Discovering the game in auctions

Abstract

Auctions are pervasive in today's society. They provide a variety of markets, ranging from consumer-toconsumer online auctions to government-to-business auctions for telecommunications spectrum licenses. Starting from a set of trading strategies, this article enables a strategic choice by introducing the use of linear programming as a methodology to approximate heuristic payoff tables by normal form games. This method is evaluated on data from auction simulation by applying an evolutionary game theory analysis. The information loss in the normal form approximation is shown to be reasonably small such that the concise normal form representation can be leveraged in order to make strategic decisions in auctions. In particular, a mix of trading strategies that guarantees a certain profit against any population of traders is computed and further applications are indicated.