Using multi-agent simulation to understand trading dynamics of a derivatives market

  • Authors:
  • Alan J. King;Olga Streltchenko;Yelena Yesha

  • Affiliations:
  • IBM Research Division, Mathematical Sciences Department, Thomas. J. Watson Research Center, Yorktown Heights, USA 10598;Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, USA 21250;Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, USA 21250

  • Venue:
  • Annals of Mathematics and Artificial Intelligence
  • Year:
  • 2005

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Abstract

A fundamental question that arises in derivative pricing is why investors trade in a particular derivative at a "fair" price supplied by Arbitrage Pricing Theory (APT). APT establishes a price that is fair for a disinterested investor with a particular set of beliefs about market evolution and attributes trading to differences in those beliefs entertained by the opposite sides of the transaction.We present a model for an investor in a frictionless market that combines investors' incentives in the form of pre-existing liability structures with derivatives pricing procedure tailored for a particular investor. This model enables us to show, through a series of experiments, that investors trade even when their belief structures are identical and accurate.More generally, our study suggests that multi-agent simulation of a financial market can provide a mechanism for conducting experiments that shed light on fundamental properties of the market. As all processes in financial markets (including decision making) become automated, it becomes crucial to have a mechanism by which we can observe the patterns that emerge from a variety of possible investor behaviors. Our simulator, designed as a dealer's market, provides such a mechanism within a certain range of models.