111–120 of 386 posts
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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).
(Straight) PVC is not acceptable for hot water supply lines.
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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.
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.
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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…
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.
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.
> 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?
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> 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 m…
> 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…
> 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…
Good tweetstorms with technical explanations on how that happened:
https://twitter.com/macrocephalopod/status/14558873523715973...
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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.
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 qu…
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.