MACD Cross (12/26/9)
Positive risk-adjusted return in 15 of 18 cells — strongest on SPX500 · 4H (Sharpe 1.30); 3 cells lose after the 0.05% per-side fee. Median cell trails buy-and-hold by 61.0pp; 4 of 18 cells beat it.
§ Verdict rationale
Composite Sharpe 0.56 across 18 cells. The edge concentrates in SPX500 4H (Sharpe 1.3); 3 of 18 cells are negative after the 0.05% per-side fee.
§ 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 | 0.05 | -52.4% | -1433.7pp | -83.8% | 36% | 3004 |
| BTCUSD 4H | 0.57 | +583.0% | -784.3pp | -74.1% | 38% | 734 |
| BTCUSD 1D | 0.83 | +2219.8% | +830.3pp | -51.7% | 39% | 117 |
| ETHUSD 1H | 0.56 | +690.3% | +162.2pp | -65.5% | 37% | 2969 |
| ETHUSD 4H | 0.59 | +811.4% | +296.2pp | -78.3% | 38% | 742 |
| ETHUSD 1D | 0.63 | +1063.8% | +536.5pp | -69.3% | 37% | 120 |
| SPX500 1H | 0.50 | +15.2% | -57.0pp | -17.6% | 42% | 185 |
| SPX500 4H | 1.30 | +33.8% | -37.9pp | -8.6% | 49% | 63 |
| SPX500 1D | 0.50 | +101.0% | -482.3pp | -15.7% | 46% | 171 |
| QQQ 1H | 0.32 | +11.5% | -81.4pp | -22.6% | 42% | 187 |
| QQQ 4H | 0.76 | +26.8% | -65.1pp | -19.6% | 44% | 66 |
| QQQ 1D | 0.59 | +177.9% | -1231.7pp | -25.0% | 48% | 155 |
| GOLD 1H | 0.61 | +25.8% | -103.2pp | -16.0% | 44% | 185 |
| GOLD 4H | 0.89 | +44.0% | -84.4pp | -28.3% | 45% | 58 |
| GOLD 1D | 0.33 | +66.6% | -158.3pp | -29.7% | 38% | 160 |
| EURUSD 1H | -3.33 | -43.7% | -52.8pp | -44.4% | 34% | 664 |
| EURUSD 4H | -0.41 | -6.5% | -15.6pp | -11.4% | 42% | 161 |
| EURUSD 1D | -0.41 | -33.2% | -14.5pp | -38.5% | 38% | 172 |
15 of 18 cells positive · best SPX500 · 4H · cells are not equal length — the composite is a median
§ The exact source that ran — Pine v5
//@version=5strategy("MACD Cross (12/26/9)", initial_capital=100000, default_qty_type=strategy.percent_of_equity, default_qty_value=100)[macdLine, signalLine, histLine] = ta.macd(close, 12, 26, 9)longSig = ta.crossover(macdLine, signalLine)exitSig = ta.crossunder(macdLine, signalLine)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 median of the 18 cell Sharpes, not the mean — cells differ in length by an order of magnitude, and one long cell should not carry the other seventeen.
- 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. The headline figure is the deepest of the 18 cells, not their average.
- 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. Shown as the median of the 18 cells plus how many cells beat it; a mean would let one long cell stand in for the rest.
- Alpha score
- The desk’s 0–100 composite: out-of-sample edge (0–40; the methodology page defines what out of sample means for the catalog), 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: resin 0.2.2 (next-bar-open fills, TV rule) · scored UTC 2026-11-07 10:58 · 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.