multi-factor-strategy

What This Skill Does

The multi-factor-strategy skill for OpenClaw is a specialized assistant designed to empower quantitative researchers and traders. It acts as an expert interface for the quantcli library, streamlining the process of creating, validating, and managing complex multi-factor stock selection models. By translating user requirements into structured YAML configuration files, it ensures consistency and reproducibility in financial analysis. The skill covers the entire lifecycle, from defining fundamental financial screening criteria (such as ROE or P/E ratios) to technical price condition screening and advanced factor weight fusion techniques. Whether you are building a custom value-growth hybrid strategy or integrating standardized alpha factors, this tool handles the syntax and logic, allowing you to focus on strategy performance.

Installation

To enable this skill, run the following command in your terminal: clawhub install openclaw/skills/skills/wumu2013/multi-factor-strategy

Ensure you have the underlying framework installed by running: pip install quantcli

Verify that the environment is set up correctly by executing quantcli --help.

Use Cases

• Strategy Prototyping: Rapidly experiment with different factor combinations, such as mixing momentum signals with fundamental value metrics.
• Portfolio Optimization: Define custom weightings for multiple alpha factors to achieve specific risk-adjusted returns.
• Backtesting Preparation: Generate clean, error-free YAML files that are ready to be piped into quantcli for execution against historical market data.
• Factor Library Management: Organize external factor definitions and integrate them modularly into main strategies.

Example Prompts

1. "Create a multi-factor strategy YAML that selects stocks with ROE over 15%, a P/E ratio between 10 and 25, and a 10-day MA crossover signal."
2. "Help me build a strategy that uses a 0.4 weight for alpha_001, 0.3 for alpha_008, and 0.3 for a custom momentum expression where I look at the 20-day return."
3. "Can you check my strategy configuration? I am getting a syntax error in my factor weights definition for my fundamental screening criteria."

Tips & Limitations

• Modularity: Always prefer referencing external .yaml files for factor definitions to keep your main strategy file clean and maintainable.
• Normalization: When mixing factors with different scales, use the zscore normalization method in the ranking section to ensure no single factor disproportionately dominates the scoring.
• Limitations: This tool generates configuration files for quantcli. It does not execute real-time trading or connect to brokerage APIs; it is intended for research and analytical data filtering purposes only.