CCI Reversion (20, ±100)
Positive risk-adjusted return in 10 of 18 cells — strongest on GOLD · 4H (Sharpe 0.75); 8 cells lose after the 0.05% per-side fee. Median cell trails buy-and-hold by 166.4pp; 1 of 18 cells beat it.
§ Verdict rationale
Composite Sharpe 0.1 across 18 cells — expectancy does not survive the 0.05% per-side fee. Best cell: GOLD 4H (Sharpe 0.75).
§ 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 | -0.23 | -84.1% | -1465.4pp | -87.5% | 70% | 1591 |
| BTCUSD 4H | -0.07 | -73.8% | -1441.0pp | -86.8% | 70% | 371 |
| BTCUSD 1D | 0.09 | -34.6% | -1424.1pp | -76.8% | 69% | 61 |
| ETHUSD 1H | -0.48 | -99.0% | -627.1pp | -99.2% | 69% | 1544 |
| ETHUSD 4H | -0.02 | -82.7% | -597.9pp | -96.8% | 70% | 371 |
| ETHUSD 1D | -0.18 | -91.7% | -619.0pp | -94.8% | 64% | 55 |
| SPX500 1H | 0.50 | +14.1% | -58.2pp | -11.4% | 72% | 99 |
| SPX500 4H | 0.36 | +10.8% | -60.9pp | -15.1% | 75% | 32 |
| SPX500 1D | 0.42 | +100.9% | -482.4pp | -26.9% | 80% | 76 |
| QQQ 1H | 0.53 | +19.4% | -73.5pp | -14.6% | 71% | 96 |
| QQQ 4H | 0.58 | +25.4% | -66.5pp | -17.4% | 82% | 33 |
| QQQ 1D | 0.37 | +103.9% | -1305.6pp | -25.4% | 77% | 75 |
| GOLD 1H | 0.36 | +11.0% | -118.0pp | -18.1% | 71% | 79 |
| GOLD 4H | 0.75 | +26.3% | -102.1pp | -20.0% | 88% | 33 |
| GOLD 1D | 0.11 | +10.0% | -214.9pp | -34.5% | 67% | 78 |
| EURUSD 1H | -2.69 | -27.5% | -36.6pp | -27.8% | 68% | 378 |
| EURUSD 4H | -0.12 | -1.7% | -10.7pp | -6.3% | 71% | 90 |
| EURUSD 1D | -0.04 | -5.6% | +13.0pp | -21.9% | 63% | 83 |
10 of 18 cells positive · best GOLD · 4H · cells are not equal length — the composite is a median
§ The exact source that ran — Pine v5
//@version=5strategy("CCI Reversion (20, ±100)", initial_capital=100000, default_qty_type=strategy.percent_of_equity, default_qty_value=100)c = ta.cci(close, 20)longSig = ta.crossover(c, -100)exitSig = ta.crossover(c, 100)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.