You might not remember about a year and a half ago when there was a big trend on Tiktok (and other forms of social media) putting Zillow and other firms to task for their homebuying programs. The financial press picked up on this story quickly, firstly pointing to the scandal and then, after the story ended, hinting that these influencers stopped Zillow (Z) and other firms from profiting off of their inside information that is causing them to manipulate home prices, cause prices to rise, and make homes unafforadable for average Americans.
It’s a compelling and familiar story: insiders in big firms use clout to get an advantage on the little guy, and the evil banks are facilitating the near-fraud right in front of us while regulators are asleep at the wheel.
It’s also entirely wrong.
Zillow’s homebuyer program shut down in late 2021 as did similar programs at other well positioned real estate firms, but the influencers were targeting Zillow the most. Before it was shut, the influencers made their accusations very clear, and Nevadan Sean Gotcher, a real estate agent, earned the most attention by squarely attacking Zillow for manipulating the housing market.
Zillow also lost hundreds of millions of dollars due to the program. The accusation that Zillow used its wealth of real estate data to corner real estate markets, earn a profit, and price homes out of the reach of middle class buyers is demonstrably false; Zillow lost money on the program, if it attempted to corner any real estate market it failed, and there are a growing number of stories (heavily researched in detail by many sell-side analysts covering the company over the last year) of the opposite happening—Zillow’s approach to the market resulted in the company backing itself into a corner, instead of cornering a market.
The iBuyer fad is dead and it did not work, but there is a lot to learn from that fact.
The most obvious lesson is that financial advice on social media is bad, and financial illiteracy is rampant. Gotcher’s factually incorrect accusations could easily have lead one to buy Zillow stock at the time; that same stock is down 55% from then, with most of those losses happening in the last few months of 2021 before the broader market fell. This is much worse than the Nasdaq 100’s 25% fall over the same time period.
The second lesson is less intuitive, but it is arguably more important both for individuals and for the theory and practice of finance. Theoretically, in any market superior information provides an advantage that buyers or sellers can use to get a profit. Information, within capital markets, is fungible and can be exchanges for money in a probabilistic if not mechanistic way that can be modeled to produce long-term wins that compound on one another.
Sound complicated? If you’ve taken a few intro to finance and econ classes, absolutely not—but if you haven’t, that paragraph might sound like a foreign language. And that’s just the first step into unpacking the lessons from the iBuyers’ big losses.
The value of information within any market is limited, and different pieces of information have different values. Let’s say, for example, that I know that a trend of wearing purple shoes has taken hold of City A—and no one else has noticed this trend has begun. I can buy all of the purple shoes in the market and win big, right?
That’s the theory, and with all of the information in this hypothetical, that theory would hold. But what if there are unknown variables—or even known variables whose value is unknown? For example, what if I try to capitalize on this trend and expand my shoe selling business from City A to City B—but City B is City A’s rival, and will actively mock anyone following trends from City A. If I don’t have that information, my purple shoe selling business will go in the red.
This is most likely the problem that Zillow and other iBuyers faced, although the jury is still out on this one. Perhaps real estate markets are hyperlocal, and what works in one part of one small neighborhood won’t work one block down—and Zillow’s informational edge did not have that level of granularity. Possibly, Zillow instead could not solve the observer problem—namely that the existence of its homebuying problem changed market dynamics so that the assumptions built on their informational edge no longer works. Or a third possibility is that there are so many dimensions to real estate markets, and so many significant variables are either random or arbitrary, that predicting housing markets with the most robust data sets and data analysis currently available is impossible (and it may always be that way).
We don’t know, and we need to know before understanding both real estate markets and iBuyers’ future in them. But that takes a lot more work than what it takes to produce an error-filled short video on Tiktok that can cause people to lose their entire life savings.
