Robu, Valentin, Vetsikas, Ioannis, Gerding, Enrico and Jennings, Nick
Addressing the Exposure Problem of Bidding Agents Using Flexibly Priced Options.
At 19th European Conference on Artificial Intelligence (ECAI), Lisbon, Portugal,
In this paper we present a novel option pricing mechanism for reducing the exposure problem encountered by bidding agents with complementary valuations when participating in sequential, second-price auction markets. Existing option pricing models have two main drawbacks: they either apply fixed exercise prices, which may deter bidders with low valuations, thereby decreasing allocative efficiency, or options are offered for free, in which case bidders are less likely to exercise them, thereby reducing seller revenues. Our novel mechanism with flexibly priced options addresses these problems by calculating the exercise price as well as the option price based on the bids received during an auction. For this novel model, which extends and encompasses all the previous models examined, we derive the optimal strategies for a bidding agent with complementary preferences. Finally, we use these strategies to empirically evaluate the proposed option mechanism and compare it to existing ones, both in terms of the seller revenue and the social welfare. We show that our new mechanism achieves higher market efficiency compared to having no options and free options, while achieving higher revenues for the seller than any existing option mechanism.
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