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A Binary Particle Swarm Optimization Algorithm for a Double Auction Market

In: Artificial Markets Modeling

Author

Listed:
  • Calogero Vetro

    (University of Palermo)

  • Domenico Tegolo

    (University of Palermo)

Abstract

In this paper, we shall show the design of a multi-unit double auction (MDA) market. It should be enough robust, flexible and sufficiently efficient in facilitating exchanges. In a MDA market, sellers and buyers submit respectively asks and bids. A trade is made if a buyers bid exceeds a sellers ask. A sellers ask may match several buyers bids and a buyers bid may satisfy several sellers asks. The trading rule of a market defines the organization, information exchange process, trading procedure and clearance rules of the market. The mechanism is announced before the opening of the market so that every agent knows how the market will operate in advance. These autonomous agents pursue their own interests maximizing their own utilities. Therefore, we can view our market as a multi-agent system where the market mechanism defines the structure and rules of the environment in which agents will play the market game. An efficient market maximizes the total profit obtained by all participating agents (Fudenberg and Tirole, 1991). However, voluminous game theory literature focuses on auction markets. Satterthwaite and Williams (1989) were among the early researchers studying double auction markets. They designed a single-unit double auction (SDA) market where they eliminated the strategic behavior on the sellers side. McAfee (1992) allowed strategic behavior on both sides of a SDA market and required a market maker to balance the budget.

Suggested Citation

  • Calogero Vetro & Domenico Tegolo, 2007. "A Binary Particle Swarm Optimization Algorithm for a Double Auction Market," Lecture Notes in Economics and Mathematical Systems, in: Andrea Consiglio (ed.), Artificial Markets Modeling, chapter 18, pages 249-257, Springer.
    • Handle: RePEc:spr:lnechp:978-3-540-73135-1_18
    DOI: 10.1007/978-3-540-73135-1_18
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