Opendoor losses stem from unprecedented market conditions, says CEO Eric Wu
Rate hikes slowed demand from a wide-open firehose to a trickle faster than the company or its algorithms could predict.
Key points:
- The speed of the market slowdown caught the iBuyer off guard, leading to losses and layoffs in Q3.
- Wu said sharply rising interest rates and plummeting demand are “outlier” events and “nearly impossible to predict.”
- There was no historic precedent to help companies foresee the direction of the market.
The breathtaking speed of this year's real estate slowdown caught even Opendoor's vaunted algorithm off guard, CEO Eric Wu acknowledged in an interview on the Stratechery podcast.
"We've seen a once-in-a-40-year move in home prices, on top of a move in velocity that we've never actually seen in housing," Wu told host Ben Thompson. "The market moved from positive 7% appreciation per quarter to negative 1% in three months, and that is actually steeper than what happened during the GFC (Great Financial Crisis)."
Opendoor suffered $211 million in adjusted third-quarter losses and laid off 550 employees, or 18% of its workforce as a result.
The company's algorithms were accurate in estimating home values in the moment, but no one at the company saw the deceleration in prices coming at the pace they did, Wu said in the podcast. "We did have models that said that's possible, but we didn't say it was likely."
Wu acknowledged that rising interest rates weren't unexpected, given inflation and warnings from the Federal Reserve. But the speed of the hikes and the impacts on buyers were more dramatic than forecast, he said.
"We had already started to widen spreads in anticipation for rates to rise," Wu said. "Now, they rose slightly faster than we anticipated, and then the home prices moved dramatically because demand just paused. There was uncertainty about where the rates would end up and buyers just sat out."
That sudden drop in demand "was a shift that we hadn't seen before in any of the back testing and any of the data that we analyzed from previous home price depreciation, even the GFC," Wu said. "And so I would say that from a macro standpoint, by definition outlier events are nearly impossible to predict. And what has to happen for us … is that we have to build to widen spreads or decrease spreads based on our view of volatility and risk. But the platform itself has to be able to service customers in any situation."