OPEN-SOURCE SCRIPT
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)
• 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)
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免責聲明
這些資訊和出版物並非旨在提供，也不構成TradingView提供或認可的任何形式的財務、投資、交易或其他類型的建議或推薦。請閱讀使用條款以了解更多資訊。