Exploring Coevolutionary Dynamics of Competitive Arms-Races Between Infinitely Diverse Heterogenous Adaptive Automated Trading Agents

Nikolay Alexandrov, Dave Cliff, Charlie Figuero

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

Abstract

We report on a series of experiments in which we study the coevolutionary "arms-race'' dynamics among groups of agents that engage in adaptive automated trading in an accurate model of contemporary financial markets. At any one time, every trader in the market is trying to make as much profit as possible given the current distribution of different _other_ trading strategies that it finds itself pitched against in the market; but the distribution of trading strategies and their observable behaviors is constantly changing, and changes in any one trader are driven to some extent by the changes in all the others. Prior studies of co-adaptive dynamics in markets have concentrated on systems where traders can choose one of a small number of fixed pure strategies, and can change their choice occasionally, thereby giving a market with a discrete phase-space, made up of a finite set of possible system states. Here we present first results from two independent sets of experiments, where we use minimal-intelligence trading-agents but in which the space of possible strategies is continuous and hence infinite. Our work reveals that by taking only a small step in the direction of increased realism we move immediately into high-dimensional phase-spaces, which then present difficulties in visualising and understanding the co-adaptive dynamics unfolding within the system. We conclude that further research is required to establish better analytic tools for monitoring activity and progress in co-adapting markets.
Original languageEnglish
Title of host publicationProceedings of the 16th Annual Social Simulation Conference
Publication statusAccepted/In press - 19 Jul 2021
EventThe 16th Annual Social Simulation Conference - Cracow University of Economics, Krakow, Poland
Duration: 20 Sep 202124 Sep 2021
Conference number: 16
https://ssc2021.uek.krakow.pl/

Conference

ConferenceThe 16th Annual Social Simulation Conference
Abbreviated titleSSC2021
CountryPoland
CityKrakow
Period20/09/2124/09/21
Internet address

Keywords

  • Co-evolution
  • Automated Trading
  • market dynamics
  • Agent-based model
  • Financial Markets
  • Agent-based Computational Economics

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