Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Guides users through building multi-factor stock selection strategies and outputs them as runnable YAML configuration files for quantcli. Covers factor selection, screening conditions, weight allocation, and inline or external Alpha101 factor references.
The guided workflow handles factor expression syntax and weight configuration in one conversation, producing a complete quantcli-compatible YAML file without manual trial and error.
When to use it
- Build a value-growth hybrid screener using ROE and P/E conditions
- Combine Alpha101 built-in factors with custom momentum expressions
- Generate a ready-to-run YAML strategy file without writing config manually
- Tune factor weights for fundamental vs technical score blending
- Screen stocks by moving average position before applying factor ranking
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Create a momentum strategy that picks the top 20 stocks
- 1Clarify holding period and desired selection size
- 2Select momentum and volume ratio as primary factors
- 3Define screening conditions to exclude loss-making stocks
- 4Assign factor weights and set zscore normalization
- 5Output a complete strategy YAML with output limit set to 20
A complete YAML file ready to run with: quantcli filter run -f strategy.yaml --top 20
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.