Designing Bidding Strategies in Sequential Auctions for Risk Averse Agents: A Theoretical and Experimental Investigation

Abstract

Designing efficient bidding strategies for sequential auctions remains an important, open problem area in agent-mediated electronic markets. In existing literature, a variety of bidding strategies have been proposed and have been shown to perform with increasing degrees of efficiency. However, most of strategies proposed so far do not explicitly model bidders’ attitudes towards risk which, in mainstream economic literature, is considered an essential attribute in modeling agent preferences and decision making under uncertainty. This paper studies the effect that risk profiles (modeled through the standard Arrow-Pratt risk aversion measure), have on the bidders’ strategies in sequential auctions.

We model the sequential bidding decision process as an MDP and we analyze, for a category of expectations of future price distributions, the effect that a bidder’s risk aversion profile has on her decision-theoretic optimal bidding policy. This analysis is performed separately for the case of first-price and second-price sequential auctions. Next, we simulate the above strategies, and we study the effect that an agent’s risk aversion has on the chances of winning the desired items. We conclude the paper with an experimental study of how the presence of risk-averse bidders in a market affects allocation efficiency and expected seller revenue.