Shadow trading detection: A graph-based surveillance approach

IF 6.9 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters Pub Date : 2025-09-30 DOI:10.1016/j.frl.2025.108524

Alexis Stenfors , Ting Guo , Boyu Li , Kaveesha Hewage , Peter Mere , Fang Chen

引用次数: 0

Abstract

This paper introduces a novel graph-based deep learning framework for detecting risks of shadow trading, an emerging form of insider trading where material nonpublic information is used to trade securities of economically related but distinct companies. Motivated by the landmark SEC v. Panuwat case in April 2024, the study proposes an Adaptive Market Graph Intelligence Network (AMGIN) that integrates both industry relationships (e.g., sectoral ties, inter-organizational connections) and dynamic market behaviors (e.g., short/long-term price co-movements) to uncover hidden trading patterns. By modeling the financial market as a spatio-temporal graph, the framework captures complex interdependencies that traditional statistical methods often overlook. Empirical evaluation using US equity market data demonstrates AMGIN’s superior ability to identify subtle, non-obvious relationships indicative of shadow trading, offering regulators a scalable, data-driven tool for modern market surveillance.

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影子交易检测：基于图形的监视方法

本文介绍了一种新的基于图的深度学习框架，用于检测影子交易的风险，影子交易是一种新兴的内幕交易形式，在这种交易中，重要的非公开信息被用来交易经济上相关但不同公司的证券。受2024年4月具有里程碑意义的SEC诉Panuwat案的启发，该研究提出了一个自适应市场图智能网络（AMGIN），该网络整合了行业关系（例如，部门关系，组织间联系）和动态市场行为（例如，短期/长期价格协同运动），以发现隐藏的交易模式。通过将金融市场建模为一个时空图，该框架捕获了传统统计方法经常忽略的复杂的相互依赖关系。利用美国股市数据进行的实证评估表明，AMGIN在识别暗示影子交易的微妙、不明显关系方面具有卓越的能力，为监管机构提供了一种可扩展的、数据驱动的现代市场监管工具。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Finance Research Letters BUSINESS, FINANCE-

CiteScore

11.10

自引率

14.40%

发文量

863

期刊介绍： Finance Research Letters welcomes submissions across all areas of finance, aiming for rapid publication of significant new findings. The journal particularly encourages papers that provide insight into the replicability of established results, examine the cross-national applicability of previous findings, challenge existing methodologies, or demonstrate methodological contingencies. Papers are invited in the following areas: Actuarial studies Alternative investments Asset Pricing Bankruptcy and liquidation Banks and other Depository Institutions Behavioral and experimental finance Bibliometric and Scientometric studies of finance Capital budgeting and corporate investment Capital markets and accounting Capital structure and payout policy Commodities Contagion, crises and interdependence Corporate governance Credit and fixed income markets and instruments Derivatives Emerging markets Energy Finance and Energy Markets Financial Econometrics Financial History Financial intermediation and money markets Financial markets and marketplaces Financial Mathematics and Econophysics Financial Regulation and Law Forecasting Frontier market studies International Finance Market efficiency, event studies Mergers, acquisitions and the market for corporate control Micro Finance Institutions Microstructure Non-bank Financial Institutions Personal Finance Portfolio choice and investing Real estate finance and investing Risk SME, Family and Entrepreneurial Finance