Detecting Collusive Cliques in Futures Markets Based on Trading Behaviors from Real Data

Details Detecting Collusive Cliques in Futures Markets Based on Trading Behaviors from Real Data Detecting Collusive Cliques in Futures Markets Based on Trading Behaviors from Real Data

2011-10-07

arxiv.org/abs/1110.1522v1

Economy

Quantitative Finance

Trading and Market Microstructure

13 pages, 5 figures and 3 tables. submitted to Neurocomputing

Scientific paper

In financial markets, abnormal trading behaviors pose a serious challenge to market surveillance and risk management. What is worse, there is an increasing emergence of abnormal trading events that some experienced traders constitute a collusive clique and collaborate to manipulate some instruments, thus mislead other investors by applying similar trading behaviors for maximizing their personal benefits. In this paper, a method is proposed to detect the hidden collusive cliques involved in an instrument of future markets by first calculating the correlation coefficient between any two eligible unified aggregated time series of signed order volume, and then combining the connected components from multiple sparsified weighted graphs constructed by using the correlation matrices where each correlation coefficient is over a user-specified threshold. Experiments conducted on real order data from the Shanghai Futures Exchange show that the proposed method can effectively detect suspect collusive cliques. A tool based on the proposed method has been deployed in the exchange as a pilot application for futures market surveillance and risk management.

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