Low-balling according to their own estimate (Zestimate) with imperfect knowledge. If this Zestimate overvalues a house, but the iBuyers assume “we are low-balling anyways,” they may find themselves in an iBidding war ending in the winner’s curse: whoever pays the most for the overvalued house wins.
Not a problem though right? They overvalue some, undervalue others, it evens out. But, as the article points out, the nature of this algorithmic buying is that the iBuyers will only - or at least predominantly - end up with the houses they overpaid for or got only a slightly good deal on because many sellers will be willing to take longer for a better deal. The end result is very thin margins or, as seen with Zillow, substantial losses as they hold a lot of lemons.
Because they want to make money. Which they can’t by buying for X and then selling for X.
But is asking price "market" price. As in does the seller price a 10-20% premium calculating this. Always easier to negotiate down than up.
But iBuyers are always low-balling. They are bidding under the asking price with an all-cash offer that they hope will make up in speed and ease what it lacks in price.
> It's not that uncommon to see nearly entire neighborhoods converted to short term rentals now in some areas where they're still legal. Hearing that really depressed me.
I lived in Lake Tahoe for ten years before AirBnB was a thing and three out of four homes there were absentee owners that only used them a few weeks a year. It made it a very hard place for small businesses to stay afloat. Most visitors stayed at big hotels or paid huge premiums for ad hoc "cabin rentals" through local realtors. The most depressing part was Halloween - kids hiking up and down steep hills to mostly empty houses. :)