Your edge Compounded
Adjust any variable. Watch your equity curve update in real time. Monte Carlo simulation (a statistical model that tests your strategy across thousands of random scenarios) — every run is honest, not cherry-picked.
THIS PANEL COMPOUNDS A RETURN YOU SUPPLY. IT IS NOT A DOCUMENTED CAP FIGURE. FOR SCALE: IN THE BACKTEST, BITCOIN’S REAL TRADES IN ORDER AT 1% RISK (MIDDLE OF TEN VERSIONS) TURNED $1,000 INTO ABOUT $21,200 FROM JANUARY 2018 TO SEPTEMBER 2026: ABOUT 0.1% A DAY ON AVERAGE, AND NOT IN A STRAIGHT LINE.
How the model works
Each run generates a statistically random sequence of wins and losses based on your win rate. Re-randomised on every slider move — no cherry-picked curves.
Risk % applies to the current account balance after every trade. Winners increase dollar risk. Losers reduce it. Exactly how professional position sizing works.
Expectancy = (Win Rate × Average Win) − (Loss Rate × Average Loss), measured in R. Above zero, the system earns more than it loses per unit of risk. The CAP backtest runs +3.12R per trade: a 78.6% win rate, an average win of +4.19R and an average loss of only −0.80R, because many losers end at the move’s end before the stop is reached.
The CAP Backtest preset resamples all 10,899 S and A grade trades of the four-coin backtest (BTC, ETH, SOL and LINK, 2018 to 2026, all costs in), so every run carries the real mix of losers, small winners and long runners. The 1-in-5-Wrong preset shows the same rules with one call in five deliberately wrong. The protocol was built over 10+ years in live markets; the numbers quoted here are backtested, not an audited live track record. See the full methodology.
The edge is real.
The system is learnable.
The CAP Framework is the decision engine that produced these metrics. Five sequential gates. One clear entry signal. Built for perpetuals traders who are done guessing.
Questions, Answered Plainly
Frequently asked questions
What is the CAP Framework win rate?
Backtested on 2018 to 2026 prices with every cost included, 78.6% of 10,899 S and A grade CAP trades finished in profit (Bitcoin 80.1%, n=3,031). Winners are held until the bigger move ends, so the average winning trade made +4.19R and the average losing trade cost 0.80R. These are modelled versions of Charles's calls, not account statements, and every trade is downloadable on the Protocol Results page.
How does the compound trade calculator work?
The calculator runs a Monte Carlo simulation — a statistically random sequence of wins and losses based on your stated win rate. Risk is applied as a percentage of the current account balance after each trade, compounding gains and losses realistically. Each slider move re-randomises the sequence for honest, non-cherry-picked projections.
What is trading expectancy and how is it calculated?
Expectancy = (Win Rate × Average Win in R) − (Loss Rate × Average Loss in R). For the CAP backtest (78.6% won on n=10,899 S and A grade trades, average win +4.19R, average loss −0.80R), expectancy = (0.786 × 4.19) − (0.214 × 0.80) = +3.12R per trade. The median trade is a smaller +1.53R, because a few very large winners lift the average, and it remains a backtest of modelled calls rather than a live track record: with one call in five deliberately wrong, the average falls to about +2.0R.
What does an average win of +4.19R mean in trading?
Under the tested CAP rules there is no take-profit ladder: the full position is held until the bigger move ends, with the stop beyond the last 4-hour swing. Across the 10,899 backtest trades the average winning trade made +4.19R and the average losing trade cost 0.80R. If you risk $100, the average winner returned about $419 and the average loser cost about $80; the median trade made +1.53R ($153). Averages like these are pulled up by a few very large winners, which is why the calculator resamples every real trade instead of using a single average.
What is Monte Carlo simulation in trading?
A Monte Carlo simulation generates a statistically random sequence of wins and losses based on your stated win rate. Unlike fixed-sequence projections, it produces a realistic distribution of possible equity curves — each run is different, showing the range of outcomes your edge could produce across hundreds of trades.