摘要：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 traders 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.
关键词：agents, data mining, market microstructure pattern, market surveillance
