> this strange strategy will maximize your profit. “To me, it was a complete surprise”
It doesn't seem like such a surprise that algorithms that use information about rivals to optimising profit tend to price high.
Consider a small town with two gas stations, you own one. You can set the price (high or low) in the morning and can't change it until the next day. Your goal is to optimise profit for the next 1000 days. On day one you price high (hoping your rival will). But your rival prices low and wins lots of business. On day two, you price high again (hoping your rival will have seen your prices and cooperate). If your rival prices high, you both stay high for the most of the next 998 days (there's some incentive to 'cheat' and price low, but that is easily countered by the rival pricing low). If your rival priced low on day 2, you have to start pricing low too. But occasionally you'll price high to try to 'nudge' your rival to price high to avoid low-low. If they eventually understand, you can both price high for the rest of the 1000 days. Critically, even if stuck at the low-low equilibrium, you'll keep trying to 'nudge' high periodically. The frequency with which you try to 'nudge' will depend on the ratio of profit for high-high vs low-low. If you both make extreme profits when pricing high-high, you have more incentive to 'nudge', but if the difference isn't great, you won't nudge as often.
Seems obvious pricing high will be attempted in proportion to the reward relative to pricing low.
The researchers' conclusion seems reasonable:
> it’s very hard for a regulator to come in and say, ‘These prices feel wrong’”
and
> what can regulators do? Roth admits he doesn’t have an answer.
(i.e. in practical terms, there's no way regulators can police what algorithms sellers use - I can't think of exceptions to this, but perhaps there are some special cases)