Your idea: IF (rsi_15m cross_below 70 or rsi_15m cross_below 50) and macd_3m.macd… — backtested on Indian market data | FakeTrades
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Your idea: IF (rsi_15m cross_below 70 or rsi_15m cross_below 50) and macd_3m.macd…

💡 Described strategy
Analysed 05 Sep 2026, 08:16 PM IST
★☆☆☆☆ 1.0 / 5

Detected components (auto-read from transcript)

MACD

Verdict

Real option-buying backtest. Decoded entry: a MACD signal-line cross on NIFTY 10-min bars → buy the ATM weekly CE (long) / PE (short), stop 0% / target 0% of premium, square-off by 15:15. Priced on real 1-minute NIFTY option premiums (GFDL, 2015–2026 — every tick of theta, IV crush and gamma is inside these prices), real charges and spread.

9,071 trades on ₹1L: net -662.0% over 12 years (-55.2%/yr, loses money), win 0%, payoff 0.00 (avg win ₹0 / avg loss ₹-73), max drawdown -662%, worst trade ₹-200. 2015: ₹-24,466. 2016: ₹-37,399. 2017: ₹-41,428. 2018: ₹-48,686. 2019: ₹-46,334. 2020: ₹-52,435. 2021: ₹-83,636. 2022: ₹-66,346. 2023: ₹-59,080. 2024: ₹-60,495. 2025: ₹-96,322. 2026: ₹-45,398.

Option buying is convex — low win-rates are normal; the question is whether winners outrun the premium bleed. Backtested on 12 years of minute-level premium data (2015–2026; monthly contracts before 2019 — weeklies didn't exist; constant 65-unit lot); entries tested intraday as taught. Flagged for human review.

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Is it profitable? (green above the line = made money, red below = lost it)

Year by year (every trade the rules fired, on real NIFTY option premiums — 1 lot, ₹1L)

YearTradesWin %Net P&L
20153490% ₹-24,466
20165650% ₹-37,399
20176590% ₹-41,428
20186820% ₹-48,686
20197490% ₹-46,334
20206950% ₹-52,435
202111450% ₹-83,636
20228540% ₹-66,346
20239110% ₹-59,080
20247830% ₹-60,495
202512050% ₹-96,322
20264740% ₹-45,398
Full transcript (35 words)
IF (rsi_15m cross_below 70 or rsi_15m cross_below 50) and macd_3m.macd_line < macd_3m.signal_line sell market EXIT CONDITIONS OR Stop: entry_price * (1 + 0.001) Target: entry_price - (entry_price * 0.001 * 1.5) NIFTY50 ATM long option

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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.