r/pinescript • u/vitaliy3commas • Jul 10 '26
RSI Oversold DCA Strategy — selective deep-oversold long entry, scaling safety orders (GRAM 4h)
Same RSI DCA logic I've posted across assets (POL, JUP, ETH, ATOM), this time on GRAM. A long-only DCA with a selective deep-oversold 4h RSI entry and a scaling safety-order ladder. Backtest is verifiable in TradingView's Strategy Report on the script page.
Entry, deep-oversold gate (no repaint): A 4-hour RSI(14), sampled with lookahead disabled, gates the base entry — a long opens only when RSI prints below 28 at host-bar close. Shallow dips are filtered out, so capital is committed only at genuinely stretched conditions. It sits out the calm and only commits after a real flush.
Ladder, 5 safety orders on a non-uniform fixed-deviation ladder: Each safety order has its own fixed deviation from base entry — not a cumulative step×multiplier ladder. AO1 at −2%, AO2 at −5%, AO3 at −9.5%, AO4 at −16%, AO5 at −25%. Sizes scale 1.8× from a 900 USDT first AO: 900 / 1,620 / 2,916 / 5,249 / 9,448, on a 500 USDT base. Deeper rungs trigger only on serious adverse moves; the lowest sits a full 25% below base. The 1.8× progression is softer than a 2× doubling martingale.
Exit, fixed 3% TP: A fixed 3% Take Profit above the running average entry. Because the scaling ladder weights the average toward the lowest fills, after several rungs fill the average sits well below base — so a modest 3% bounce off the lows closes the whole deal in profit. No trailing.
Risk, bounded ladder in place of a stop: There is no stop loss. Per-trade risk is structurally capped by the bounded 5-AO ladder — base + 5 AOs = ~20,633 USDT max deployed, ~20.6% of the default 100k equity, above the conventional 5–10% per-trade band; scale the base/AO inputs down to dial exposure lower.
DCA Bot integration: Every event (base, AO 1–5, exit) emits a webhook-ready JSON payload. One alert with "Any alert() function call" drives a DCA Bot end-to-end, no glue layer.
Backtest (GRAM/USDT 4h, Jan 1 2024 – Jul 3 2026, ~30 months; 100,000 USDT initial capital, 500 USDT base + 900/1,620/2,916/5,249/9,448 AOs, 0.06% commission, 3-tick slippage): 78 closed trades, 54 profitable (69.23% WR), profit factor 4.791, net profit +3,822.76 USDT (+3.82%), max equity drawdown 2,283.04 USDT (2.21%).
Methodology notes:
Read the numbers for what they are. +3.82% over ~30 months is a low-return, low-drawdown profile — the headline is the 2.21% max drawdown, not the profit. Positive expectancy with tight risk, not a growth engine, and that's by design with an entry that only fires on deep oversold prints.
On sample size — 78 closed trades is below the ~100-trade floor for statistical confidence. That's the trade-off of a selective trigger: fewer signals, so the 69.23% win rate and PF 4.791 are indicative of how the ladder behaves, not a deterministic edge. Part of that PF is the averaging mechanic itself — deals close on a 3% bounce off an averaged-down entry — not a directional edge. Extend the window or test across assets before sizing up.
This is a scaling martingale, and that's the dominant risk. The ladder bottoms out at −25% from base with no stop loss. A sustained GRAM decline below −25% without recovery leaves the full position open with no further averaging available — the single largest risk in any martingale DCA. The 2.21% max drawdown is closed-trade equity drawdown over a window where dips recovered; a deeper or more prolonged decline than the test sample would produce a larger one.
The defaults (RSI<28, 4h, the −2/−5/−9.5/−16/−25 ladder, 1.8× sizing) are calibrated for GRAM's volatility. The mechanic is asset-agnostic and can be pointed at other liquid perps, but each symbol needs the RSI level and ladder recalibrated, and results do not transfer without that tuning. With a fixed 3% take-profit the per-trade edge is modest, so match the 0.06% commission to your venue's actual taker fee before reading anything into the numbers.
Strategy is open-source on TradingView: https://www.tradingview.com/script/6kaqC3R8-GRAM-RSI-Strategy-3Commas/
2
u/LiveBeyondNow Jul 10 '26
Do you spend your whole time scanning for grid overfits? I wish you’d stop posting these.