Your idea: Entry: At exactly 09:20 AM, the bot checks the Nifty spot price, round… — backtested on Indian market data | FakeTrades
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Your idea: Entry: At exactly 09:20 AM, the bot checks the Nifty spot price, round…

💡 Described strategy
Analysed 28 Oct 2026, 11:25 PM IST
★★★☆☆ 3.0 / 5

Verdict

Real minute-level backtest. Scored as the nearest tested variant: strangle sold at 09:20 with 30% per-leg stop-loss, square-off 15:15, on 2,126 real trading days 2015–2026 (1-minute NIFTY option premiums — every crash, election and expiry day included), real charges and spread, 1 lot.

Net ₹+287,218 (≈ ₹+23,934/yr, +16.0%/yr on ~₹1.5L margin — a genuinely consistent premium-collection edge), 56% green days, avg ₹+135/day, max drawdown ₹-44,265. Yearly: 2015: ₹+1,751. 2016: ₹-9,716. 2017: ₹+1,691. 2018: ₹-1,528. 2019: ₹+37,821. 2020: ₹+42,546. 2021: ₹+64,307. 2022: ₹+37,908. 2023: ₹+1,019. 2024: ₹+92,354. 2025: ₹+41,357. 2026: ₹-22,292.

Worst days: 01-Feb-26 ₹-10,924 | 13-May-26 ₹-9,264 | 01-Feb-22 ₹-8,984 | 02-May-25 ₹-8,001 | 14-May-26 ₹-7,768. The per-leg stop caps normal disasters, but it fills at market on the breach — a violent single minute can blow through it (see the worst-day figure).

Intraday premium-selling verdicts are scored against our precomputed 12-year variant grid; the nearest variant to this video's described rules is shown. Flagged for human review.

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Full transcript (103 words)
Entry: At exactly 09:20 AM, the bot checks the Nifty spot price, rounds to the nearest 50 to find the ATM strike, and sells the Call and Put. Hedge: It immediately buys OTM wings exactly 400 points away (HEDGE_DISTANCE = 400) to cap risk and reduce margin requirements. Individual Stop-Loss: It places a 30% stop-loss on the sold Call and Put individually. Breakeven Trailing: If one side hits the 30% stop-loss, it instantly modifies the stop-loss of the surviving leg down to its entry price, ensuring the remaining position cannot lose money. Exit: At 03:15 PM, it squares off all remaining open positions.

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Results are AI-generated from stored historical market data and are for educational purposes only — they cannot be treated as 100% accurate, nor as investment advice or a recommendation to buy or sell any security. Strategies from non-Indian markets are also backtested on Indian market data only. Past performance does not guarantee future results.