Ricki Heicklen on Bayes Shammai

In the wheelbarrow examples, the thing I'm describing is winner's curse—my point is that the winning bidder overpays relative to the true value, while the median bidder neither profits nor loses. (A bidder whose model is mistaken such that they substantially underbid profits $0, like the median winner). That is, there's an asymmetry between your PnL when your model is correct and when your model is incorrect. The point is: conditional on winning the auction, you outbid every other person. You are at the extreme end of bids. The price you bid ($180) is a combination of your model of the wheelbarrow's price ($200, with some uncertainty) and the amount of edge you ask for on account of winner's curse concerns (10%, or $20). If you are the winner, it means everybody else either models the price as lower, or asks for greater edge, or (most likely) some blend of the two. If it's just because they're asking for more edge, your bid may still be profitable. But it's likely some combination of the two, and their price models all (or almost all) being lower than yours should cause you to update that the true value of the wheelbarrow is lower than you'd previously estimated. The field one is about the danger of sending market orders. If you send a market order, you might get filled at the fair value, or you might get filled at a bad price. You're never going to get filled at a better price than fair. Instead of sending a market order, you should specify an upper limit, since there is some true upper limit above which you wouldn't want to pay for the item.