Quant analytics
Monte Carlo simulation and the rolling Sharpe ratio, explained simply.
Two quant tools turn your journal into forward-looking risk numbers: Monte Carlo answers "what else could these trades have done?", rolling Sharpe answers "is the edge still alive right now?".
Monte Carlo Simulation
Your equity curve is one shuffle of your trades. Monte Carlo replays them 500 times in random order and draws the whole family of outcomes:
- Shaded bands : the outer band holds 90% of simulated paths, the inner band 50%. Your realistic range of futures with this exact trade distribution.
- Dashed line : your actual curve, so you see where reality sits inside the possibility cloud.
- Re-simulate reshuffles all 500 paths; Expand opens the chart full screen.
How to use it: if a meaningful share of simulated paths visit drawdowns your sizing cannot survive, the problem is the sizing, not bad luck. The insight line under the chart summarizes the median outcome and the tail risk.
Rolling Sharpe Ratio (20 trades)
For every point in your history, the mean result of the last 20 trades divided by their standard deviation. In plain words: recent edge per unit of recent chaos. The chart appears once you have at least 20 trades in scope; click a point to open the last trade of its window.
- Above 0.3 (the faint dashed line marked Tradeable edge) reads as a tradeable edge; the curve's color shifts greener as it strengthens and red when the edge is gone. The Average line is your mean over every window, the level to compare today against.
- Falling Sharpe with a flat equity curve means variance is rising even if money is not yet leaving: an early warning the market regime and your strategy are drifting apart.
Why R makes this possible
Both tools work because every trade is normalized to R. Position size noise is removed, so shuffling and windowing compare like with like.