Trend

Golden Cross 50 200

Buys on the golden cross — the 50-bar average crossing above the 200-bar average — and sells on the death cross, when it crosses back below.

Total score 62/ 100 rank 02 / 42 · trend 02 / 20

How It Works

  1. Compute two simple moving averages: a medium 50-bar one and a long 200-bar one.
  2. Buy on the golden cross — the 50-bar average crossing above the 200-bar: the medium-term trend has overtaken the long-term one, the classic sign a major uptrend is underway.
  3. Sell on the death cross, when the 50-bar average crosses back below the 200-bar.

Worked example. The 50-bar average has been climbing and prints 101.2 today against a 200-bar average of 101.0, having been below it yesterday — a golden cross, so buy. Much later the 50-bar average slips back under the 200-bar — the death cross — and the position 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.

Simple Moving Average (SMA)
The plain average of the last N closing prices: add them up, divide by N. It smooths out bar-to-bar noise so the underlying direction is easier to see — a rising SMA means recent prices sit above where they used to be.
SMAN = P1 + P2 + … + PNN
Example: With N = 3 and closes 100, 102, 104 the SMA is (100 + 102 + 104) / 3 = 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

59/ 100Composite score

Metrics Per Trade

Final Metrics

Scores

Resampled Data

64/ 100Composite score

Metrics Per Trade

Final Metrics

Scores