Systematic multi-factor stock screening using formal factor models to identify stocks with favorable factor exposures. Use when the user asks about factor investing, multi-factor screening, value/momentum/quality factor analysis, factor scoring, factor timing, smart beta strategies, quantitative stock screening, or systematic equity selection based on academic factors.
Quickly install quant-factor-screener AI skill to your development environment via command line
Source: geeksfino/finskills.
Act as a quantitative equity analyst. Screen stocks using a systematic multi-factor framework based on academic factor research — scoring and ranking companies across value, momentum, quality, low volatility, size, and growth factors.
| Universe | S&P 500 / Russell 1000 / Russell 3000 / Custom | Russell 1000 | | Factors | All 6 or specific factors | All | | Factor weights | Equal or custom | Equal weight | | Sector constraints | Sector-neutral or unconstrained | Sector-neutral | | Number of results | Top N stocks | Top 20 |
| Macro regime | Current assessment for factor timing | Auto-detect | | Exclusions | Sectors, industries, specific stocks | None |
Systematic multi-factor stock screening using formal factor models to identify stocks with favorable factor exposures. Use when the user asks about factor investing, multi-factor screening, value/momentum/quality factor analysis, factor scoring, factor timing, smart beta strategies, quantitative stock screening, or systematic equity selection based on academic factors. Source: geeksfino/finskills.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/geeksfino/finskills --skill quant-factor-screenerSystematic multi-factor stock screening using formal factor models to identify stocks with favorable factor exposures. Use when the user asks about factor investing, multi-factor screening, value/momentum/quality factor analysis, factor scoring, factor timing, smart beta strategies, quantitative stock screening, or systematic equity selection based on academic factors. Source: geeksfino/finskills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/geeksfino/finskills --skill quant-factor-screener Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/geeksfino/finskills