How It Works
- Track the parabolic stop from each bar's high and low: it trails below price while the trend is up, creeping closer every bar and faster with each new high.
- Buy when the close is above the stop — the trend has flipped up and the stop has moved beneath price to trail it.
- Sell when the close falls back through the stop. Because the stop accelerates, a long-running trend gets stopped out on a much smaller pullback than a young one would.
Worked example. The stop flips below price at 100 and the strategy buys. As the rally extends the stop climbs from 90 toward 118, tightening with each new high, until a pullback to 118 touches it and closes the trade — the gain is kept because the stop had ratcheted up behind it, not because the trend was called at the top.
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.
- Parabolic SAR
- A trailing stop that tightens as a trend runs. It starts far below a rising market and steps toward price each bar, covering a fraction of the remaining distance to the highest high reached so far. That fraction — the acceleration factor — begins at 0.02 and rises by 0.02 every time the trend posts a new extreme, capped at 0.2, so a long quiet trend is given room early and squeezed later. When price finally touches the stop, it flips to the other side of price and the trend is considered over — the stop and reverse the name refers to.
- SARt+1 = SARt + α(EP − SARt), α = min(0.02 n, 0.2)
- Example: In a rising market the stop sits at 90 with the highest high (EP) at 100 and α still 0.02, so the next stop is 90 + 0.02·(100 − 90) = 90.2. After several new highs α has grown to 0.10 and the same 10-point gap pulls the stop a full point per bar — the longer the trend lasts, the less room it is given.
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. |