edge-strategy-reviewer

You can automate trading strategy review by running a Python script that evaluates your strategy draft for edge plausibility, overfitting risk, sample size adequacy, and execution realism. This automated evaluation applies specific scoring criteria to identify potential issues before implementation.

Execution realism validation checks whether a trading strategy's expected performance holds up under actual market execution conditions. It is part of an automated strategy review that evaluates edge plausibility and overfitting risk to ensure the strategy draft is practical.

You validate sample size adequacy by running an automated review script on your strategy draft file. The evaluation checks if your trading strategy has sufficient sample size for reliability, alongside assessing overfitting risk and execution realism.

Yes, you can use a Python script with PyYAML to evaluate strategy drafts against 8 criteria for quality control. The automated strategy review assesses edge plausibility, overfitting risk, sample size adequacy, and execution realism.

You need Python with PyYAML installed to run the automated strategy review. Provide the path to your strategy draft file in YAML format, and the script will evaluate it for edge plausibility, overfitting risk, sample size adequacy, and execution realism.

Automated strategy review may not suit trading strategies lacking structured YAML draft files or those outside standard risk management workflows. The review requires Python and PyYAML to evaluate edge plausibility and overfitting risk against specific scoring criteria.