Algo Trading for Beginners in India: A 30-Day Plan

If you’re starting algo trading in India, my advice for the first 30 days is to keep real money out of it. Spend week one learning how orders and costs work at your broker, week two writing one strategy on paper, week three backtesting it with every cost switched on, and week four paper trading it behind hard loss limits. Real money comes in month two, in the smallest size your broker allows.

That sounds slow, and it’s meant to be. SEBI’s August 2026 study found that 87.7% of individual traders in equity F&O lost money in FY26, and that was the better year: the figure was 91.1% in FY24 and 90.9% in FY25. The average loss-maker lost ₹1.47 lakh (SEBI, Profitability of Individual Traders in the Equity Derivatives Segment, FY25–FY26). Automation doesn’t exempt you from those numbers. A computer will follow a bad plan with perfect discipline.

Last updated: November 2026.

This post is short on purpose. If you want the background first (what algo trading is, how the regulation works, the full idea-to-live workflow), read our complete algo trading guide. What follows is the order I’d do things in, and what I’d leave alone.

Week 1: learn the plumbing before the strategy

Everyone wants to start with the strategy because it’s the interesting part. Start with the dull part instead. A surprising share of early losses has nothing to do with the strategy: it comes from an order type you didn’t understand or a charge you didn’t know existed.

By Sunday you should be able to answer these without looking anything up:

• What CNC, MIS and NRML mean, and which one your strategy will use. An algo that sends MIS orders when you meant CNC will have its “swing trade” squared off by the broker in the last few minutes of the session.
• What limit, market, SL and SL-M orders actually do. Since the April 2026 rules, some brokers convert API market orders into market-price-protection orders, which can sit unfilled in a fast move. Your broker’s API notice will say how it handles this.
• What your broker’s API costs and how login works. At Zerodha, the order API for personal use is free and the plan with live data and historical candles is ₹500 a month per app (Zerodha support, checked November 2026). API sessions now end every day under the new rules, so expect a 2FA login each morning.
• Whether you need a static IP. If you’ll run your own code through your own API app, yes: since 1 April 2026 those orders must come from a static IP registered with your broker. Our static IP guide covers the options.

Then work out what one round trip costs, by hand, once. Say you buy 100 shares at ₹1,000 intraday and sell them at ₹1,000. No profit, no loss. At Zerodha’s published rates you’d still pay ₹40 brokerage, ₹25 STT, about ₹6 in exchange charges, ₹3 stamp duty and about ₹8 GST. Roughly ₹83 to stand still. On a ₹1 lakh position the stock has to move about 83 paise your way before you’ve made a rupee. The brokerage calculator does this for any broker we track; doing it by hand once makes the numbers stick.

One piece of homework I’d insist on: place two or three tiny manual trades (one share is fine) and read the contract note line by line. It’s the cheapest lesson in this whole plan.

Week 2: one idea, one instrument, written on paper

One strategy. One instrument. Not five strategies across Nifty, Bank Nifty and twenty stocks. When something goes wrong in the first month (and something will), you need to know which rule caused it. That’s only possible if there’s one set of rules to blame.

A good first idea is simple enough to explain in two sentences and trades often enough to give you a sample. It should also run on something liquid. A moving average crossover on the daily chart of a large-cap stock works. So does an opening range breakout on one liquid Nifty 50 stock. Neither is clever, and that’s fine. This month is about learning the workflow, not finding the strategy that funds your retirement.

Write it as a rule card. Here’s a hypothetical one:

• Instrument: one liquid Nifty 50 stock, cash segment, intraday (MIS).
• Opening range: the high and low from 9:15 to 9:30 am.
• Entry: buy if a 5-minute candle closes above the range high before 11:00 am. Long side only for now.
• Stop: the range low.
• Exit: a target at 1.5 times the risk, or 3:10 pm, whichever comes first.
• Size: risk ₹500 per trade (1% of a ₹50,000 account). Quantity is ₹500 divided by (entry minus stop).
• Limits: one trade a day. Skip the day if the stock opens more than 2% away from yesterday’s close.

The test for a rule card: hand it to a friend along with a chart and ask them to mark the trades. If they mark different trades from you, a rule is ambiguous. Fix it before you open any software.

What I wouldn’t start with is option selling. I know it’s the most popular retail strategy in India and I understand the appeal, because you win most weeks. SEBI’s companion study shows the shape of the problem. Traders who were mostly option sellers had the lowest share of loss-makers of any group in FY26 (44%), but the ones who did lose averaged about ₹51.7 lakh each, more than 11 times the average for mostly-option buyers (SEBI, Trading Behaviour of Individual Traders, Aug 2026). SEBI flags that its seller sample is small, so don’t lean on the exact figure. The pattern is the point: small, frequent wins and rare, large losses. That’s a terrible profile to learn on, because a backtest can look smooth for months before the bad week arrives.

Pure option buying isn’t a gentler start either. In the same study, the median “only options buyer” lost more than the peak margin they had used during the year. My order would be equity first, then one lot of index futures once your capital allows it, and options after you’ve run the full cycle at least once.

Week 3: backtest with costs, then try to break it

Run the rule card over enough history to include a few different market moods. I’d want at least 100 trades before reading anything into the results. Switch every cost on (brokerage, STT, exchange charges, GST, stamp duty) and add a slippage assumption, because historical candles show the price that traded, not the price you would have got.

Then spend more time attacking the result than admiring it:

1. Nudge each parameter by 10–20%. Change the 9:30 range to 9:35, the 1.5× target to 1.3×. If the profit disappears, you’ve fitted noise. Our post on overfitting explains why this happens.
2. Find the worst month and the longest losing streak, and ask honestly whether you’d have kept the strategy running through them.
3. Compare it with doing nothing: holding the stock or the index over the same period.
4. Hold back the most recent year. Build on the older data, then test once on the year you didn’t look at.

Be most suspicious of the backtest you like most. When a beginner’s first strategy produces a smooth equity curve, the usual cause is a mistake (a cost left out, a fill at a price nobody could have got, a stop assumed to fill exactly at its trigger, data that peeks into the future), not a discovery.

A disclosure, since this is where a tool matters: we build INDfolio, so weigh this accordingly. You can describe a rule card like the one above in plain English, backtest it on NSE history with the Indian cost stack included, and paper trade it, all on our free Starter plan. Any backtester that models Indian costs honestly will do the job, though. The habit matters more than the tool.

Week 4: paper trade, and set loss limits now

Run the strategy on live prices with virtual money. With one trade a day, four weeks gives you about 20 trades. That’s nowhere near enough to prove an edge. It is enough to prove the machinery: signals fire when they should and paper fills look like what the backtest assumed. You’ll also find out what breaks on a market holiday, or on the morning your login expires. Our piece on backtesting vs paper trading goes through what each stage can and can’t tell you.

This is also the week to set your loss limits, before any real money exists to argue with you. My starting rules of thumb, which are opinions and not regulations:

• Risk per trade: 0.5–1% of the capital you’ve given the strategy.
• Daily loss cap: 2%. The strategy stops for the day. No override.
• Pause-and-review line: 6% down from the peak, or 1.5 times the worst month in the backtest, whichever comes first.

Write your go-live criteria down before the paper period starts, too. Something like: no missed or duplicate orders, results inside the backtest’s normal range, zero manual overrides, at least 20 signals. If you write them after you’ve seen the results, you’ll write criteria the results happen to meet.

Month 2: real money, smallest size

Go live at the smallest size that still tests the system: a handful of shares, or one lot. The point of the first live month isn’t profit. It’s measuring the gap between paper and reality: slippage, rejections, partial fills, and how you feel watching real money move.

Keep a plain log. Date, signal, intended price, actual fill, and the reason for any manual action. If live results drift from paper by more than costs and slippage can explain, stop the strategy and find out why. Don’t tweak parameters while it’s running.

I’d hold off on a second strategy until the first has about 30 live trades, and I wouldn’t increase size until live results have tracked paper for a couple of months. Tell your CA you’ve started trading actively, too: intraday equity profits are treated as speculative business income and F&O as non-speculative business income, and the record-keeping is easier from day one.

Two things I’d skip entirely in the first 30 days. Anything sold on Telegram or Instagram with a monthly return figure attached. And paying for any platform before you’ve finished week three. On a small account, fixed monthly fees can cost more than the strategy earns, which our post on minimum capital for algo trading works through with real numbers.

If you want to run weeks two to four without writing code, INDfolio’s Starter plan is free.

Frequently asked questions

Can I learn algo trading in 30 days? You can learn the workflow in 30 days: broker plumbing, writing rules, backtesting with costs and paper trading. Learning whether you have a strategy worth running takes months of live results, and many people find they don’t.

Do I need to know Python to start algo trading in India? No. No-code platforms, broker tools and alert-based setups cover most beginner strategies, and our guide to algo trading without coding compares the routes. Python becomes necessary for custom data, tick-level logic or machine-learning models.

How much money do I need to start algo trading? Nothing for the first month of this plan, since backtesting and paper trading need no capital. For live trading, equity strategies can start with a few thousand rupees, while one lot of Nifty futures needed roughly ₹1.76 lakh of margin in November 2026.

Is algo trading legal for beginners in India? Yes, when orders go through your SEBI-registered broker’s official API and follow the broker’s rules, including the static IP and daily login requirements that applied from April 2026. Rules differ slightly by broker, so read your broker’s API notice.

Is algo trading profitable for beginners? Usually not at first, and SEBI’s data says most individual F&O traders lose money with or without algorithms. Automation helps with discipline and testing; it doesn’t create an edge. Our post on whether algo trading is profitable goes through the numbers.