Trend

WMA 20 200 Crossover

The golden cross on weighted averages: buys when the 20-bar weighted moving average crosses above the 200-bar and sells when it crosses back below.

Total score 58/ 100 rank 05 / 42 · trend 05 / 20

How It Works

  1. Compute two weighted moving averages of the close: a fast one over 20 bars and a slow one over 200.
  2. Buy when the fast WMA crosses above the slow one — the same golden-cross idea as the 50/200 simple averages, but weighted, so both lines turn toward new prices sooner.
  3. Sell when the fast WMA crosses back below the slow one. The 200-bar anchor makes this the slowest of the crossover pairs: few trades, each meant to last a whole trend.

Worked example. WMA20 climbs from 97.8 to 98.4 while WMA200 edges from 98.1 to 98.2 — the fast average has crossed above the slow one, so buy. Months later WMA20 slides back under WMA200 and the position is sold.

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.

Weighted Moving Average (WMA)
A moving average where newer prices count more: the latest close gets weight N, the one before N − 1, down to weight 1 for the oldest. That makes it react to a turn in price sooner than a plain average.
WMAN = N · Pt + (N−1) · Pt−1 + … + 1 · Pt−N+1N + (N−1) + … + 1
Example: With N = 3 and closes 100, 102, 104 (oldest to newest): (1·100 + 2·102 + 3·104) / (1 + 2 + 3) = 616 / 6 ≈ 102.67 — pulled closer to the latest price than the plain average of 102.

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

55/ 100Composite score

Metrics Per Trade

Final Metrics

Scores

Resampled Data

62/ 100Composite score

Metrics Per Trade

Final Metrics

Scores