We study the problem of mechanism design for a double auction market where multiple buyers and sellers buy and sell a commodity. We design and implement a matching algorithm that maximizes market liquidity, including the number of transactions and buy/sell-volume. We prove that, given the number of matches, the algorithm also maximizes auctioneer's profit. Based on the CAT Tournament (Trading Agent Competition Market Design) platform, we show with experiments that the new matching method not only increases market liquidity but also significantly improves market share and auctioneer's profit in the long term, compared with equilibrium matching, the most commonly used matching method. © 2010 Springer-Verlag.
CITATION STYLE
Zhao, D., Zhang, D., Khan, M., & Perrussel, L. (2010). Maximal matching for double auction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6464 LNAI, pp. 516–525). https://doi.org/10.1007/978-3-642-17432-2_52
Mendeley helps you to discover research relevant for your work.