SMA Crossover Strategy with Monte Carlo Tuner

Core logic
• Two signals:
• FAST SMA
• SLOW SMA
• Trade rule:
• FAST > SLOW → long
• FAST < SLOW → short
• Nothing else. No indicators stacked on top.

⸻

Two operating modes

1) Deterministic mode (baseline)
• MC = OFF
• You choose (fast, slow) explicitly (default 8/34)
• Behavior is stationary and repeatable

This is your control experiment.

⸻

2) Monte Carlo mode (adaptive discovery)
• MC = ON
• The script:
• Samples (fast, slow) pairs randomly from bounded integer ranges
• Simulates trades for each pair in parallel
• Tracks (gross profit, gross loss, trade count)
• Computes PF = GP / GL
• Promotes best-so-far online

Key point:
This is not grid search. It’s stochastic sampling with early stopping with time control (default 35 s)