F-trade: an agent-mining symbiont for financial services

  • Authors:
  • Longbing Cao;Chengqi Zhang

  • Affiliations:
  • University of Technology Sydney, Australia;University of Technology Sydney, Australia

  • Venue:
  • Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

The interaction and integration of agent technology and data mining presents prominent benefits to solve some of challenging issues in individual areas. For instance, data mining can enhance agent learning, while agent can benefit data mining with distributed pattern discovery. In this paper, we summarize the main functionalities and features of an agent service and data mining symbiont -- F-Trade. The F-Trade is constructed in Java agent service following the theory of open complex agent systems. We demonstrate the roles of agents in building up the F-Trade, as well as how agents can support data mining. On the other hand, data mining is used to strengthen agents. F-Trade provides flexible and efficient services of trading evidence back-testing, optimization and discovery, as well as plug and play of algorithms, data and system modules for financial trading and surveillance with online connectivity to huge quantities of global market data.