Can I automate option selling strategies like straddles and strangles?

Yes. Time-based entries, strike selection by offset, percentage or premium, per-leg stop-losses, re-entry rules and end-of-day square-off are all supported — the building blocks of systematic option selling on NIFTY and BANKNIFTY. Sell-side risk is real, so per-leg stops and a daily loss cap are enforced in the cloud.

How are lot sizes handled for NIFTY and BANKNIFTY options?

Automatically. INDfolio AI tracks current NSE contract specifications, so position sizing is always in whole lots at the correct current lot size, and backtests apply the lot sizes that were in force in each historical period. When the exchange revises a lot size, the platform updates — you don’t maintain it.

Does it handle weekly and monthly expiries?

Yes. Strategies can target the current or next expiry, and the platform follows NSE’s live expiry calendar — including the changes to weekly index expiry schedules made by exchange circular. Expiry-day behaviour like square-off before close is built in.

Can I buy options with algos, or only sell?

Both. Directional option buying — breakout triggers, momentum entries with stops and targets — automates with the same strike-selection and risk machinery as selling strategies. The backtester models premium paid, decay and costs either way.

What does options algo trading cost on INDfolio AI?

Building and backtesting options strategies starts free (3 years of NSE data, 5 AI generations a month). Live automation starts with Trader at ₹999/month for one broker; Pro at ₹2,499/month adds all seven brokers and unlimited strategies. GST included. Broker charges are separate.

Markets · Options

Algo trading for NSE options — built, tested and automated

Last updated: August 2026

Short answer

Yes — INDfolio AI automates NSE options strategies end to end: strike selection by ATM offset, points, percentage or premium; correct lot sizes and expiry handling for NIFTY, BANKNIFTY, FINNIFTY and stock options; per-leg stop-losses and automatic square-off. Strategies are backtested on NSE options history with the full Indian cost stack, paper traded on live data, then deployed through your broker’s official API — all without coding.

Options are where Indian retail algo trading concentrates, and where generic software breaks down fastest. An options algo is not "buy when RSI is low" — it is "at 9:20, sell the strike closest to a chosen offset from spot, in the current expiry, with a per-leg stop and a hard square-off time". Those rules — time-based entries, strike selection, expiry awareness, leg-level exits — are first-class concepts in INDfolio AI, whether you sell premium systematically or buy options on breakouts.

Describe the structure in plain English ("sell a NIFTY strangle at 9:20, strikes about 1% OTM, exit any leg at 25% stop-loss, square off everything at 3:15") and the platform builds it as editable rules. From there the path is the standard one: expiry-aware backtest, paper trade on live NSE data, then live deployment to Zerodha, Fyers, Dhan, Angel One, Upstox, Alice Blue or Shoonya.

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Strike selection logic

ATM, offset by points or percentage, or premium-based selection — the rules that define real option strategies, buying and selling alike.

Lot sizes and expiries handled

Contract specifications for NIFTY, BANKNIFTY, FINNIFTY and stock options — lot sizes and expiry calendars — are tracked by the platform and applied automatically.

Per-leg risk control

Stop-losses and targets per leg, re-entry rules, position limits, a daily loss cap and automatic square-off — enforced in the cloud.

F&O costs modelled per leg

Brokerage per leg, STT on the sell side, exchange charges, GST, stamp duty and slippage — deducted the way an options trader actually pays them.

Backtesting options strategies on NSE data

An options backtest has to answer questions an equity backtester cannot: what was the premium at the strike your rules would have selected, how did it decay toward expiry, and what did each leg cost to enter and exit? INDfolio AI simulates the actual option legs your rules select, with lot sizes and expiry behaviour matching NSE contract specifications — so a short-strangle backtest reflects premium decay and gap risk, not a spot-price approximation.

This matters most for selling strategies, where the edge is the decay itself and the risk is the tail. Costs decide these outcomes: on a multi-leg structure traded every week, brokerage, STT and slippage are frequently the difference between positive and negative expectancy. Every simulated trade pays the full Indian cost stack, per leg.

Expiry schedules and lot sizes on NSE index options have changed repeatedly by exchange circular in recent years. INDfolio AI tracks current contract specifications, and backtests respect the calendar that actually applied in each historical period.

From backtest to live options execution

A validated options strategy paper trades first — on live NSE data, through at least one full expiry cycle — so you see how it behaves on gap opens, expiry sessions and volatility spikes before money is involved. The paper engine and the live engine are the same code; going live changes where orders are sent, nothing else.

Live execution flows through your broker’s official API, with orders placed leg by leg under your rules: entry at your trigger time or condition, exits on per-leg stops or targets, re-entries if configured, and a hard square-off at your chosen time. Because everything runs in INDfolio AI’s cloud, execution does not depend on your laptop, browser tab or home internet surviving the session.

Risk controls for options algos

Options automation without hard risk limits is a fast way to discover tail risk. Every INDfolio AI options strategy carries its own risk block — per-leg stop-losses, position limits, a maximum daily loss for the account and automatic square-off — and those limits are enforced server-side. If a limit is breached, the platform acts on it whether or not you are watching.

The sober truth belongs on this page: SEBI’s own studies have found that the large majority of individual F&O traders lose money, and option selling in particular carries gap risk that no stop-loss fully removes. Backtest honestly, size small, respect the daily loss cap, and treat automation as a discipline tool — not as a promise of profit.