I've posted a couple of these now (INJ, BTC), showing what a parameter sweep does when you hold everything else constant. Two things people pushed back on last time: that drawdown balloons when you chase more return, and that the headline stats looked too good. So for this ETH one I want to focus on exactly that first point, and let you check the drawdown side by side.

The strategy (unchanged): long-only DCA on ETHUSDT.P 4h. Five safety orders at −2 / −5 / −9.5 / −16 / −25% from base, sizes scaling 1.8× per rung, no stop loss, position bounded by the ladder.

What changed: two parameters. RSI entry threshold 28 → 36, take-profit 3% → 4.5%. Nothing else touched. Both are what the sweep returned as best on the historical window.

Before/after (BYBIT:ETHUSDT.P 4h, Jan 1 2024 – Jul 2026, \~30 months, 100k initial, 0.06% commission, 3-tick slippage):

* Baseline (RSI < 28, TP 3%): +5,790.33 USDT (+5.79%), max drawdown 3.83%, 93 trades, 68.82% WR
* Optimized (RSI < 36, TP 4.5%): +14,518.03 USDT (+14.52%), max drawdown 4.41%, 134 trades, 71.64% WR

The point I want to make: net PnL went up \~2.5× (+5.79% → +14.52%), but max drawdown only moved from 3.83% to 4.41% — about +0.6pp. It's not flat, so I won't claim the extra return was free, but the risk didn't scale anywhere near as fast as the return did. The mechanism: the looser RSI entry (36 vs 28) engages dips earlier and more often, so the strategy is in the market more, while the wider 4.5% target lets each recovery run further before banking instead of exiting on the first small pop.

On the "stats look too good" pushback from last time: fair, and worth addressing directly. The thing that changes here is sample size. The optimized config produced 134 closed trades over the window, which is above the \~100 I'd generally want before taking a win rate seriously — so the 71.64% rests on a real number of deals rather than a handful, unlike the tighter-entry versions I posted before that sat in the 80–90 range.

The caveat still stands, and I'll keep saying it: two parameters were swept over the same window the results are measured on, so best in-sample is not best out-of-sample. More free parameters means more room to fit the window. Treat these as the ceiling of what the config did historically, not a forward expectation, and re-validate on fresh data. It's also a stopless martingale — a sustained ETH decline below the −25% bottom rung leaves the position fully loaded with no further adds, and that tail is the real risk here, not the backtest drawdown.

Script is open-source on TradingView: [https://www.tradingview.com/u/3Commas/#published-scripts](https://www.tradingview.com/u/3Commas/#published-scripts)

Disclosure up front: the optimizer is QuantPilot, which I work on, so I'm not pretending to be neutral. The point is the before/after and the caveat, not a pitch — the script is open-source and you can verify the backtest yourself.

Another Pine DCA optimizer before/after, this time on ETH — 2.5× the net PnL with only a small bump in drawdown (4h)