Filter stock universes by price, financial, and custom factors.
npx skills add https://github.com/xingwudao/open-xquant --skill screen-factors
Please help me install this Agent Skill. Skill: screen-factors Source: https://github.com/xingwudao/open-xquant/tree/main/agent/skills/screen-factors Command: npx skills add https://github.com/xingwudao/open-xquant --skill screen-factors
Manually filtering large stock universes using multiple factor types (price, financial, custom) is time-consuming and prone to human error for quant researchers and AI coding agents building candidate lists for trading strategies.
Use the screen-factors skill to generate a list of top 10 US large-cap stocks with the highest 60-day momentum and lowest 20-day volatility as of 2024-12-31.
High-intent search queries and answers about installing and using this skill.
Stock screening for quant research filters large symbol universes using price-based, financial statement, and custom factors. You can set rebalance dates, ranking thresholds, and missing value rules to generate reproducible candidate lists.
Filtering a stock universe by momentum and volatility involves applying price-based factor screening with configurable threshold rules. You set a rebalance date and rank stocks to extract high-momentum, low-volatility candidates for backtesting workflows.
Yes, custom user-defined factors can be used alongside financial statement factors like PE, PB, and ROE. The screening supports simultaneous filtering across price-based, financial, and custom factor types for multi-factor strategy workflows.
Missing value handling during factor screening is configurable, allowing you to define rules for how stocks with incomplete factor data are treated. This ensures reproducible filtered candidate outputs across different rebalance dates.
Yes, multi-factor candidate selection supports configurable rebalance dates to ensure reproducible screened outputs. This allows quant researchers to align filtered stock lists precisely with historical backtesting workflow requirements.
santoosaraujoFilter stock universes by PE, PB, and ROE metrics across A-share, HK, and US markets.
adennngEvaluates portfolio strategies by executing fusion policies and backtesting final weights.
samChang72Analyze stock trends with technical indicators and backtesting tools.
santoosaraujoEvaluate financial factor predictive validity via IC/IR analysis and quantile backtesting.
