SMA Crossover Strategy with Monte Carlo Tuner by AJSwogger
By AJSwogger
Performance Metrics
- Author: AJSwogger
- Symbol: NASDAQ:PYPL
- Timeframe: 1 minute
- Net P&L: +22.06 USD (+0.02%)
- Win Rate: 46.1%
- Profit Factor: 2.178
- Max Drawdown: 4.63 USD (0.00%)
- Total Trades: 52
Description
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 modes1) Deterministic mode (baseline) • MC = OFF • You choose (fast, slow) explicitly (default 8/34) • Behavior is stationary and repeatableThis 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 onlineKey point:This is not grid search. It’s stochastic sampling with early stopping with time control (default 35 s)