Momentum

Cci Trend

Lambert's Commodity Channel Index traded as designed: buys when CCI pushes above +100, marking a move strong enough to call a trend, and sells when it breaks below -100.

Total score 54/ 100 rank 10 / 42 · momentum 01 / 8

How It Works

  1. Compute the 20-bar CCI from each bar's typical price — the average of its high, low and close — measuring how far the bar sits from its recent average in units of normal deviation.
  2. Buy when CCI crosses above +100. In Lambert's original design this is not an overbought warning but the opposite: the point where a move is finally strong enough to be called a trend.
  3. Sell when CCI breaks below −100, marking a move of the same conviction in the other direction.

Worked example. The typical price pulls 4 above its 20-bar average while the mean deviation is 2, giving CCI ≈ 133 — past +100, so the strategy buys. The position is held through the trend until CCI eventually prints −120 and the trade is closed.

The Math Behind The Indicators

Everything runs on closing prices of the traded timeframe: P is a close, Pt today's close, and N counts bars — one bar is one candle of that timeframe, so 20 bars on a 1h chart is 20 hours.

Commodity Channel Index (CCI)
How far the bar sits from its recent average, measured in units of typical deviation. It works off the typical price — the average of the high, low and close — so it accounts for the whole bar rather than the close alone. The 0.015 constant is chosen so that ordinary movement lands roughly inside ±100, which makes a reading beyond ±100 the marker of a genuine trend rather than noise.
CCI = TP − SMAN(TP)0.015 · MDN,    TP = H + L + P3
Example: If the typical price is 104, its 20-bar average is 100 and the mean deviation is 2, then CCI = (104 − 100) / (0.015 · 2) ≈ 133 — above +100, so the move counts as a trend rather than routine drift.

Example Chart

Example Chart

The Metrics

Metric Calculation What it shows
Price Change % change = Plast − P0P0 × 100 The traded market's own close against its first close over the same window, as a percentage. What the market did while the rule was running — the benchmark every other row here is read against. A rule that made 40% in a market that made 120% lost to doing nothing.
Trades N = count(closed positions) How many positions the rule opened and closed over the window. The sample behind every other figure, and what the fees are charged on. Two rules with the same return are not the same rule if one took nine trades and the other took nine hundred.
Win Rate % W%n = winsnn × 100 Of the first n trades, how many closed above the cash they opened with after fees. Plotted trade by trade, so the line is the rate so far rather than a final figure. How often the rule is right, which is not how much it makes. A rule can win a third of its trades and still lead, if the third it wins pays for the two it loses.
Cumulative P&L % PnL%n = n∑i=1(fi − 1) × 100 Each trade's percentage result added up, net of fees. A sum rather than a compounding, so a 10% gain and a 10% loss cancel. What the rule returned per trade, with position size taken out of it. It answers whether the edge is in the trades themselves, where the equity curve answers what the account did with them.
Equity En = E0 n∏i=1fi The account compounded through every trade — the whole balance goes into the next position. Drawn net of fees as a solid line and gross of them as a dotted one. The account itself, which is the only figure a reader actually ends up with. The gap between the two lines is what the fees took, and it widens with every trade rather than staying a fixed share.
Cumulative Fees Fn = n∑i=1(Ci φ + Xi φ) Fee charged on the way into each position and again on the way out, at rate phi, on the capital actually committed — so the bill grows with the account as well as with the trade count. The cost of trading, in the account's own units. It is the one line here that only ever rises, and the one a rule cannot trade its way out of.
Rolling Sharpe Sharpet = mean(rdaily)sd(rdaily) × √365 Mean daily return over its deviation, annualized on a 365-day year because crypto has no weekend. Taken on the account marked to market every bar — open positions included, not just closed ones — and read off at each trade's exit. Return per unit of the swing it took to get it. It is the heaviest weight in the composite score, because an account that doubled calmly and one that doubled violently are not the same result.

Real Data

51/ 100Composite score

Metrics Per Trade

Final Metrics

Scores

Resampled Data

58/ 100Composite score

Metrics Per Trade

Final Metrics

Scores