and finance professors, they start doing
| fundamental investing but without doing any research
| themselves, and it has done nothing but haemorrhage cash.
| It takes an extraordinary amount of education to supress
| common sense here.
|
| You have to understand the domain. You have to understand
| the information you are putting in. Zillow did neither,
| they thought ML would save them.
| encoderer wrote:
| Look up their "project ketchup". Their managers overrode
| the models and cut both fees and reno cost to win more
| deals. The WSJ and Business Insider wrote about this. I
| was at Zillow for many years and the insiders I know tell
| me the articles are correct but just lacking some nuance.
|
| Many people leap to their own reasons why Zillow offers
| failed but the most proximate cause really does seem to
| be management and operational failure.
| hogFeast wrote:
| Saying that management bought at prices higher than model
| is not the same thing as saying they bought houses
| expecting to lose money. All that was said was that
| management increased the prices they would pay and
| changed the model so they could pay more. Nothing
| validates the model (again, this is a common-sense
| conclusion given the informational disparity that Zillow
| was at).
| encoderer wrote:
| Right, they didn't expect to lose money. They saw they
| were only closing 10% of deals and wanted to take a
| higher share from opendoor. They probably thought the
| market was going up fast and their models were too slow.
| Blackstone4 wrote:
| It is called the winner's curse...at an auction, the highest
| bidder wins the asset but to do so they pay the highest price
| so better hope you are right when you win
| opinion-is-bad wrote:
| The winners curse also creates the curious corollary that
| one should probably bid less, the more people are in the
| auction.
| kwertyoowiyop wrote:
| Trying to beat an auction with a single offer (and still make
| a profit) sounds like a very difficult task, whether it's
| done by a human or AI.
| throwhauser wrote:
| I think the tone is appropriate, because the issue is a bit
| more subtle than that. Zillow was afraid to _plan_ for the
| large losses necessary to gather the only data that counts,
| i.e. the data that is the outcome of their own processes.
|
| Planning to lose money takes nerve. Zillow tried to avoid avoid
| the pain, and ended up abandoning what might be a profitable
| enterprise (for someone else) in the future.
| seoaeu wrote:
| Zillow is passing on an infinite number of potentially
| profitable enterprises. The reason they attempted this one is
| because they thought they _already had good enough models to
| avoid taking large losses_. If you read their statements, it
| is clear the reason Zillow is abandoning the this effort is
| because of inaccuracies in their models not just because they
| were spooked by losing money. They were also spooked last
| quarter by making too much money!
| vmception wrote:
| I hear the division was toxic which makes more sense than
| all of this.
|
| CEO said cut! Way to go!
|
| This loss was not immaterial but it also wasnt too material
| as they werent even leveraged on the homes. They had orders
| of magnitude more capital to risk if they really chose to
| dive into this or take it at least to real estate 2008
| levels. Far from it.
| throwhauser wrote:
| > [T]hey thought they already had good enough models to
| avoid taking large losses.
|
| That's a fair point; the essay doesn't do much to
| distinguish whether they didn't know they needed to take
| losses, or couldn't take the pain of the losses.
|
| Nevertheless, it's a pretty good analysis of what a company
| needs to do, in order to build a model relevant to their
| own actual business. They need to both know about the pain
| involved, and be prepared to take it. (And even then it
| might not work!) Third-party data (and suffering) might not
| be a good substitute.
| seoaeu wrote:
| Their model was something like buy houses for
| 'market_price(house) * 95%' and then sell them for
| 'market_price(house)'. The article argues that they
| should have devised a core complex model for asking
| prices, but an equally viable strategy would be to make
| sure their market price estimations were sufficiently
| accurate. That doesn't take any company specific
| information so it is entirely plausible (although false)
| that their Zestimate values would work well enough.
| indymike wrote:
| > The reason they attempted this one is because they
| thought they already had good enough models to avoid taking
| large losses.
|
| Risk aversion and launching a new business strategy do not
| work well together.
| djbusby wrote:
| Wait. There is a lot of messaging telling entrepreneurs
| to try to de-risk their new ventures. The common pattern
| I observe is having a new ideas and de-risking it into a
| successful business.
| indymike wrote:
| > The common pattern I observe is having a new ideas and
| de-risking it into a successful business.
|
| That is a common pattern, but when you see a company
| launch a new venture and the primary goal is to not lose
| money, often, the desire not to lose money leads to
| decisions that prevent actually making money.
| seoaeu wrote:
| You could use that argument to justify spending more
| money on any unprofitable venture. If you discover that
| some market segment is higher risk or lower profit than
| you expected, that is a good reason to consider course
| correcting.
|
| Around 2008, some investment banks famously had a single
| division manage to lose significantly more money than the
| entire rest of the company made over the same time
| period. Zillow not wanting to replicate their mistake
| isn't necessarily a bad decision.
| csours wrote:
| Your data is not neutral, it is opinionated. Who is asking the
| question? What do they use the data for? What questions are they
| not asking?
| cbsmith wrote:
| The amount of Monday morning quarterbacking of Zillow is just
| staggering.
| black_13 wrote:
| That it was a bad idea?
| igammarays wrote:
| Good riddance. If large-scale house flipping took off, we might
| actually end up in a scenario where housing was treated as a
| speculative asset, with empty houses getting flipped between
| investors looking to make a quick buck, further lowering the
| supply of actual places to live (because housing units remain
| empty while being flipped), driving up the cost for families who
| just want a place to live. Oh wait...
| h2odragon wrote:
| My wife did some work for the Census last year. Our extremely
| rural neighborhood has lots of unused housing, some for a
| decade+. That work got her out to see some of the places not
| visible from the roads, and increased our awareness of the
| scale of the problem.
|
| At a guess, in our county, 20%+ of the housing is idle, owned
| by out-of-state companies, some of whom pay property taxes and
| some dont. The county isn't auctioning off because of tax
| default anymore, no one was buying these places at $100. Many
| of these places are complete teardowns now; some actually no
| longer exist, having burned or apparently been scrapped. The
| tax assessments on those have not been adjusted, for the few i
| checked.
|
| I think the housing market is so fucked no one really grasps
| the scale of the problem.
| toast0 wrote:
| > The county isn't auctioning off because of tax default
| anymore, no one was buying these places at $100.
|
| What's the issue with out of state companies owning rural
| properties nobody wants? If the market is heating up, maybe
| it's time to run tax auctions again.
|
| In WA state, if there's no bidders, the county retains the
| land and will auction it again when someone expresses
| interest (or it some cases, can sell it to a neighboring land
| holder without auction, like for the 1930s era tax
| foreclosure I bought last year)
| h2odragon wrote:
| They'll eventually be reclaimed and re-titled one way or
| another I'm sure. I'm concerned with the larger
| implications, if my supposition is correct that they are
| being accounted more valuable than they actually are. These
| are the leftovers of Countrywide mortgage bonds and such I
| think.
| toast0 wrote:
| Makes sense now, thanks!
| jason-phillips wrote:
| > I think the housing market is so fucked no one really
| grasps the scale of the problem.
|
| I don't think I agree with this assessment. I live in a very
| rural area two hours northwest of Austin, literally in the
| middle of nowhere. I've studied the local economy and
| understand how things work here.
|
| I think the characteristics you've identified in the rural
| housing supply are not unusual and also not as serious in a
| practical sense as you seem to be indicating. For example, in
| San Saba, Texas, 20-30% of the households are under the
| federal poverty threshold. The median household income in the
| town of San Saba is about $32K/yr. People just don't have any
| excess cash so the maintenance on dwellings is neglected.
| That means folks become extremely thrifty and resourceful
| patching what needs to be patched, very cheaply, if not for
| free. Some dwellings simply aren't maintained and one day
| won't be there anymore.
|
| Families live on small budgets, don't require much and
| generally just "get by". The municipal and county governments
| have very small budgets but extremely resourceful staff who
| accomplish a lot with very little. Everyone comes together as
| a community when needed (see: February 2021 freeze event) and
| it all works very efficiently, actually.
|
| To someone who is not from here and who doesn't understand
| that dynamic, they might see those properties as you
| described and believe a tragedy was unfolding. But that
| doesn't reflect reality on the ground vis-a-vis my neighbors.
| h2odragon wrote:
| I'm in rural TN; not that different a place at all. I'm not
| speaking of family owned homes tho. I'm talking about the
| _Abandoned, uninhabited_ homes that are now owned by some
| out of state thing per county records... which is a _lot_
| of them. LLC 's and INCs whom I believe have the properties
| valued highly on some book somewhere and haven't done
| anything to maintain them.
|
| Our local Craigslists always have "Property inspector" jobs
| listed. You go take some cell phone shots of buildings to
| prove they exist. The people I have spoken to who have done
| those say they didn't bother going to the places as often
| as not and took pics of some neighbors house. Even when
| people actually do that job and document the true state of
| these properties I can't help but suspect the information
| is buried or lost because _thats not the narrative
| management would want_.
|
| The actual family owned housing stock got better the last
| two years, our population doubled for the last 3/4ths of
| 2020, and all those relatives did a lot of renovation and
| rebuilding.
| jason-phillips wrote:
| I actually used to work with people from East Tennessee
| for the past 2.5 years. They described how the Knoxville
| area was growing like crazy with folks from the coastal
| states moving there.
|
| I understand what you're saying. The ripple effect
| created by that dynamic would unjustifiably inflate local
| property values, reducing affordability for locals,
| creating synthetic demand by reducing supply as the land
| could otherwise be auctioned.
| h2odragon wrote:
| West TN; we've got that happening too. The neighbor's
| $750k McMansion has ludicrous "market value" implications
| for the hunting camp trailers beside it and the
| doublewide up the road.
|
| and (ahem) East TN is more "western Arlington VA" IMO. I
| said _rural_. I 'd have to walk a half mile to get a
| decent rifle shot at a neighbor. It's getting too crowded
| here.
| SteveGerencser wrote:
| You just described my road here in Henderson County,TN.
| We bought 100 acres and built a dream home. In the last
| years (ish) 4 new single wides went in and a couple of
| new smaller homes. We were told during the entire build
| that we will never get out of it what we are putting into
| it and we don't care. We aren't building for resale,
| selling it is our kid's problem.
|
| But there are so many abandoned places out here. People
| have just walked away and never looked back. We had one
| across the road that over the last 10 years the woods has
| reclaimed and unless you knew that it was there, you
| would drive right past it.
| conductr wrote:
| My observations passing through rural Texas matches this.
| You frequently see houses that probably only served 1 maybe
| 2 generations and then they are in a poor condition
| uninhabitable by even those folks used to roughing it.
| Housing stock in rural areas just doesn't last long.
| jason-phillips wrote:
| Finding good carpenters out here who can do structural
| repairs is effectively impossible.
| 01100011 wrote:
| FWIW I lived in San Diego and saw this too. Houses bought
| by parents for $50k in 1973 ended up being unmaintainable
| for some of the families even with Prop 13 keeping their
| taxes low. Then you'd have houses passes to kids,
| sometimes with drug problems, but in any case, no
| resources or knowledge sufficient to maintain a house.
| seanmcdirmid wrote:
| How are the schools funded?
| jason-phillips wrote:
| Both local property taxes and property taxes from urban
| areas that are redistributed to rural communities by the
| state of Texas.
|
| San Saba ISD is probably the best funded entity in the
| whole county. Every student has a laptop and home
| internet. The graduation rate is 100%. It's a small
| school; the senior class is only 50 students.
|
| They built the new school in the middle of town, thus
| highlighting its position of import within the community.
| seanmcdirmid wrote:
| So Texas funds education at the state level via property
| taxes? That sounds surprisingly progressive of them.
|
| Washington state does something similar, though it's more
| of a subsidy. Education is still mainly funded locally,
| but the state kicks in with its own funding for poorer
| districts, so Seattle property taxes subsidize schools
| across the state in Spokane.
| WarOnPrivacy wrote:
| > So Texas funds education at the state level via
| property taxes? That sounds surprisingly progressive of
| them.
|
| It sounds like that funding decision predates the current
| crop of state leadership
| jason-phillips wrote:
| > It sounds like that funding decision predates the
| current crop of state leadership
|
| If anything, today it is the folks in Austin (who are
| predominantly politically liberal) who decry their
| property taxes being used to fund rural school districts.
|
| People who are actually from Texas know that we help each
| other out. That's how we roll.
| kevin_thibedeau wrote:
| Everyone forgets it used to be a Democratic state when
| Republicans were the reviled coastal elites.
| seanmcdirmid wrote:
| That was when "Southern Conservative Democrat" was still
| a thing. Republicans were reviled in the South because
| they were literally the party of Lincoln, the most
| unpopular politician among southern whites for a long
| time (suffice it to say, black southerners had no problem
| voting for Republicans when they were allowed to vote at
| all). The turning point didn't really start until Nixon's
| southern strategy, and took a three decades to finish.
|
| I'm still surprised that Texas would distribute property
| taxes equally like that for education. Even if they were
| run by Democrats, they were never run by the liberal
| kind.
| goldenkey wrote:
| You'd be surprised at how progressive southern states
| are. The Texas state motto is literally "Friendship."
| Now, I don't know much about Texas but I did live in
| Arizona for a few years. It surprised me more than a bit,
| as someone who grew up in New York.
|
| Arizona legalized medical marijuana quite early, followed
| by recreational marijuana. Their medicaid program AHCCCS
| [1] is extremely comprehensive and even pays for
| Uber/Lyft to the doctor's office and back. Patients are
| able to see a great selection of GPs and specialists, and
| the copay is always $0. The accompanying drug plan is
| comprehensive, also with a copay of $0. AHCCCS will
| approve expensive modern drugs like Rozeram (supercharged
| melatonin analog for sleep) if the sufficient
| documentation of reasonable need is provided.
|
| Cactuses are protected from destruction by law, and must
| be transplanted when doing clearing for construction. You
| may find the idea of being able to own a firearm without
| a license to be unpalatable but the state largely remains
| very safe crime-wise (perhaps due to that?)
|
| I miss living in Arizona. It's a beautiful state with
| very caring folk. I saw almost no homeless folks in
| Phoenix. Folks there seem to really care about their
| fellow citizens. Southern hospitality is for sure a
| thing, take it from a daft boy from Brooklyn!
|
| [1] https://www.azahcccs.gov/
| seanmcdirmid wrote:
| > Cactuses are protected from destruction by law, and
| must be transplanted when doing clearing for
| construction. You may find the idea of being able to own
| a firearm without a license to be unpalatable but the
| state largely remains very safe crime-wise (perhaps due
| to that?)
|
| My mom lived in Tucson and decided on a visit that I
| might want to go shooting with her and her boyfriend at
| the time. Suffice it to say, it didn't go well. BTW,
| Arizona does very poorly in crime rate (10th highest for
| violent crime, 3rd highest for property crime),
| especially Phoenix and Tucson (but is very urban, so
| there is that also). I'm not sure why you consider it
| safe crime wise when the numbers say otherwise. They also
| do very poorly in education (rank 48th). I was really
| surprised they could beat New Mexico and Louisiana
| (https://www.wmicentral.com/news/latest_news/arizona-
| ranks-48...).
|
| It is beautiful. I would love to live in Tucson someday,
| but with the bad schools, it would have to be after my
| kid was done with school and I retired.
|
| > I miss living in Arizona. It's a beautiful state with
| very caring folk. I saw almost no homeless folks in
| Phoenix. Folks there seem to really care about their
| fellow citizens. Southern hospitality is for sure a
| thing, take it from a daft boy from Brooklyn!
|
| When I was a kid, I took a greyhound bus from Vicksburg
| MS to Seattle WA via the southwest approach (I later did
| the northwest route, which wasn't as interesting). People
| would get on the bus from various prisons in Texas (the
| bus stopped a lot at prisons), New Mexico and
| Arizona...and were all going to LA. Why bother being
| homeless in Phoenix (when summers can kill) if LA isn't
| that far away? Heck, that applies to Texas as well, not
| just Arizona.
| pueblito wrote:
| Arizona isn't in the South
| registeredcorn wrote:
| I've noticed similar situations to this in my own area.
|
| In your opinion, what do you think the most effective way
| to help these families out might be?
| jason-phillips wrote:
| > In your opinion, what do you think the most effective
| way to help these families out might be?
|
| This is a question that I'm well-positioned to answer. I
| moved to this rural area in 2018 after living in Austin
| for 24 years. I immediately looked for ways to volunteer
| and help.
|
| I developed relationships with elected and community
| leaders, started my own "technology incubator" to teach
| technology skills and classes. I explored establishing a
| regional technology council with my county judge and
| Texas state leadership. The community liked that I was
| volunteering but the actual uptake, expending effort to
| learn and implement what I was teaching, wasn't there.
| They didn't know what to do with it. The gap between
| their world and the world we know at HN was too wide to
| be bridged effectively.
|
| My experience is applicable to every problem here where
| someone thinks they may be able to help in some way.
| Whether it's teaching job skills, helping those who are
| addicted to meth or whatever, I believe people can't be
| helped if they don't want to expend the effort to get
| from A to B themselves.
|
| There are many reasons for this, why offering to help in
| an economically-depressed or disadvantaged community
| doesn't yield results. Locals are apathetic, comfortable
| living in the middle of nowhere with very low
| expectations, or else they have poor self-esteem and
| don't believe they can do better.
|
| I don't "push" anymore. I just try to be empathetic and
| understand their situations. This past Thanksgiving I
| asked the community to tell me if anyone was unable to
| get a turkey for Thanksgiving and would like one. Two
| families responded; I was glad to help. It's little
| things like that which I can do to help their situation
| which I feel is the best approach now.
|
| Edited to add: There is an organization here called
| "Mission San Saba" where a group of ~30 volunteers will
| pick one house per year to renovate, typically for an
| older or economically-disadvantaged family. That has been
| very successful here.
| gnopgnip wrote:
| Vacant housing is a problem, but across the US less than 2%
| of single family homes are vacant
| rsj_hn wrote:
| Vacant housing is only a problem in constrained areas. The
| vast majority of the U.S. is not constrained. Your summer
| cabin in Montana isn't depriving anyone of a home, because
| it isn't driving up prices. Your unoccupied condo in
| Manhattan _is_ depriving someone of a home, but I suspect
| that there are not so many of these.
| asdff wrote:
| When they did the vacancy tax in Vancouver it only
| affected a couple hundred properties out of like two
| hundred thousand in the market.
| reaperducer wrote:
| _in our county, 20%+ of the housing is idle, owned by out-of-
| state companies, some of whom pay property taxes and some
| dont._
|
| I've seen this personally, too. A house I rented until a
| couple of years ago was owned by a Chinese company, which
| also owned half of the other houses on the block. We all paid
| rent to the same LLC that forwarded the cash overseas, and
| did almost zero maintenance.
|
| _I think the housing market is so fucked no one really
| grasps the scale of the problem._
|
| One thing I don't see discusses very often is the affect that
| large "master-planned communities" have on a city's housing
| prices. I've seen at least three cities where mega developers
| like Howard Hughes Corp own massive tracts of land, but
| instead of building houses, sit on that land waiting for the
| price of housing to go up. Sometimes the developers are very
| open about it. Sometimes not. But instead of allowing a free
| market to develop 5,000 new homes, they develop one lot here
| and one lot there.
|
| Or worse -- I've seen them build hundreds of homes and then
| sit on them, empty and vacant, waiting for prices to climb
| high enough to put the houses on the market. Again, a drip at
| a time, to keep the housing supply artificially small so they
| can boost their profits. Meanwhile, people have nowhere to
| live.
| asdff wrote:
| That's been true for rural areas since the green revolution
| in the 1950s changed agriculture and manufacturing went
| overseas. Even if there is still a mine in the hills outside
| of town, there are fewer jobs at that mine than there were
| when the town was built out 100 years ago.
|
| Jobs generate demand for homes. Homes cost a lot in areas
| where there's been more jobs added than homes. In the last
| decade, the bay area has added seven jobs per every unit of
| housing constructed.
| libertine wrote:
| Half way through I was already clicking "Reply" thinking "...is
| this guy for real?!", only to see the "Oh wait..."
|
| The amount of social media content revolving around "how I
| became a milionaire/how I reached my first million" and the
| common factor is "I bought a house in 201*", then I'd say
| something is a bit off...
|
| Either there's massive speculation, or 1 million isn't what it
| used to be, or worst: both.
| cwilkes wrote:
| The problem with those scenarios is that for every one that
| made a killing in real estate there's plenty that barely
| broke even. The winners think they have some special sauce
| ... maybe rhey did, maybe theg didn't.
|
| The problem is that their blogging about it attracts the
| people that want to get rich quick and they are the ones
| likely to lose their shirts.
| AdrianB1 wrote:
| It's just a bubble: owners want the value to increase, county
| or city wants the value to increase (to get more tax money),
| everyone wants the supply to be very limited to increase the
| price and the value, it's a Munchausen pulling himself by the
| hair from the swamp. In this case 1 million is not what it
| used to be.
| lotsofpulp wrote:
| Or $1M has different purchasing power in different places.
| mistrial9 wrote:
| I wonder why so few here question the basic assumption of
| injecting from above, machine-learning models to extract profit,
| into a vital part of the reproductive cycle of human families.
| pid-1 wrote:
| https://www.youtube.com/watch?v=ajGX7odA87k&t=833s
| Dowwie wrote:
| Feels analogous to the history of the collateralized debt
| obligation debacle where the models used to value CDOs were
| trained on data that no longer resembled reality. At least Zillow
| can live to fight another day, where as Stan O'Neal put all of
| Merrill Lynch's chips in with one of the biggest make-or-break
| gambles in the history of finance and the market turned against
| it, rendering Merrill to a fatally wounded company bailed out by
| Bank of America.
| marcinzm wrote:
| I think a key point that is missed is the feedback cycle time.
| Real time bidding advertising has I believe a number of the
| listed concerns however the feedback time is maybe hours at most
| and might be milliseconds. So the risk is in general a lot
| smaller and worst case you just lose some of the money you spent
| that day/week. With long term assets you could lose months worth
| of investments before your feedback loop fully kicks in.
| abiro wrote:
| I think the title is highly misleading. The main point here is
| that Zillow simply had no idea what it takes to be a market maker
| and their pool was picked off by savvy traders.
|
| Good tweetstorms with technical explanations on how that
| happened:
|
| https://twitter.com/macrocephalopod/status/14558873523715973...
|
| https://twitter.com/0xdoug/status/1456032851477028870?s=21
| MisterBastahrd wrote:
| Zillow offered to buy my home at 30% more than everyone else in
| the market for cash, without an inspection, and I wasn't even
| looking to sell it at the time.
| treis wrote:
| I'll second that this article is just wrong. Zillow burned
| plenty of money in their Offers business. The problem is that
| all that spending revealed that they performed poorly in a
| questionable market segment.
|
| Ultimately they were really bad as flippers. More often than
| not paying more than market price for the homes they bought.
|
| I think the root problem is that this was a panic move. They
| saw Open Door's success and thought they had no choice but to
| try and replicate it. But its a questionable business move for
| Zillow and ultimately they couldn't make it work
| Petabits wrote:
| Would it be too dystopian if governments sectioned off certain
| neighborhoods and set price caps per sqft? This would make it so
| speculative investors are unable to build capital in houses, thus
| leaving homes for actual people. I'm not super familiar with land
| grant homes, but the prospect of seemingly fixed price homes
| seems to prevent investors from buying in.
| leot wrote:
| Real estate is one of the few markets where non-experts can make
| money, where it's not a hyper-liquid winner-take-all game.
| Coupled with this is the fact that housing is a necessity and
| owning a home leads people to invest in their communities more
| than if they were renting, I think it's a good thing if Zillow
| (and OpenDoor, etc.) fail at pushing everyday people out of the
| business of real estate investing. Here's hoping we see some
| regulation--the illiquidity of the home buying market is not a
| problem that needs to be solved.
| jdross wrote:
| Opendoor doesn't compete with real estate investors, they
| compete with realtors and mortgage brokers.
|
| Opendoor's primary benefit is to enable people to move when
| they otherwise could not easily do so, creating more liquidity
| and matching supply and demand (often number of bedrooms in
| house to number of bedrooms now needed).
|
| The challenge with moving is that most people need to sell
| their current house before they can afford (or even know what
| they can afford) to buy their next home. Opendoor lets a family
| buy that next home with its cash, then list their current home
| on the market or sell it to the company so they avoid the
| double mortgage or double move (home->rental->home)
| robocat wrote:
| Does Opendoor avoid some of the standard x% realtor fees on
| either or both of the transactions? Reduced fees could easily
| make a huge difference to expected profitability.
|
| In contrast, "Zillow Seeks to Sell 7,000 Homes for $2.8
| Billion" so Zillow lost more than a few percentage points.
| jedberg wrote:
| Zillow's mistake is that they thought their AI could replace
| human buyers instead of augment them.
|
| Most AIs today are for augmentation, not replacement. Vehicle
| autopilots are a perfect example. The ones that are commercially
| available aren't capable of replacing the human, they just
| augment the human's abilities.
| skohan wrote:
| > They thought they needed to build a machine learning model when
| they really needed to build an entirely new organization, one
| that possessed the technical and cultural mindset necessary to
| succeed in this space.
|
| I totally agree. It's not impossible to imagine their model
| working: why couldn't you serve as a market-maker for homes at a
| large scale, especially with the unique insights Zillow could
| have based on their datasets.
|
| However I think where the hubris lay is in how they thought they
| could leapfrog all the way to an automated solution before
| building a competency as a house-flipping company.
|
| From what I understand, where they failed was partly in building
| a rich enough model to properly account for the less easily
| quantifiable elements which ultimately account for a property's
| value. I.e. the price per square foot might make a property look
| like a steal, while something like a sewer main nearby, or
| problematic neighbor could radically change the value proposition
| to anyone standing at the site. That's a non-trivial problem to
| solve for even the best ML and it's not clear how you would
| automate this.
|
| If you ask me, instead of focusing on building an automated price
| discovery system, they should have started by trying to build a
| quality home-flipping organization, and figuring out how to
| super-charge manual work using their datasets. Over time you
| might find ways to optimize the process and increase the level of
| automation to scale output relative to head-count.
| it_does_follow wrote:
| > a machine learning model
|
| Not to mention that generally ML models are not useful for
| assessing _risk_. ML nearly always focuses almost exclusively
| on some point estimate rather than a distribution of what you
| believe about a value. The former case is all about
| _expectation_ and the latter about _variance_. Correctly
| modeling variance is far more essential to risk modeling than
| expectation alone.
|
| I recall talking to a startup that was attempting to model
| credit risk by building a binary classier for defaulting, and
| trying to figure out a way to use this to score people for
| credit (obviously they chose to ignore the fact that there is a
| huge industry with decades of experience in assessing consumer
| credit risk).
|
| They focused exclusively on finding more advanced models to get
| better AUC without even realizing that that's not important. I
| mentioned that the most simplistic credit score model should at
| least model P(default|info) and then set the interest rate to -
| P(default|X)/(P(default|X)-1) to break even and they couldn't
| comprehend this basic reasoning. It was doubly hilarious since
| their population's base default rate was such that the solution
| to this equation was higher than the legal limit they could
| charge for interest.
|
| In the early part of the current startup/tech boom there was a
| focus on "disruption", the idea that new ideas could easily
| dominate old ways of doing things. But for many industries,
| such as credit/lending and real estate, you should at least
| understand the basic principles of how these "old ways" work
| before trying to disrupt them.
| JoeyBananas wrote:
| > Not to mention that generally ML models are not useful for
| assessing risk. ML nearly always focuses almost exclusively
| on some point estimate rather than a distribution of what you
| believe about a value.
|
| It is actually quite a common practice to design neural
| networks that output probability distributions.
| it_does_follow wrote:
| That distribution is still a point estimate for a
| multinomial, not truly the distribution of your certainty
| in that estimate itself. This is essentially a
| generalization of logistic regression, which will of course
| give the probability of a binary outcome, but in order to
| understand the variance of your prediction itself you need
| to take into account the uncertainty around your parameters
| themselves.
|
| This can be done for neural networks, through either
| bootsrap resampling of the training data or more formal
| bayesian neural networks, both of these are fairly
| computationally intensive and not typically done in
| practice.
| NortySpock wrote:
| I was going to say, that seems like an "easy" second step
| once you get your ML to output hard numbers -- tack on
| ranges and confidence intervals.
| lotsofpulp wrote:
| > why couldn't you serve as a market-maker for homes at a large
| scale, especially with the unique insights Zillow could have
| based on their datasets.
|
| Why would Zillow have unique insights? With the exception of
| Texas, I thought real estate sales information is public
| information in the US.
| ctvo wrote:
| Can you not imagine how useful it is to know user data e.g.
| what neighborhoods receive the most clicks, what type of
| homes generate the most favorites, how long people view one
| listing vs. another, ... that is unrelated to public MLS
| data?
| lotsofpulp wrote:
| Maybe, but I was under the impression that
| Redfin/Trulia/Realtor.com would have the same information.
|
| Also, unless Zillow started imposing confidentiality
| agreements on their bids, then competing buyers would just
| have to bid $1 more without their dataset, right?
| ctvo wrote:
| Zillow is the largest aggregator. They own Trulia. I can
| squint and see the thought process here by Zillow, though
| execution, as evident, did not go as planned.
| lotsofpulp wrote:
| I somehow missed they had bought Trulia way back when.
| indymike wrote:
| > Can you not imagine how useful it is to know user data
| e.g. what neighborhoods receive the most clicks, what type
| of homes generate the most favorites, how long people view
| one listing vs. another, ... that is unrelated to public
| MLS data?
|
| Click data is much less valuable that the recent sale price
| data available in MLS. Using 90s style dwell time and click
| counts would likely yeild a lot of very noisy data. False
| positives from people's browser reopening with 15 tabs
| looking at different houses. False positives from social
| and paid advertising boosting a particular home or
| neighborhood's numbers. False positives from enterprising
| real estate entrepreneurs doing everything they can to get
| the clicks up in areas they own property to drive up
| prices. Meanwhile, the recent sale prices tell you much
| more, with certainty and are very expensive to manipulate.
| sokoloff wrote:
| Surely Zillow was _also_ using that data.
| indymike wrote:
| > Surely Zillow was also using that data.
|
| One would hope.
| mgraczyk wrote:
| Evidently not as useful as Zillow expected!
| iandanforth wrote:
| One example, User search behavior should contain several
| leading indicators.
| sokoloff wrote:
| I have given Zillow a lot of non-public information over
| years of searching.
|
| How many people search on bedrooms but not bathrooms? When
| people search on both, what's the pattern they use? If we
| highlight prices and BRs on the map does that give more
| clicks than just prices? How important are photos (times 50
| different questions there)? How strong a signal is repeat
| views spaced over time? Saving a house to favorites? Sending
| a link to a friend? Clicking on comps in the neighborhood?
| Which comps do people zero in on (as evidenced by spending
| more time on the page)? How strong a signal is sending a
| message to the real estate agent on the listing? What areas
| of the country are seeing an uptick in search traffic? How
| long between claiming a house as an owner on the site,
| updating the information, and listing it for sale?
|
| They are sitting on a (well-earned) treasure trove of data
| and it's not unreasonable to think they could use that to be
| better informed than another buyer without that information.
|
| Where they seem to have failed is in not augmenting that
| advantageous data with regular old boots-on-the-ground
| observations.
| silvestrov wrote:
| I think the opposite: there is not much valuable data, it
| is just noise.
|
| It is very difficult to go from what users browse to what
| they actually buy. People very often say one thing, then do
| something completely different.
|
| And sometimes they browse stuff just to make sure that
| their current decision is correct, so they will look at a
| lot of items they're not going to buy.
|
| (oh, and everybody and their mother knows photos are
| important. No need for ML to find that out)
| sokoloff wrote:
| Do you think that A/B or multi-variate testing works in
| general?
| silvestrov wrote:
| In some cases A/B testing works very well and in other
| cases not at all.
|
| So it is easy to test UI changes, but difficult to find
| out why people do what the do.
| skohan wrote:
| My understanding is that they believed they had an advantage
| in terms of buyer intent information. Everyone can see who
| buys what, but Zillow has access to more information about
| how people shop for homes, and the events leading up to the
| actual sale.
| [deleted]
| johnebgd wrote:
| People forget that tech is able to automate workflows. You
| don't often yield success when you attempt to automate and
| invent the workflows in parallel.
| spywaregorilla wrote:
| I would say the opposite is true. Dying companies are stuck
| in their own routines because they're trying to automate
| their poorly designed processes that require humans at
| multiple steps. Smart companies are designing newer, better
| processes that are enabled by tech.
|
| Starting from scratch can be a huge advantage.
| javajosh wrote:
| This is a statement I would have agreed with wholeheartedly
| 20 years ago, and that I disagree with wholeheartedly now.
| spywaregorilla wrote:
| I'd be curious to learn why. I've seen the pain of
| companies tricked into thinking robotic process
| automation to do their horrendous excel workflows is a
| good idea. I've seen the benefit of a decent python data
| engineer with a small AWS budget.
|
| The techier folks definitely have a different set of
| problems but the speed at which hings get done is night
| and day. Companies with old school work patterns (which,
| in my personal experience, means dusty old banks) are
| terminally entrenched in their ways.
| mattcwilson wrote:
| I think you're both right.
|
| Taking some hopelessly byzantine, spreadsheet-driven
| process and "automating" it by building a Rube Goldberg
| scripting framework around it is the kind of totally
| stupid automation that doesn't work.
|
| Actually getting down to surface level and understanding
| fundamentally what each of those humans is accomplishing
| via those spreadsheets, extracting that all the way back
| out to a domain model and process flow diagram, and then
| selectively replacing process steps, whole cloth, with
| tech designed to be an actual subservice with SLA
| targets, is the right way to do it.
|
| Throwing the spreadsheets and/or humans out altogether
| and starting "from scratch" is so exceedingly and
| needlessly risky from an information loss and hubris
| point that, well, good luck, but you're nearly certain to
| fail.
| rrrrrrrrrrrryan wrote:
| Ideally, you want to understand the whole process from
| beginning to end, including all the complex edge cases,
| _before_ trying to automate it, _then_ automate the whole
| shebang in one giant undertaking. You need a tremendous
| amount of high-level buy-in to pull this off, as people
| will have to wait and suffer with the old process until you
| 're completely done building the new one.
|
| What often ends up happening is a large manual processes is
| automated bit by bit, and you end up with the situation you
| describe: a poorly designed manual process painstakingly
| replicated in code. Full automation is often never actually
| achieved here.
|
| The absolute worst thing to do, though, is to begin
| automating the thing without fully understanding it. It's
| putting rocket boosters on your self-driving car without
| first understanding the rules of the road.
| caseysoftware wrote:
| Personally, I would treat the GP's mindset of "inventing
| workflows" differently than your mindset of redesigning at
| "poorly designed processes".
|
| Yes, a poorly designed process sucks _but_ it works at some
| level. That means the rough flow of it is figured out. Yes,
| there are exceptions and complications and all kinds of odd
| things but it 's fundamentally different. It's not "from
| scratch" as you're taking an existing working-but-broken
| process where you know the input, know the output, and
| rethinking everything in between.
|
| In an "inventing" scenario, you have what you think should
| be the input, a notion of what the output should be, and
| you're trying to build towards that notion.. without the
| validation that you're thinking of it correctly.
|
| The first is a harder social problem (aka getting people to
| change) while the second is a harder technical problem.
| skohan wrote:
| Ultimately you have to build within your sphere of
| competence. If you have a well-established but
| inefficient manual process, it may sometimes be the case
| that burning it down and replacing it with a tech-driven
| approach might be the best way forward.
|
| But if you are trying to solve a novel problem, and the
| proposed solution involves "ML will magically predict the
| future", you'd better have a _very_ good idea of
| _exactly_ how the problems will be solved, or else you
| 're probably better off starting with good old-fashioned
| human intelligence.
| staticautomatic wrote:
| It's more complex than this in practice because in a large
| organization you have a significant change management
| component to every process change, whereas automation of an
| existing process immediately frees up bandwidth even if the
| process isn't great. I interview global executives for a
| living; I hear this every day and I fully believe it.
| [deleted]
| RyanDagg wrote:
| This is a critical concept that appears to be poorly
| understood in at least the web development circles I run in.
|
| It reminds me of one of my favorite Bill Gates quotes:
|
| "The first rule of any technology used in a business is that
| automation applied to an efficient operation will magnify the
| efficiency. The second is that automation applied to an
| inefficient operation will magnify the inefficiency."
| draw_down wrote:
| That sounds hard. Why don't we just rub some machine learning
| on it?
| pge wrote:
| Isn't is also true that the original pricing algorithm was
| built for a very different purpose? It was useful for getting a
| ball park estimate of value, but it was hardly accurate in the
| underwriting sense (for the reasons you point out). The hubris
| of assuming that those prices were so accurate that Zillow was
| willing to buy at them sight unseen is mind blowing,
| particularly when one takes into account the adverse selection
| (if Zillow's estimate is above what I can get from in-person
| bidders, I am more likely to take it than if the error is in
| the other direction).
| lordnacho wrote:
| Yes, you might discover that your average price is accurate,
| which is just fine for a reporting site. But beneath that
| there could be some structure, for instance there might be
| blobs of houses that your model makes too cheap vs reality,
| and blobs that are too expensive. If those are identifiable,
| eg via some sort of local knowledge, you might find that
| people will sell you houses that you've marked too high, but
| you can't buy the ones that you've marked too low.
| spoonjim wrote:
| Totally. There's a surly creep who lives on our street and
| the houses next to his are worth less because of that. But
| Zillow would never know that.
| neltnerb wrote:
| Makes me wonder if Zillow wasn't planning to "tune" the
| models, surely they wouldn't want to publicly publish what
| they think things are worth and then offer 5% less. I wonder
| whether accurate estimates or making money from flipping
| would have dictated their decision-making...
| dsizzle wrote:
| Even if their ML model provided excellent predictions,
| another potential problem they may not have accounted for is
| adverse selection: the only takers may have been on houses
| whose bids were too high.
| EMM_386 wrote:
| > I.e. the price per square foot might make a property look
| like a steal, while something like a sewer main nearby, or
| problematic neighbor
|
| This is the real problem.
|
| Even if they have the historical data for that exact
| house/unit, it won't help them in cases such as:
|
| * That nice view of the woods out the window is now blocked by
| a massive radio antenna that was just built there
|
| * The river running through the back yard is now heavily
| polluted by something up-stream
|
| * The new neighbor across the street is a huge nuisance and
| says they will never move
|
| * The house just had a mass-murder event in it
|
| Just because something is now cheaper than "comps" at price/sq
| ft and other metrics doesn't mean it's comparable.
| ricardobayes wrote:
| anectodal evidence, but yes, an apartment I lived in was 30k
| cheaper than everything in the house, and the estimate. So I
| was really happy to have caught a bargain. Then after moving
| in it turned out the neighbors were unbearable. The father
| had developed a DIY habit during covid and he would regularly
| put together furniture at 11PM. Then they had two monsters
| for kids. Would literally jump around uncontrollably for
| hours, and for some reason, through some defect or lack in
| the sound proofing, the sounds were even amplified. Every
| time they went down to the playground the kids were literally
| screaming at the top of their lungs the whole way down. I
| nearly lost my sanity and fortunately could sell it at at 2k
| loss in a year.
| lisper wrote:
| You could sue your seller for failure to disclose.
| desmosxxx wrote:
| "i never really noticed"
| lisper wrote:
| Yes, you'd have to be prepare to counter that with e.g.
| testimony from neighbors, or friends who heard the
| previous owners complain. It's not a slam-dunk, but it is
| an actionable tort.
| lazide wrote:
| Also good luck getting positive ROI on that multi-year
| lawsuit over things that buyer can reasonably say 'never
| bothered me really, I don't know what they're talking
| about - sounds like they're just irritated at life'.
| Especially when you factor in all the legal fees and
| several years of hassle going through the courts.
|
| None of these things are necessarily unusual in most
| neighborhoods. All at once is irritating to most people -
| but hard to objectively prove are a true nuisance in a
| legal sense.
| andi999 wrote:
| Apart from that of course you can sue anybody for
| anything (with more or less success); why would that be
| the case here? I mean isnt if neighbours are annoying a
| subjective thing? Do you know of any court ruling which
| implies one has to disclose the state of the neighbours?
| ricardobayes wrote:
| Yes, and even if something is super annoying, it might be
| legal. For example they listened to music until 2-3 in
| the morning a lot of cases. Thumping reggaeton. And while
| it for sure wasn't over legal limit by decibel, the bass
| made my bed shake.
| lisper wrote:
| It all depends. But in general you have a common law
| right to peaceful enjoyment of your property.
|
| http://bryancrews.com/private-nuisance-right-peace-quiet/
| nitrogen wrote:
| The one noise ordinance I've read in full also said that,
| even if the decibel limit is not exceeded, an audible
| beat or bass can also be cited.
| elliekelly wrote:
| There is a famous (among first year law students) case[1]
| that seems relevant given the nature of the issue is one
| a buyer would not reasonably be able to ascertain on
| their own. One possible point of differentiation: ghosts
| are a permanent defect on the value of the property while
| loud children living next door would probably only
| torment the homeowner for a decade or so at most.
|
| The opinion is famous not just for its unusual fact
| pattern but also because the Judge clearly had quite a
| lot of fun working in other-worldly puns and references
| while writing it.
|
| [1]https://en.m.wikipedia.org/wiki/Stambovsky_v._Ackley
| gregd wrote:
| You indeed can if there are nuisance neighbors and I
| believe that is considered a material fact in most
| states. However, most documents, I believe contain a Real
| Estate Transfer Disclosure Statement which would have had
| a line indicating a "yes" if there were nuisance
| neighbors and it would have been up to you to ask for
| more details.
| GCA10 wrote:
| This is the key insight. Systems like Zillow's model a dozen
| or so big factors that are easy to collect (square footage,
| exact location, nearby comps, sales history, etc.) -- and
| then treat the rest as minor random noise.
|
| Minor? Usually.
|
| Random? Not at all. A minor annoyance like a cracked driveway
| ($1,500 to fix) is also likely to be associated with older
| kitchen appliances, faulty water pressure, deteriorating
| deck; poorly seated windows, etc. And then, buying that house
| for what the algo tells you -- or even algo minus 3% -- isn't
| likely to be a happy choice. Its fair market price may be
| algo minus 10% or worse.
|
| Also worth bearing in mind, the Realtor community is not
| going to make life easy for Zillow. Once it's known that
| Zillow is loading up on clunkers, buyers' agents are likely
| to tell their customers: There's a Zillow house on the
| market, too. It's probably got problems. I'd demand a full
| inspection and some indemnities if I were you.
|
| Common flaw of market disruptors. They assume that the
| existing players will remain neutral and indifferent to their
| arrival. The real world tends to be much tougher.
| poulsbohemian wrote:
| Yes!! You nailed it! I spent a long career in software and now
| work in real estate, and you are spot on that they are not a
| company who understands real estate well enough to be buying
| and selling it. There are plenty of bad real estate agents in
| the world, but the amount of know-how and connections that good
| ones have is exactly the encapsulated in the examples you gave
| - local, specific knowledge that a national/international
| player isn't going to have and isn't going to be able to scale
| without a whole lot of human investment... gee wiz, kinda like
| real estate firms.
|
| I wish I had the data that I _assume_ they have internally,
| because watching their actions I'm not convinced they
| understand what questions would actually be interesting to
| explore with ml.
| initplus wrote:
| Even if Zillow had an algorithm that was 100% accurate at
| predicting current house prices, the housing market is just
| incompatible with market making. A market maker isn't exposed
| to changes in the price, they clip the ticket on providing
| liquidity regardless of price direction. Zillow may have been
| able to successfully speculate on house prices with an accurate
| model, but they would not be a market maker.
|
| Houses trade slowly, so would sit on Zillows books for a long
| time (days/months). Market makers on the stock market can have
| assets sit on the books for under a second. Houses are not
| fungible, which extenuates the slow trade problem.
| elliekelly wrote:
| > However I think where the hubris lay is in how they thought
| they could leapfrog all the way to an automated solution before
| building a competency as a house-flipping company.
|
| In my mind this is the problem with consultants who try to
| automate processes. It's really difficult (maybe even
| impossible?) to successfully write a program to make a computer
| do $thing if you don't understand the intricacies of how to do
| $thing manually.
| Lhiw wrote:
| > and it's not clear how you would automate this.
|
| The amount of things you encounter in the real world is
| ultimately limited.
|
| Any half decent valuer will already have a literal book on
| these types of things predefined.
|
| Automating it isnt really the problem, properly surveying the
| grounds and the area are.
|
| I'd also posit going this way is the wrong approach, they
| should be using metrics like time on site and ratio of views
| online vs views on site.
|
| These things work as proxies and are enough to apply as a
| modifier to more usual pricing models.
| spoonjim wrote:
| When we were looking for a house we rejected many because of
| the "wrong sort" of neighbor, ascertained entirely (and
| possibly erroneously) without meeting them. I doubt Zillow can
| model that with public data.
| Robotbeat wrote:
| One huge difficult-to-quantify risk is the public opinion risk
| of being a very high profile company that flips houses. If it
| had succeeded to actually push up housing prices considerably,
| the whole company could be destroyed in the court of public
| opinion and therefore probably would be destroyed legally,
| regulatorally, and legislatively as well.
| winternett wrote:
| It's a pretty interesting discussion as I sold my house just
| this year, and was frequently watching Zillow trends and
| information.
|
| Originally the estimate on Zillow said my house was 20% over
| the value I actually sold my house for just last month. I
| listed with a traditional realtor for a 5% commission, because
| when I looked up the service and other fees for Zillow sales, I
| found they included around 20% of cost for buying homes and
| closing within generally 10 days.
|
| As I listed my house, and as I reduced price on it for it to
| gain attention, I noticed the zillow estimate also went down to
| always stay below my listed price. I believe the estimate that
| both Zillow and Redfin display prominently were purely based on
| what my list price was changed to last, not on any meaningful
| algorithm, which can be very harmful to sellers and buyers,
| because it makes the process a bit deceptive by nature. Luckily
| Zillow also displays the price history on homes, which
| apparently cannot be "gamed" as much as the "zestimate" can be.
| Another thing I noticed was that the view stats on my listing
| that zillow regularly provided changed, even after days passed,
| that was very concerning because stats of that kind aren't
| supposed to change... They indicate real interest in a
| property, that guide decisions for sellers to reduce price, and
| they also indicate what is truly a "hot home".
|
| No matter what, there is always the "human factor" that can
| corrupt or even destroy any company, where realtors can game
| the process to maximize their own sales profit or positions, or
| where appraisers can inflate an estimate as a favor for a
| personal friend, even despite laws against doing so. In a bad
| economy, the lengths people will go to to suit their advantage
| are wild. This type of issue can never be properly addressed by
| any algorithm, and that's why trusting technology too much can
| so easily lead to failure in any setting.
|
| Ultimately I am glad I did not sell to Zillow, because of all
| of the potential for hidden costs and because they manipulate
| the process even when you don't use their service, but I am not
| feeling sorry for them as a company... I felt the impact of
| their presence in the market whether I involved them or not,
| and that's a big problem when it comes to preserving the value
| of traditional investment and stable investment in a house that
| should be properly addressed by regulation.
| breischl wrote:
| >as I reduced price on it for it to gain attention, I noticed
| the zillow estimate also went down to always stay below my
| listed price. I believe the estimate that both Zillow and
| Redfin display prominently were purely based on what my list
| price was changed to last, not on any meaningful algorithm
|
| The fact that a house is for sale at a given price, but has
| not sold after some time, is a strong signal that it's
| overpriced. The longer it's been sitting, the stronger that
| signal is. They'd be crazy not to include that data in the
| Zestimate.
|
| Now, if it's extremely fast, eg they adjust the price down
| within a day or so, then it seems a little ridiculous. OTOH
| the Zestimate has always been a rough indicator at best.
| winternett wrote:
| When you reduce price on a house listed on Zillow and
| Redfin right now, it bumps it to the top of taxonomy-based
| cues on those sites because of the information update,
| which increases overall recommendations/listing promotion
| to potential buyers. It's a new step in getting a property
| sold introduced by technology dynamics. Price reductions in
| traditional real estate listings worked differently (You
| were not refreshed on MRIS). with everyone performing price
| reductions though, that can have mis-leading effect on
| economic indicators, and it can also create harmful price
| reduction "panic" in certain markets though, so this is
| going to be a burgeoning issue moving forward.
|
| I am luckily both a web developer and knowledgeable about
| real estate, most people don't properly understand the
| dynamics that are impacted/introduced into the market by
| technology and algorithms... People assume the traditional
| real estate market rules are still in play primarily still,
| but technology has complicated everything... That's also
| why Zillow overbought homes, because people making critical
| decisions too often put "traditional pre-tech" real estate
| market concerns over considering modern impacts of IT to
| their decisions.
|
| My house sold within 2.5 months overall, it was not on the
| market for a long time.
| JumpCrisscross wrote:
| > _a market-maker for homes at a large scale...a house-flipping
| company_
|
| These are different things.
|
| Archetypal market making involves simultaneously buying and
| selling an asset. Flipping involves buying, improving and later
| selling. One _might_ be able to deal with the heterogeneity of
| houses by operating at scale. (Zillow attempted this.) One
| might also deal with the delay between buying and selling by
| hedging. (Zillow never seems to have thought about this.) But
| the improvement function makes what Zillow attempted
| fundamentally separate from market making.
|
| They weren't paid to provide liquidity. If anything, they paid
| a premium for scale and immediacy. They were a real estate
| operation masquerading as a tech outfit. WeWork in different
| stripes.
| sklargh wrote:
| I never got WeWork because it looked like they onboarded all
| of a 10-year lease's duration risk and then hoped to make up
| the difference somehow?
| erikpukinskis wrote:
| > somehow?
|
| By marking it up and/or appreciation. They buy it for
| $500/sqft and then rent it for $100/sqft. In that
| hypothetical the breakeven is 5 years, plus overhead.
|
| If the occupancy doesn't work out in their favor, they may
| still make it up in appreciation.
|
| What's a duration risk?
| wpietri wrote:
| > Archetypal market making involves simultaneously buying and
| selling an asset
|
| Does it? I worked for a few years for a market maker, and
| that's not what we did. Simultaneous buying and selling is
| what the arb guys did. We'd buy and sell with generally short
| hold times. Which makes sense to me given that the exchange
| has market makers to provide liquidity. If something can be
| simultaneously bought and sold, then the market-maker is
| unnecessary.
| JumpCrisscross wrote:
| > _that 's not what we did_
|
| Archetypal, not predominant.
|
| > _Simultaneous buying and selling is what the arb guys
| did. We 'd buy and sell with generally short hold times_
|
| The ideal market maker is arbitraging (and eliminating the
| arbitrage-able inefficiency). That's why humans were
| replaced by faster-trading machines everywhere they could
| be. In most cases, the arbitrage is synthetic or
| approximate, _e.g._ hedging an options or swaps book. But a
| fundamental separation between speculating and marketing
| making is the latter does not take a view on the assets
| _per se_ , and should not be betting on their future price
| movement.
|
| No market maker always achieves the ideal. But they tend
| towards it. Zillow didn't have that tendency. In fact, they
| erected fundamental obstacles between themselves and that
| ideal.
| bee_rider wrote:
| If we look at archetypal on Wikipedia, we get:
|
| > 1) a statement, pattern of behavior, prototype, "first"
| form, or a main model that other statements, patterns of
| behavior, and objects copy, emulate, or "merge" into.
| Informal synonyms frequently used for this definition
| include "standard example," "basic example," and the
| longer-form "archetypal example;" mathematical archetypes
| often appear as "canonical examples."
|
| > 2) the Platonic concept of pure form, believed to
| embody the fundamental characteristics of a thing.
|
| The confusion between you two seems (to me at least) to
| fit almost entirely within the difference between those
| two definition. If you are describing the ideal market
| maker as essentially performing arbitrage, that seems to
| fit the second definition pretty well, right?
|
| Meanwhile if wpietri says that most of the work at his
| believed-to-be-typical example of a market maker was
| doing non-arbitrage stuff, that'd make sense, right? I
| guess in most places the main work would be managing the
| divergence from idealness.
| wpietri wrote:
| That could be it. Except that if market-makers were ideal
| in that sense, they wouldn't need to exist. If a buyer
| and a seller simultaneously exist at a given price, they
| can just trade with one another. Market-makers are
| valuable to markets only when they provide liquidity
| through non-simultaneous buy/sell pairs.
|
| I think it also leaves out that not every market maker
| wants to be flat instantly. The one I worked for, and at
| least some of our peers were sometimes happy to hold
| inventory for a bit when they thought the market would
| even out.
| wpietri wrote:
| Sorry, what's your source for this archetype? I thought
| maybe the place I worked for was just weird, but I've
| just looked at a half-dozen sources and as far as I can
| tell, we were pretty typical.
| JumpCrisscross wrote:
| > _what 's your source for this archetype?_
|
| I'd have to dig up the textbook sources, but the key bit
| is in the definition: market makers quote a two-sided
| market and make money from the spread [1], _i.e._ buying
| at the bid and selling at the offer. If it happens
| simultaneously, that's ideal. Every second one is long or
| short, risk and cost are incurred. Market makers seek to
| minimise and manage these.
|
| In practice, arbitrage is tough. So most market makers
| simulate simultaneity by hedging. For example, if longs
| are accumulating ( _e.g._ due to specialist obligations)
| one might open shorts or buy positional puts or wing it
| by shorting SPYs.
|
| An unhedged market maker is just day trading.
|
| [1] https://www.investopedia.com/terms/m/marketmaker.asp#
| what-is...
| hhmc wrote:
| > i.e. buying at the bid and selling at the offer.
|
| Really they _quote_ simultaneously the bid and offer
| (although there will be times when they do only one or
| neither).
|
| Saying they simultaneously buy/sell is wrong/confusing.
| JumpCrisscross wrote:
| > _Saying they simultaneously buy /sell is
| wrong/confusing_
|
| That wasn't claimed. What was said is the _archetype_ is
| simultaneity. That is 100% accurate for how the term
| "market maker" has been used, globally, since at least
| 1999. (Pre-GLB /LTCM and post-ECN, the term was used more
| broadly.)
|
| Drift from simultaneity incurs cost and risk. Those costs
| and risks must be managed. If you aren't thinking in
| those terms, you aren't market making.
|
| Zillow's downfall mirrors that of the money-centre banks
| in securities dealing post-GLB leading up to the crisis.
| What does and does not constitute market making, which is
| risky but less so than leveraged day trading, was a huge
| area of policy concern. When non MMs think of themselves
| as market makers, there is a predictable set of risks
| they get downed by. Zillow, like so many others, fell
| prey to that misconception. (There is loose analogy in
| the ABS markets, where banks holding inventory of
| esoteric products, either badly hedged or hedged with a
| busted counterparty, got hosed.)
| hhmc wrote:
| You can't garauntee your (bid/ask) resting orders are
| executed against in the same epsilonic time window, nor
| would you want to. No market making practioners would
| think in these terms.
| kgwgk wrote:
| > Drift from simultaneity incurs cost and risk. Those
| costs and risks must be managed.
|
| That's the point of being a market maker. Managing those
| costs and risks well enough to make money from the
| spread.
| faizshah wrote:
| Theres a good video here from a british hedge fund manager on
| why zillows real estate market making doesn't make sense:
| https://youtu.be/eDc4saE5m9k
|
| The main insights are that market makers hold assets for a
| short period of time making money on the spread between
| buyers and sellers offers. Zillow had to hold on to houses
| for a long time and was speculating that the houses would be
| worth more in the future which is not market making.
| opportune wrote:
| I don't think it's just that they had a poor model, but the
| combination of that and adverse selection.
|
| If you pledge to purchase at the Zestimate then people who
| reasonably think they can get more than the Zestimate on the
| open market don't have an incentive to sell their house to
| Zillow (besides convenience). But people who think the
| Zestimate is an over estimate will of course sell to Zillow. So
| instead of a normal distribution of actual value:estimated
| value you end up with a skew towards the end where the estimate
| is over the actual value.
|
| Trading housing is very different from normal market making
| because houses are not fungible commodities like most
| securities are. For most entities trading securities at low
| frequency it does not really matter whether a market maker
| skims off a few pennies on their trade; it's worth it for the
| liquidity. Houses are less liquid (because they are non
| fungible) so the liquidity is more valuable, but the price
| improvement routing around a MM can also be many percentage
| points of a trade because there are not only so many factors
| affecting their valuation, but also just chance and random
| noise (bidding war, a particular buyer falling in love with the
| property, not-price-conscious buyers).
| [deleted]
| perl4ever wrote:
| >adverse selection
|
| According to Matt Levine's recent column, while you might
| think that, it wasn't what sunk them in practice. Bidding low
| in fact worked; it just was inherently limited in scale,
| which is why they switched to bidding higher. Unfortunately,
| being wrong in the other direction is very bad.
|
| "I know, I know, the traders are saying: "No, this is stupid,
| your algorithms will not be 100% precise, some of your
| 'lowball' bids will in fact be too high, and those will be
| the ones that sellers accept. You'll get adverse selection
| and end up losing money." But that was not Zillow's actual
| experience in the first quarter! The actual experience is
| presumably that _some_ people accidentally got too-high bids,
| realized they were good and accepted them, but _mostly_
| Zillow sent too-low bids to everyone, and some people, for
| whatever irrational reason -- market ignorance or financial
| necessity or laziness or whatever -- accepted the too-low
| bids. The general point is that there is no reason at all to
| think that the people on the other side of these trades from
| Zillow are generally _better informed_ than Zillow is. Sure
| they know more about their houses than Zillow does, but
| Zillow knows more about the market, and has more money "
|
| "If you systematically bid too low, you will not do many
| trades, but you will make a lot of money on each trade. If
| you systematically bid too high, you will lose money on each
| trade, and also you will do a whole ton of trades. This is
| much worse!"
| intuitionist wrote:
| I think the question of fungibility comes into play here,
| too. If I'm a HFT and I accidentally post a too-high bid
| for Anacott Steel then there are well-capitalized players
| in a position to sell me a whole lot of Anacott until I
| lower the bid. (They may even be other HFTs who can naked
| short it to me.) But if I'm an iBuyer and post a too-high
| bid for 742 Evergreen Terrace, only the Simpson family can
| hit that bid, and only the one time. If I'm
| _systematically_ overbidding, then that's bad, but not
| every counterparty is informed enough to take advantage (or
| willing to stomach the considerable transaction costs), and
| there's not a well-capitalized player to step in and
| arbitrage away the difference.
| bee_rider wrote:
| I wonder -- does it really matter if the previous homeowner
| is more informed than Zillow? For things like "annoying
| neighbor" or other hard to quantify/quickly detect
| annoyances, the buyer doesn't know about those things
| either, so I guess the information asymmetry is almost 100%
| in Zillow's favor, right?
| notahacker wrote:
| The buyer might not realise about the annoying neighbour
| (unless the most annoying thing about the neighbour is
| the mess they leave everywhere) but will definitely pick
| up on things that Zillow's algorithm doesn't.
| mistrial9 wrote:
| no - because machine data of the deal is not complete,
| therefore cannot be represented in the models. As any
| computer-vision researcher knows, the code sometimes does
| not see what is "obvious" to almost any person.
| lazide wrote:
| If you bid low, almost no one will take the opposite side
| of the deal, so your overall deal flow is low and total
| profit is low (even if margins are high).
|
| If you 'open up' the flood gates on the other end, then yes
| you'll do a lot of deal flow - Buyers sense a sucker - and
| open up a lot of opportunities for matches. It just so
| happens you're also losing your shirt.
|
| It's easy to 'make money' (close deals) by giving money to
| people, and losing money in the actual business.
| martincmartin wrote:
| _[W]hy couldn 't you serve as a market-maker for homes at a
| large scale, especially with the unique insights Zillow could
| have based on their datasets._
|
| Indeed, I believe this is what OpenDoor does. From The
| Economist article [1],
|
| "They [OpenDoor] charge a fee for the services they provide:
| buying and selling homes immediately, with zero fuss. The quick
| in-and-out makes them more like marketmakers than property
| investors, who buy to hold.
|
| ...
|
| "A former Zillow employee told Business Insider that management
| had been hellbent on catching up with Opendoor, the front-
| runner. In order to compete, the employee alleged, the company
| pushed to offer generous deals to potential clients. It called
| this "Project Ketchup". Now it has its own fake blood on its
| hands."
|
| [1] https://www.economist.com/finance-and-
| economics/2021/11/13/a...
| SteveGerencser wrote:
| Or a house full of cats. I had a 'cat lady' friend who
| struggled to sell her home because she had 13 cats. 13 'indoor'
| cats. Even at a great price the house would not sell. Enter the
| wonderful folks at Zillow that bought her house based purely on
| the numbers. Last I heard they still hadn't been able to move
| that house at any price.
| zionic wrote:
| Toxoplasmosis is a scary thing.
| goldenkey wrote:
| Indoor cats don't magically get diseases. Just like an
| indoor pet bat isn't going to magically contract rabies.
| They might if you are letting them out to go roam the
| terrain. I'm really tired of these silly perpetuated
| mythologies.
| erikpukinskis wrote:
| How can an indoor cat ever clean themselves though? It
| doesn't seem like most indoor cat owners bathe the cats,
| do they?
| fwip wrote:
| Cats lick themselves to get clean. They don't bathe even
| when they're outside.
| halfmatthalfcat wrote:
| Not exactly. From what I read it's almost completely benign
| in most humans.
| willcipriano wrote:
| Certainly it isn't a issue after they cats no longer live
| there and it's been cleaned to a reasonable standard. If
| it knocks 20 grand off the price of the house it's worth
| spending 2k to have everything deep cleaned.
| mint2 wrote:
| Cat pee permanently stains flooring and is also extremely
| hard to get the smell out. 2k will not be nearly enough
| if there's extensive cat damage. Wood floors turn black
| with it and must be replaced.
| tartoran wrote:
| Yes, even after extensive renovations cat pee smell can
| persist and some people are bothered by that smell. Im
| one of those people but I do like cats and wouldn't mind
| having cats if they wondered around the neighborhood
| rather than be inside only.
| megablast wrote:
| Killing small animals and birds.
| trhway wrote:
| There are billions of old and ill small animals and birds
| each year who would normally be taken care by various
| predators. Around humans pretty much only cats can do
| that important and necessary job.
|
| Another aspect - rats, a human civilization companion,
| raid nests for eggs thus decimating birds population
| around humans. By controlling rats cats help to maintain
| birds population.
| SilasX wrote:
| Okay even accepting that Zillow made big unforced errors,
| that doesn't sound believable. Like, they don't make the
| offer conditional on someone looking at it in person for red
| flags?
| kube-system wrote:
| As I understand, they were buying sight unseen.
|
| This happens in hot real estate markets. If you don't want
| to miss out or start a bidding war, you have to be the most
| frictionless buyer.
| spamizbad wrote:
| Walking through a house with a high quality N95 mask in a
| hurry you might not notice the cat pee smell - or chalk it
| up to there being 13 cats and once they're gone the smell
| will go away.
| cardosof wrote:
| Would investors pour their money if they were more conservative
| and said something along the lines of "look, this is a very
| complex subject driven by and for humans, we should hire a
| bunch of non-technical people with relevant industry experience
| and try to make some bucks of profit before going full scale
| engineering and AI"?
| skohan wrote:
| Theoretically investors should reward a realistic and well-
| reasoned business plan, and punish hand-wavy science fiction.
| The fact that this is largely not the case (cough metaverse
| cough) is probably an indicator about how frothy the market
| currently is.
| technobabbler wrote:
| Orrr maybe someone in the org could've practiced some basic
| morality and compassion and refrained from further contributing
| to the housing shortage. Just because you can make money being
| a sociopath doesn't mean you should...
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