摘要翻译：
在金融市场中，异常交易行为对市场监管和风险管理提出了严峻的挑战。更糟糕的是，一些有经验的交易者结成串通集团，共同操纵某些工具，通过类似的交易行为误导其他投资者，以达到个人利益最大化的异常交易事件日益增多。本文提出了一种检测期货市场工具中隐藏的串通集团的方法，该方法首先计算任意两个合格的有符号订货量统一聚合时间序列之间的相关系数，然后将由相关矩阵构造的多个稀疏加权图中的连通分量组合起来，其中每个相关系数都超过用户指定的阈值。在上海期货交易所的实际订单数据上进行的实验表明，该方法能够有效地检测出可疑的串通集团。一个基于建议方法的工具已在交易所部署，作为期货市场监察和风险管理的试点应用。
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英文标题：
《Detecting Collusive Cliques in Futures Markets Based on Trading
  Behaviors from Real Data》
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作者：
Junjie Wang, Shuigeng Zhou, Jihong Guan
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最新提交年份：
2011
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Trading and Market Microstructure        交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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一级分类：Computer Science        计算机科学
二级分类：Neural and Evolutionary Computing        神经与进化计算
分类描述：Covers neural networks, connectionism, genetic algorithms, artificial life, adaptive behavior. Roughly includes some material in ACM Subject Class C.1.3, I.2.6, I.5.
涵盖神经网络，连接主义，遗传算法，人工生命，自适应行为。大致包括ACM学科类C.1.3、I.2.6、I.5中的一些材料。
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英文摘要：
  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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PDF链接：
https://arxiv.org/pdf/1110.1522