Financial market manipulations represent a major threat to trust and market integrity in capital markets. Manipulations contribute to mispricing, market imperfections and an increase in transaction costs for market participants and in costs of capital for issuers. Manipulations are facilitated by increased transaction velocity, speculative trading and abusive usage of new trading technologies, i.e., they are directly linked to financial sector changes that drive financialization. Research at the intersection of financialization and IS might support regulatory authorities and market operators in improving market surveillance and helping to detect fraudulent activities. However, confusing terminology is prevalent on financial markets with respect to different manipulation techniques and their characteristics, which hampers efficient fraud detection. Furthermore, recognizing manipulations is challenging given the large number of information sources and the vast number of trades occurring not least because of high-frequency traders. Therefore, automated market surveillance tools require a comprehensive taxonomy of financial market manipulations as a basis for appropriate configuration. Based on a cluster analysis of SEC litigation releases, a review of the latest market abuse regulation and academic studies, we develop a taxonomy of manipulations that structures and details existing manipulation techniques and reveals how these techniques differ along several dimensions. In a case study, we show how the taxonomy can be utilized to guide the development of appropriate decision support systems for fraud detection.

中文翻译：

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金融市场操纵分类：通过自动欺诈检测在金融化经济中建立信任和市场完整性

金融市场操纵是对资本市场信任和市场诚信的主要威胁。操纵会导致定价错误、市场不完善以及市场参与者交易成本和发行人资本成本的增加。交易速度的提高、投机性交易和新交易技术的滥用促进了操纵，即它们与推动金融化的金融部门变化直接相关。金融化和信息系统交叉点的研究可能会支持监管机构和市场运营商改善市场监督并帮助发现欺诈活动。然而，金融市场上普遍存在关于不同操纵技术及其特征的混淆术语，这阻碍了有效的欺诈检测。此外，鉴于大量信息源和大量交易发生，尤其是由于高频交易者，因此识别操纵具有挑战性。因此，自动化市场监控工具需要对金融市场操纵进行全面分类，作为适当配置的基础。基于对 SEC 诉讼发布的集群分析、对最新市场滥用监管和学术研究的回顾，我们开发了一种操纵分类法，该分类法对现有操纵技术进行了结构化和详细说明，并揭示了这些技术在几个方面的不同之处。在一个案例研究中，我们展示了如何利用分类法来指导开发适当的欺诈检测决策支持系统。鉴于大量信息源和大量交易发生，尤其是由于高频交易者，因此识别操纵具有挑战性。因此，自动化市场监控工具需要对金融市场操纵进行全面分类，作为适当配置的基础。基于对 SEC 诉讼发布的集群分析、对最新市场滥用监管和学术研究的回顾，我们开发了一种操纵分类法，该分类法对现有操纵技术进行了结构化和详细说明，并揭示了这些技术在几个方面的不同之处。在一个案例研究中，我们展示了如何利用分类法来指导开发适当的欺诈检测决策支持系统。鉴于大量信息源和大量交易发生，尤其是由于高频交易者，因此识别操纵具有挑战性。因此，自动化市场监控工具需要对金融市场操纵进行全面分类，作为适当配置的基础。基于对 SEC 诉讼发布的集群分析、对最新市场滥用监管和学术研究的回顾，我们开发了一种操纵分类法，该分类法对现有操纵技术进行了结构化和详细说明，并揭示了这些技术在几个方面的不同之处。在一个案例研究中，我们展示了如何利用分类法来指导开发适当的欺诈检测决策支持系统。