propfirms_optimal_risk

io.github.LuxAlgo/luxalgo-mcp-server · Verify this server

Sweep risk-per-trade over a grid, run the full journey simulation at every point, and report two optima separately: bestByPassProbability (the risk that maximizes a single attempt's chance of passing) and bestByEv (the risk that maximizes expected value across attempts, fees and funded payouts). They usually differ (diverges=true) - and that divergence is the insight: lower risk survives loss limits more often, but EV also weighs the cost of extra attempts and the size of funded payouts, which can favor a different risk. Never present one number as THE optimal risk; report both optima and the trade-off, and let the user choose. The sweep uses common random numbers (the same seed at every grid point), so curves are smooth and the argmax is signal, not Monte Carlo noise. Grid units follow riskMode: percent units for percent modes (default grid 0.1 to 3 in steps of 0.1, i.e. 0.1%-3% per trade), currency per trade for 'fixed-amount' (set min/max/step explicitly). Parametric trader only (riskValue is not a parameter here - the grid supplies it). Cost scales with grid size: one full simulation per point, so ~30 points at the default 10,000 paths takes roughly 10 seconds; use fewer paths or a coarser grid for a first pass, then refine around the optima. UNITS: every *Pct rule field and every percent-mode risk value is in PERCENT UNITS (5 = 5%, 0.5 = 0.5%). The one exception is winRate, which is a FRACTION in [0, 1] (0.55 = 55% winners). Probabilities in results are fractions in [0, 1]. DETERMINISM: identical inputs including `seed` reproduce byte-identical results on any platform. Include the seed and path count when reporting numbers so users can reproduce them exactly; re-run with a few different seeds to gauge Monte Carlo spread. ASSUMPTIONS: every result carries assumptions.flags - dataset-declared rules the engine does NOT simulate (e.g. scaling plans or soft daily lockouts, which make real odds worse than simulated) plus engine simplifications - and assumptions.disclaimer. These are material: always surface the flags and the disclaimer to the user alongside the numbers, never just the headline probability. Results are distributions under stated assumptions, not promises.