Algorithmic Trading in India's Retail-Dominated Markets: Liquidity, Volatility, and Regulatory Challenges

Abstract

This study investigates algorithmic trading’s (AT) impact on India’s uniquely retail-driven equity markets using high-frequency order-book data from the National Stock Exchange (NSE; 2020–2024). Employing structural breakpoint analysis and instrumental variable techniques, we document three key findings: Retail Algo Regime Shift (2020): Retail algorithmic traders transitioned from passive investors to active liquidity providers, tightening Nifty 50 spreads by 0.42 bps (*p* < 0.01) but amplifying small-cap volatility by 14.7% (*p* = 0.003), revealing a segment-dependent liquidity-volatility tradeoff. UPI’s Exogenous Shock: Unified Payments Interface (UPI) integration precipitated volatility jumps in small-caps, with retail algo herding reaching 2.7 orders/second during price spikes—a novel payment-system-driven microstructure effect. SEBI’s Regulatory Trilemma: The 2022 order cancellation limits (100:1 → 50:1) reduced excessive cancellations by 32% but increased small-cap spreads by 0.11 bps per 10% reduction (2SLS β = 0.11, SE = 0.03), highlighting unintended consequences of uniform regulation. We propose a dynamic tiered framework integrating UPI monitoring and market-quality scores to balance stability, liquidity, and fairness in emerging markets.