--- title: "Retail Algo Rules in India: A Compliant Design" description: "SEBI's retail algo framework in force from 1 Apr 2026 as a design: the ten orders a second line, static IP, tagging, kill switch and your own risk layer." source_url: "https://www.rupeecase.com/learn/path-19/module-19-5-building-a-compliant-algo" --- [Path 19 5 of 16](/learn/path-19/)Building a compliant retail algo[Next 19.6](/learn/path-19/module-19-6-backtesting-options) From 1 Apr 2026 SEBI's retail algo framework applies to every stock broker. A retail algo can send up to ten orders a second to an exchange without registering, and that ceiling is 600 orders a minute and 2,25,000 in a six and a quarter hour session. No hand clicks that fast. Under the rules, every order a program sends through the broker's API is an algo order whatever its rate: tagged, traced to a key and a static IP, risk checked by the broker and open to a kill switch. This lesson takes the framework as the circulars set it and turns it into an architecture. It is education about design and rules. It is not a strategy to run, not a view on any contract and not a list of vendors. 3By the end you can 1. Say who does what under SEBI's retail algo framework and what changes at the order rate threshold. 2. List what the connection needs: static IP, client key, OAuth, two factor login, daily logout and tagging. 3. Add the risk layer the framework leaves to you, and see in a model why size decides ruin. Watch in the terminal: what sets Low to Very High? A short tutorial on sample data. ## The idea, plainly ### Who does what under the framework? The circular of 4 Feb 2025 splits the roles. The investor writes or buys the logic. The broker is the principal: it holds the API, answers for every order that comes through it and handles the grievances. An algo provider is the broker's agent and must be empanelled with the exchanges. The exchange registers algos, tags orders, runs surveillance and keeps a kill switch for orders from one algo identifier. The circular describes that switch as the last level of defence against an algo malfunction, expected to halt trading on pre-defined conditions. ### What changes at the ten orders a second line? Every order that reaches the broker through a client's API is an algo order and carries an exchange tag. The line decides registration, nothing else. The NSE standards of 5 May 2025 set the threshold, "not exceeding 10 orders per second" per exchange and segment to begin with, applied on the calendar second of the broker's server, and the exchange may change it after notice. A broker may set a lower limit for a client. * **At or below the line:** the investor's own algo runs through the broker's API without registration. Its orders carry a generic tag from the exchange. Above the line the broker rejects the excess. * **Above the line:** the algo is registered with each exchange where it will trade, through the broker. The exchange issues a registration ID and the orders carry it. The same registered algo may serve the investor's family: self, spouse, dependent children and dependent parents, and no other investor. * **For others:** giving an algo to people outside the family is the provider route, which needs exchange empanelment. A black box, whose logic the user cannot see, also needs the provider to register as a research analyst and keep a research report for each algo. A change of logic makes it a fresh algo. Watch in the terminal: why did my broker refuse an order? A short tutorial on sample data. ### What does the connection itself need? The broker may allow no open API. Access is through an API key specific to the client and a static IP the broker has whitelisted, with OAuth and two factor authentication. The NSE standards add that a client may give one primary and one secondary static IP, may change them no more than once in a calendar week, and shares an IP with another client only inside one family. A client may hold several API keys, but unregistered algos run only through one predefined key. API sessions are logged out every day before the next trading day. Algo orders may not be market orders. The broker keeps an audit trail for at least five years and is liable for every order through its systems. Every order passes your risk layer, the broker's checks and the exchange The parts of a retail algo built under SEBI's circular of 4 Feb 2025 and the NSE standards of 5 May 2025. A rule diagram with no market figures. The first two boxes are the investor's own design, the rest are set by the framework. Source: SEBI circular of 4 Feb 2025; NSE circular NSE/INVG/67858 of 5 May 2025. As of 17 Oct 2026. ### When did all this apply? The dates moved more than once, so name the circular a page relies on. The circular was due to apply from 1 Aug 2025. NSE issued its detailed operational modalities on 22 Jul 2025 and SEBI moved the start to 1 Oct 2025 on 29 Jul 2025. A circular of 30 Sep 2025 let brokers who were ready go live on 1 Oct 2025 and gave the others three milestones, with those missing them barred from onboarding new API algo clients from 5 Jan 2026. From 1 Apr 2026 the framework applies to all stock brokers. Exchanges update operational details by circular, so check the NSE page before relying on one. The retail algo framework applied to all brokers from 1 April 2026 1. 4 Feb 2025**SEBI circular**The framework for safer retail participation in algo trading 2. 5 May 2025**NSE standards**Threshold, static IP, API keys and tagging set out 3. 29 Jul 2025**Start moved to 1 Oct 2025**SEBI extends the implementation date 4. 30 Sep 2025**Glide path**Ready brokers go live, others follow three milestones to 3 Jan 2026 5. 5 Jan 2026**Onboarding bar**Brokers that missed the milestones cannot onboard new API algo clients 6. 1 Apr 2026**All brokers**The framework applies to every stock broker Dates of the SEBI circulars and NSE standards that set the framework. A record of rule dates with no market figures. Later exchange circulars change operational details. Source: SEBI circulars of 4 Feb, 29 Jul and 30 Sep 2025; NSE circular of 5 May 2025. As of 17 Oct 2026. The term this section turns on: Static IP From the module glossary; every term is in the Learn glossary too. Source: Module 19.5, Building a compliant retail algo. ### What should the investor's own layer add? The framework puts risk management on the broker and the kill switch on the exchange. Neither knows your intention. A design that follows the rules still needs its own guards, written before the first live order: a size limit per order, a loss limit per day that stops the program, a rate limiter set well under the threshold, a guard against sending the same order twice, a check of positions against the broker's at each start, and a log of every order and every rejection. The daily logout means the program must log in again each day and must not trade on a stale session. ### What does one trading day look like? Before the open the program logs in again, because its session was logged out the evening before, and it checks that the static IP the broker has mapped is still the one it runs from. It reads its positions and open orders from the broker and compares them with its own records. It starts with the rate limiter live and the loss limit armed. Each order goes out with a limit price and never as a market order, and every response, fill and rejection is written to a log with a time stamp. If the loss limit trips or the data feed fails, the program cancels what it can, stops sending and tells its owner. After the close it reconciles again. Only the login, the static IP and the order type come from the circulars. The rest is practice, and it turns the broker's audit trail into a record the owner can read too. Two terms to hold on to from 19.5 From the module glossary. Source: Module 19.5, Building a compliant retail algo. ## Worked example: why a risk layer sets the size Take a rule with an assumed edge, made up for the model and not found in any market: it wins 55% of the time and each win equals each loss. The Kelly fraction of such a rule is 10% of the account. The model below runs 250 trades on 2,000 simulated paths and counts how often the account falls by half at four sizes of risk per trade. Model, not market data The same rule rarely ruins at a small size and ruins two paths in five at a large one A model of one assumed rule, not a strategy and not market data. Only the risk per trade changes between the bars. Inputs: win rate 55.0%, average win 1.00 times the average loss, 2% of the account risked on each trade, ruin at a 50% loss of the starting account, 250 trades, 2,000 simulated paths, seed 1. Source: RupeeCase model, seeded simulation. As of 17 Oct 2026. The maths: rate and ruin Orders in a session = rate x seconds Kelly = p minus (q / b) A session of six and a quarter hours has 22,500 seconds. At ten orders a second that is 2,25,000 orders. The Kelly fraction for win rate p, loss rate q and a win of b times the loss is p less the ratio q over b. With p of 55% and b of one it is 10%. Kelly is a limit, not a target, and it assumes the edge is known exactly. The ruin figures come from the engine's seeded simulation, so the same inputs give the same bars. Read one more paragraph, 82 words At 1% of the account per trade, 0.0% of the paths lose half. At 10%, 41.0% do, with the same rule and the same edge. The framework cannot fix that. It tags the order, checks the margin and can halt the algo. It does not decide the size, and a size that is too large ruins a rule that works as designed. The size is a line in your own risk layer, fixed in the rules file before the first order. ### What about testing and claims? Test on dated data first, as in [the backtest biases module](/learn/path-19/module-19-1-backtest-biases), with the costs of each date. The exchanges run a standard procedure for testing algos and mock sessions, and the NSE FAQ says an individual tech savvy client is not required to join the monthly mock sessions. Claims are a separate rule. SEBI allows only registered advisers, research analysts and empanelled algo providers to state past performance, as risk and return figures verified by a recognised verification agency. That agency has operated since 4 May 2026. A backtest chart posted in a group is not that. ## The common mistake The belief: My algo stays under ten orders a second, so it is outside the rules. The line decides only whether the algo is registered with the exchange. Below it, every order through the API is still an algo order. It still comes from a static IP the broker has whitelisted, through a client key, after OAuth and two factor login, with a daily logout, an exchange tag and a trail the broker keeps for five years, and the broker answers for it. Selling or sharing the algo outside the family is a different step again. Read the circular and the exchange standards, name their dates, and keep your own risk layer. Where this section sits in module 19.5 Sections 1 to 4 of 4; the highlighted one is next. Source: Module 19.5, Building a compliant retail algo. ## Key takeaways * The broker is the principal. The algo provider is its agent. * Ten orders a second per exchange decides registration, not whether the rules apply. * Every API order is tagged. Static IP, client key and two factor login apply. * Algo orders may not be market orders. Sessions log out daily. * The exchange keeps a kill switch. The size limit is yours to design. * Only registered firms may state past performance, as verified figures. Watch in the terminal: what is in each tab? A short tutorial on sample data. **Before you trade.** Derivatives trading carries a high risk of loss. SEBI's study "Profitability of Individual Traders in the Equity Derivatives Segment (FY25 to FY26)" (August 2026) found that 87.7% of individual traders in equity F&O made net losses in FY26, with aggregate net losses of Rs 91,685 crore. [Read the SEBI study](https://www.sebi.gov.in/reports-and-statistics/research/aug-2026/study-profitability-of-individual-traders-in-the-equity-derivatives-segment-fy25-fy26-_103835.html) What does Building a compliant retail algo cover?The framework as the circulars set it, turned into an architecture, with one model of why your own risk layer sets the size. It works through The idea, plainly, Worked example: why a risk layer sets the size, The common mistake, Key takeaways. It is module 19.5 of Path 19, Algo, HFT and Backtesting, about 10 minutes of reading, free. TTry it ## Risk of ruin, on the same example. Win rate, payoff and size, simulated to the chance of losing the account. Dated NSE end of day data, nothing live, no orders. **Risk of ruin**. [Open the risk of ruin](/learn/tools/risk-of-ruin?preset=edge-big-size) AF&O on RupeeCase ## Hedging only, in development F&O at RupeeCase will do one job: protect a portfolio you already own, by a rule published before it runs. No speculation, no naked option selling, no leveraged bets. It is not available yet. [How hedging will work](/hedging)[Sign up for RupeeCase](https://invest.rupeecase.com/signup) [No hedgeFalls with the marketWith a putA floor, for a premiumIllustration with made up numbers, not a product and not a recommendation.](/hedging) QQuick check ## 10 questions, 7 to pass. Each attempt draws 10 of the 15 questions in this module's bank, and a retake draws a fresh set. A pass gives this module's Certificate of Completion. Your result stays on this device and counts towards the Path 19 certificate. 7 of 10 correct passes module 19.5 Every answer is explained when you check; a retake is always free. Source: RupeeCase Learn quiz rules (70% to pass). Passed ### Certificate ID Download PNGPrint or save as PDF[Check the ID](/learn/certificates/verify) Self paced and unproctored. A record of completing free education by RupeeCase; not a NISM certificate and not endorsed by NISM, NSE, BSE or SEBI. It qualifies no one to deal, advise or publish research. CCheck yourself ## Path 19 so far. Your quick check results on this device, stop by stop. Stop 5 of 16 on Path 19 Algo, HFT and Backtesting: every live stop, this module ringed. Source: RupeeCase Learn, Path 19. 1. [19.1What a backtest is, and five biases that ruin itNot yet](/learn/path-19/module-19-1-backtest-biases) 2. [19.2Strategy metrics: CAGR, Sharpe, Sortino, drawdown and expectancyNot yet](/learn/path-19/module-19-2-strategy-metrics) 3. [19.3HFT, MFT and LFT comparedNot yet](/learn/path-19/module-19-3-hft-mft-lft) 4. [19.4Colocation, latency and fairness: NSE's historyNot yet](/learn/path-19/module-19-4-colocation-and-latency) 5. [19.5Building a compliant retail algoNot yet](/learn/path-19/module-19-5-building-a-compliant-algo#quiz) 6. [19.6Backtesting options on Indian dataNot yet](/learn/path-19/module-19-6-backtesting-options) 7. [19.7Walk forward and out of sample testingNot yet](/learn/path-19/module-19-7-walk-forward-testing) 8. [19.8Monte Carlo and bootstrap of trade resultsNot yet](/learn/path-19/module-19-8-monte-carlo-and-bootstrap) 9. [19.9Microstructure models: spreads, informed trading and price impactNot yet](/learn/path-19/module-19-9-microstructure-models) 10. [19.10Market making: inventory and quotingNot yet](/learn/path-19/module-19-10-market-making) 11. [19.11Optimal execution and market impactNot yet](/learn/path-19/module-19-11-optimal-execution) 12. [19.12HFT economics and the latency raceNot yet](/learn/path-19/module-19-12-hft-economics) 13. [19.13Backtest overfitting: deflated Sharpe, PBO and multiple testingNot yet](/learn/path-19/module-19-13-backtest-overfitting) 14. [19.14Financial machine learning done carefullyNot yet](/learn/path-19/module-19-14-financial-machine-learning) 15. [19.15Expiry day market integrity: a SEBI interim order, FutEq limits and surveillanceNot yet](/learn/path-19/module-19-15-expiry-day-market-integrity) 16. [19.16Capstone: a research note on an Indian derivatives questionNot yet](/learn/path-19/module-19-16-capstone-research-note) 17. [TPath test, 30 questionsNot yet](/learn/path-19/module-19-16-capstone-research-note#pathTestSection) Path 19 in reading time: 172 minutes over 16 modules Minutes of reading per module, this one in amber. Source: RupeeCase Learn, Path 19. Explore next ## Put the module to work. * [Free module 12.7Position sizing and risk of ruin for F&O beginners8 min read](/learn/path-12/module-12-7-position-sizing-and-risk-of-ruin) * [ToolOption payoff builderLegs on a dated Nifty chain, breakevens and charges](/learn/tools/payoff-builder) * [Free module 19.1What a backtest is, and five biases that ruin it9 min read](/learn/path-19/module-19-1-backtest-biases) * [Free module 19.3HFT, MFT and LFT compared10 min read](/learn/path-19/module-19-3-hft-mft-lft) * [Free module 19.4Colocation, latency and fairness: NSE's history11 min read](/learn/path-19/module-19-4-colocation-and-latency) * [Free module 19.6Backtesting options on Indian data11 min read](/learn/path-19/module-19-6-backtesting-options) Community ## Join my WhatsApp group. Scan the code, fillFill one short form, and join my WhatsApp group. Slides, sources, factsheets and the rebalance logs live there, and members join a daily Google Meet with me. New to RupeeCase? [Getting started](/getting-started) [See the terminal](/terminal) [Sign up for RupeeCase](https://invest.rupeecase.com/signup) [Join the WhatsApp group](https://forms.gle/C6HMtM1Z2GfeocQV7) [One form, one group](https://forms.gle/C6HMtM1Z2GfeocQV7)Scan with your phone camera SSources ## Go to the source. 8 sources, NSE the most cited The publisher of each source listed below. Source: Module 19.5 source list. 1. [SEBI circular SEBI/HO/MIRSD/MIRSD-PoD/P/CIR/2025/0000013, Safer participation of retail investors in algorithmic trading (4 February 2025)](https://www.sebi.gov.in/legal/circulars/feb-2025/safer-participation-of-retail-investors-in-algorithmic-trading_91614.html) SEBI 2. [SEBI circular SEBI/HO/MIRSD/MIRSD-PoD/P/CIR/2025/108, extension of timeline for the algo framework (29 July 2025)](https://www.sebi.gov.in/legal/circulars/jul-2025/extension-of-timeline-for-implementation-of-sebi-circular-sebi-ho-mirsd-mirsd-pod-p-cir-2025-0000013-dated-february-04-2025_95677.html) SEBI 3. [SEBI circular SEBI/HO/MIRSD/MIRSD-PoD/P/CIR/2025/132, extension of timeline and glide path for the algo framework (30 September 2025)](https://www.sebi.gov.in/sebi_data/attachdocs/sep-2025/1759232056254.pdf) SEBI 4. [NSE circular NSE/INVG/67858, implementation standards for retail algo trading (5 May 2025)](https://nsearchives.nseindia.com/content/circulars/INVG67858.pdf) NSE 5. [NSE, FAQs on safer participation of retail investors in algorithmic trading](https://nsearchives.nseindia.com/web/sites/default/files/inline-files/FAQ_Retail_Algo_03112025_NSE.pdf) NSE 6. [NSE, algorithmic trading and decision support tools](https://www.nseindia.com/static/trade/platform-services-non-neat-decision-support-tools-algorithm-trading) NSE 7. [NSE, empanelled algo providers](https://www.nseindia.com/static/trade/empanelled-algo-providers-exchange) NSE 8. [SEBI, circular of 3 August 2026, enrolment with PaRRVA for verified past performance](https://www.sebi.gov.in/legal/circulars/aug-2026/extension-of-timeline-for-enrolment-with-parrva-as-specified-in-sebi-circular-no-ho-38-14-4-2026-mirsd-pod-i-10557-2026-dated-april-29-2026_103314.html) SEBI GTerms ## 5 terms from this module. Threshold orders per secondThe order rate, ten a second per exchange to begin with, above which an investor's own algo must be registered with the exchange. Static IPA fixed internet address the broker whitelists for a client's API access. It may be changed no more than once in a calendar week. Algo IDAn identifier issued by the exchange that tags algo orders, so that the exchange can trace and, if needed, halt them. Kill switchAn emergency function and last defence against algo malfunction, set to halt trading on pre-defined conditions. Black box algoAn algo whose logic the user cannot see. Its provider must register as a research analyst and keep a research report for it. [All 230 terms in the glossary](/learn/glossary) [Question people askWhat are SEBI's algo rules (static IP, 10 orders per second, algo ID)?A short answer with a dated chart](/learn/questions/sebi-algo-rules)[Question people askHow do people build an algo with Python and broker APIs?A short answer with a dated chart](/learn/questions/build-an-algo-with-python)[Related module19.1 What a backtest is, and five biases that ruin it9 min, Intermediate](/learn/path-19/module-19-1-backtest-biases)[Related module19.3 HFT, MFT and LFT compared10 min, Advanced](/learn/path-19/module-19-3-hft-mft-lft)[Pillar guideDerivatives and Quant115 modules across paths 12 to 19](/learn/derivatives) Education only, not investment advice, a research report or a recommendation to buy, sell or hold any security. RupeeCase (QC Alpha Technologies Pvt Ltd) is not registered with SEBI as an investment adviser or research analyst. Contracts and prices shown are for illustration only, come from NSE end of day files at least 30 days old, and are not recommendatory. Derivatives trading carries a high risk of loss.