Algorithmic trading regulation now centres on broker accountability, audit trails, and investor protection across retail API-based market access.
Algorithmic trading in India has moved from institutionally limited Direct Market Access and co-location to a retail-facing regulatory regime shaped by market manipulation risks, intermediary attribution problems, and investor protection concerns. Early safeguards required broker routing, risk controls, exchange permission, and algorithm identifiers, but flash crashes, co-location controversies, and unregistered retail vendors exposed gaps in enforcement and accountability. SEBI's Innovation Sandbox and Regulatory Sandbox provided controlled testing environments, yet deployment in the live market still requires full compliance. The 2025 framework resolves attribution by making brokers principals and vendors agents, while imposing audit trails, exchange approval, and research analyst obligations for black box strategies. (AI Summary)

Tokenised securities: recognise blockchain records and enable a regulatory sandbox to safely pilot DLT issuance and custody.
Tokenised securities are blockchain-based instruments enabling fractional ownership and programmable rights via smart contracts, offering potential for real time settlement and reduced intermediation. Indian statutes (SCRA, Companies Act, Depositories Act, SEBI Act, IT Act) may apply but currently do not expressly recognise blockchain registries or decentralised registers, creating legal uncertainty around statutory registers, depository roles, cross border compliance, taxation and investor protection. A sequenced approach is advised: statutory recognition of blockchain records, regulator licensing of DLT market infrastructure, and a targeted regulatory sandbox to test issuance, custody, interoperability and smart contract audits. (AI Summary)