Market Microstructure Patterns Powering Trading and Surveillance Agents

نویسندگان

  • Longbing Cao
  • Yuming Ou
چکیده

Market Surveillance plays important mechanism roles in constructing market models. From data analysis perspective, we view it valuable for smart trading in designing legal and profitable trading strategies and smart regulation in maintaining market integrity, transparency and fairness. The existing trading pattern analysis only focuses on interday data which discloses explicit and high-level market dynamics. In the mean time, the existing market surveillance systems available from large exchanges are facing crucial challenges of diversified, dynamic, distributed and cyber-based misuse, mis-disclosure and misdealing of information, announcement and orders in one market or crossing multiple markets. Therefore, there is a crucial need to develop innovative and workable methods for smart trading and surveillance. To deal with such issues, we propose the innovative concept microstructure pattern analysis and corresponding approaches in this paper. Microstructure pattern analysis studies trading behaviour patterns of traders in market microstructure data by utilizing market microstructure knowledge. The identified market microstructure patterns are then used for powering market trading and surveillance agents for automatically detecting/designing profitable and legal trading strategies or monitoring abnormal market dynamics and trader’s behaviour. Such trading/surveillance agent-driven market trading/surveillance systems can greatly enhance the analytical, discovery and decision-support capability of market trading/surveillance than the current predefined rule/alert-based systems.

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عنوان ژورنال:
  • J. UCS

دوره 14  شماره 

صفحات  -

تاریخ انتشار 2008