Research on Algorithmic Regulation of Market Manipulation in Algorithmic Trading

随着科技发展，程序化交易在金融市场占比迅速扩张。它具有非结构性、不可解释性、偏置性和非标准化特征，带来了如动量点火、分层报价、反向操作、嗅探试单、报价填充等新型操纵市场行为。目前，其监管存在主观要件认定争议、算法共谋与黑箱导致监管套利、个别风险易系统化、Alpha收益消失且缺乏有效监测标准等问题。针对这些，我国应完善操纵行为监管法规，推进监管重心前移，优化监管职权配置，建立有效检测模型和智能检测标准。With the advancement of technology, programmatic trading has rapidly expanded its share in financial markets. Characterized by non-structural, unexplainable, biased, and non-standardized features, it has introduced novel market manipulation behaviors such as momentum ignition, layered quoting, reverse operations, sniffing and test orders, and quote stuffing. Current regulatory frameworks face challenges, including controversies over the determination of subjective elements, algorithmic collusion and regulatory arbitrage due to black-box algorithms, systemic risks from individual vulnerabilities, the disappearance of Alpha returns, and a lack of effective monitoring standards. To address these issues, China should improve regulatory laws on manipulative behaviors, shift regulatory focus to preemptive measures, optimize the allocation of regulatory authority, and establish robust detection models and intelligent monitoring criteria.