monte-carlo

Monte Carlo Simulation Skill

This skill runs a Monte Carlo simulation on a specific strategy using the scripts/monte_carlo_v1.py script. It validates the statistical robustness of a strategy by repeatedly sampling trade returns.

Usage

Invoke with: /monte-carlo <strategy_name> [limit] [iterations] [source]

Examples:

• /monte-carlo scalp_1m_sweep_optimized (Default: 1000 bars, 1000 iterations, bitunix source)
• /monte-carlo scalp_1m_sweep_optimized 5000 (5000 bars)
• /monte-carlo scalp_1m_sweep_optimized 2000 5000 mock (2000 bars, 5000 iters, mock data)

Parameters

• strategy_name (required): Name of the strategy file in config/strategies/ (without .json extension).
• limit (optional): Number of bars to backtest before simulation (Default: 1000).
• iterations (optional): Number of Monte Carlo iterations (Default: 1000).
• source (optional): Data source, 'bitunix' or 'mock' (Default: bitunix).

Prerequisites

• The script scripts/monte_carlo_v1.py must exist.
• Python env must be set up.

Steps

// turbo-all

Step 1: Validate Script and Strategy

Ensure the tool and strategy exist.

$scriptPath = "scripts/monte_carlo_v1.py"
$stratPath = "config/strategies/$strategyName.json"

if (-not (Test-Path $scriptPath)) {
    Write-Error "Monte Carlo script not found at $scriptPath"
    exit 1
}
if (-not (Test-Path $stratPath)) {
    Write-Error "Strategy not found at $stratPath"
    exit 1
}
Write-Host "Ready to simulate $strategyName using $scriptPath"

Step 2: Run Simulation

Execute the python script.

• Defaults are applied if arguments are missing.
• $limit defaults to 1000 if not provided.
• $iterations defaults to 1000 if not provided.
• $source defaults to "bitunix" if not provided.

# Set defaults if variables are null/empty
if (-not $limit) { $limit = 1000 }
if (-not $iterations) { $iterations = 1000 }
if (-not $source) { $source = "bitunix" }

Write-Host "Running Monte Carlo: Strategy=$strategyName, Source=$source, Limit=$limit, Iterations=$iterations"

$env:PYTHONPATH="src"
.\.venv\Scripts\python.exe scripts/monte_carlo_v1.py --strategy $strategyName --limit $limit --iterations $iterations --source $source

Step 3: Interpret Results

The script will output a table.

• Pass Criteria:
  • Prob. of >20% DD should be 0.00%.
  • 95% Max Drawdown should be acceptable for your risk tolerance (e.g., < 20%).
  • 50% Percentile (Median) Equity should be > Starting Balance for a profitable strategy.

On Failure

• If Prob. of >20% DD is high (> 0%), the strategy is too risky.
• If Median Equity is < Start, the strategy has negative expectancy.