RSI Mean Reversion (14, 30/70)
Positive risk-adjusted return in 13 of 18 cells — strongest on GOLD · 1H (Sharpe 1.03); 5 cells lose after the 0.05% per-side fee. Trails buy-and-hold by 452.8pp on average.
§ Verdict rationale
Composite Sharpe 0.39 across 18 cells. The edge concentrates in GOLD 1H (Sharpe 1.03); 5 of 18 cells are negative after the 0.05% per-side fee. Trails buy-and-hold on average.
§ Alpha score breakdown
alpha = edge (0-40: clamp(compositeSharpe/2,0,1)*40) + stability (0-25: positiveCells/18*25) + flaw penalty (0 to -25: static findings, 0 across v1 catalog) + reproduction (0-10: engine oracle parity vs pine2py, 251/257 scripts = 9)
§ Equity vs buy-and-hold — fee-adjusted, per cell
§ All 18 cells — including the ugly ones
| Market · TF | Sharpe | Return | vs B&H | Max DD | Win | Trades |
|---|---|---|---|---|---|---|
| BTCUSD 1H | -0.06 | -75.3% | -1484.3pp | -89.7% | 65% | 285 |
| BTCUSD 4H | 0.25 | +25.3% | -1369.3pp | -84.2% | 68% | 90 |
| BTCUSD 1D | 0.36 | +129.9% | -1273.2pp | -51.9% | 77% | 13 |
| ETHUSD 1H | -0.18 | -94.9% | -630.7pp | -97.2% | 65% | 303 |
| ETHUSD 4H | -0.18 | -94.6% | -617.1pp | -97.8% | 60% | 75 |
| ETHUSD 1D | 0.19 | -6.2% | -537.3pp | -73.7% | 75% | 12 |
| SPX500 1H | 0.58 | +20.3% | -52.4pp | -19.4% | 74% | 23 |
| SPX500 4H | 0.63 | +21.1% | -51.6pp | -17.0% | 83% | 6 |
| SPX500 1D | 0.57 | +191.1% | -398.3pp | -28.7% | 86% | 14 |
| QQQ 1H | 0.89 | +46.0% | -47.0pp | -16.8% | 85% | 27 |
| QQQ 4H | 0.52 | +21.2% | -71.6pp | -19.7% | 80% | 5 |
| QQQ 1D | 0.58 | +222.9% | -1210.7pp | -29.9% | 94% | 16 |
| GOLD 1H | 1.03 | +44.8% | -78.4pp | -16.8% | 94% | 31 |
| GOLD 4H | 0.42 | +11.2% | -111.9pp | -18.4% | 83% | 6 |
| GOLD 1D | 0.20 | +25.3% | -194.8pp | -29.2% | 71% | 14 |
| EURUSD 1H | -0.19 | -2.6% | -11.8pp | -7.9% | 62% | 71 |
| EURUSD 4H | 0.50 | +6.7% | -1.6pp | -7.8% | 77% | 22 |
| EURUSD 1D | -0.30 | -26.1% | -8.2pp | -37.9% | 50% | 10 |
13 of 18 cells positive · best GOLD · 1H · cells are not equal length — the composite is a median
§ The exact source that ran — Pine v5
//@version=5strategy("RSI Mean Reversion (14, 30/70)", initial_capital=100000, default_qty_type=strategy.percent_of_equity, default_qty_value=100)r = ta.rsi(close, 14)longSig = ta.crossover(r, 30)exitSig = ta.crossover(r, 70)if longSig strategy.entry("L", strategy.long)if exitSig strategy.close("L")plot(strategy.equity, "equity")plot(strategy.position_size, "pos")plot(strategy.closedtrades, "closed")plot(strategy.wintrades, "wins")plot(strategy.grossprofit, "gp")plot(strategy.grossloss, "gl")This source was executed verbatim by the wavealgo JS engine — there is no port step to drift. The engine is oracle-verified bar-by-bar (1e-9 tolerance) against an independent Python implementation on 251/257 corpus scripts.
§ Flaw checklist
Verdict rules: pass: composite Sharpe >= 0.9 and >= 12/18 cells positive · cond: composite Sharpe > 0 and best cell Sharpe >= 0.9 · fail: otherwise · rep: static repaint/look-ahead finding (none in the authored v1 catalog: confirmed-bar signals, next-bar-open fills)
§ What the numbers mean
- Sharpe ratio
- Risk-adjusted return: mean daily return divided by its standard deviation, annualized ×√252. The composite figure is the mean of the 18 cell Sharpes — one bad market drags it honestly.
- Max drawdown
- The worst peak-to-trough equity loss over the window, measured on the fee-adjusted curve. What you would have sat through, not what you would have ended with.
- Profit factor (PF)
- Gross profit divided by gross loss, with fees charged to the loss side. Above 1.0 means gross gains exceeded gross losses; 1.0–1.2 is usually noise.
- Win rate
- Share of closed trades that closed profitable. A high win rate with a profit factor near 1 means many small wins and a few large losses — common in mean-reversion.
- vs buy-and-hold
- Strategy total return minus the return of simply holding the asset over the same window — the benchmark any active strategy must beat to justify existing.
- Alpha score
- The desk’s 0–100 composite: out-of-sample edge (0–40), regime stability across cells (0–25), flaw penalty (0 to −25), reproduction accuracy (0–10). The exact formula ships with the data.
Bring your own. We grade it the same.
Engine: pine2js (next-bar-open fills, TV rule) · scored UTC 2026-08-08 04:53 · deterministic rerun — same data, same numbers. Backtested results are measurements of the past, not investment advice; nothing here is a recommendation to trade. wavealgo is operated by Streamize LLC.