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We address the problem of improving bidders' strategies in prior-dependentrevenue-maximizing auctions and introduce a simple and generic method to designnovel bidding strategies if the seller uses past bids to optimize hermechanism. We propose a simple and agnostic strategy, independent of thedistribution of the competition, that is robust to mechanism changes and local(as opposed to global) optimization of e.g. reserve prices by the seller. Thisstrategy guarantees an increase in utility compared to the truthful strategyfor any distribution of the competition. In textbook-style examples, forinstance with uniform [0,1] value distributions and two bidders, thisno-side-information and mechanism-independent strategy yields an enormous 57%increase in buyer utility for lazy second price auctions with monopolyreserves. When the bidder knows the distribution of the highest bid of thecompetition, we show how to optimize the tradeoff between reducing the reserveprice and beating the competition. Our formulation enables to study someimportant robustness properties of the strategies, showing their impact evenwhen the seller is using a data-driven approach to set the reserve prices. Inthis sample-size setting, we prove under what conditions, thresholding biddingstrategies can still improve the buyer's utility. The gist of our approach isto see optimal auctions in practice as a Stackelberg game where the buyer isthe leader, as he is the first one to move (here bid) when the seller is thefollower as she has no prior information on the bidder.

Thresholding at the monopoly price: an agnostic way to improve bidding strategies in revenue-maximizing auctions