Name: S.B.Yadav & Aruna Baswaraj Saganali
Country: India

Year: 2025
Volume: Volume-12, Issue-2 (July-December)
Page Number: 351-360
DOI: https://doi.org/10.5281/zenodo.18835302

ABSTRACT
Algorithmic trading has fundamentally reshaped modern financial markets by increasing execution speed, enhancing liquidity, and improving price discovery. However, the proliferation of automated and high-frequency trading strategies has also introduced significant systemic, operational, and market integrity risks. In response, jurisdictions worldwide have developed regulatory frameworks aimed at mitigating these risks while preserving innovation and competitiveness. This paper undertakes a comparative analysis of regulatory approaches governing algorithmic trading in the United States, the European Union, the United Kingdom, India, and Singapore. It evaluates differences in licensing regimes, pre-trade risk controls, testing requirements, surveillance mechanisms, enforcement styles, and transparency obligations. The study finds that while the European Union adopts a highly prescriptive, ex-ante regulatory model under MiFID II, the United States relies more heavily on enforcement-driven oversight through agencies such as the Securities and Exchange Commission and the Commodity Futures Trading Commission. Emerging markets, including India and Singapore, emphasize preventive controls and technology risk management under centralized supervision by the Securities and Exchange Board of India and the Monetary Authority of Singapore, respectively. The paper argues that regulatory divergence creates potential arbitrage risks in increasingly interconnected markets and highlights the need for greater international coordination, particularly in light of AI-driven trading and cross-border digital asset markets.

Keywords Algorithmic Trading, High-Frequency Trading, Financial Regulation, Market Microstructure, MiFID II, SEC, ESMA, SEBI, MAS, Regulatory Arbitrage, Systemic Risk, Cross-Border Supervision.