How significantly can this reduce processing time?

By reducing a candidate pool from roughly 4,000 to 1,300 symbols, this skill can cut historical data download and processing times by approximately 70%.

Does this skill work with the Alpaca API?

Since Alpaca does not natively provide sector data, this skill specifically integrates yfinance to fetch and cache sector metadata into your local symbol database for use in filtering.

What are the database requirements?

The filtering logic requires SQLite version 3.25 or higher to support advanced window functions like ROW_NUMBER() and PARTITION BY.

Why use sector filtering instead of just picking the top volume symbols?

Selecting purely by volume often leads to over-representation in high-activity sectors like Tech or Finance. Sector filtering ensures your strategy evaluates opportunities across the entire market, preventing sector-specific risk.

Per-Sector Trading Candidate Filter

Name: Per-Sector Trading Candidate Filter
Author: smith6jt-cop

bysmith6jt-cop

0•

数据科学与机器学习

Optimizes trading universe selection by applying sector-specific volume filters to ensure a diverse and manageable pool of candidates.

This skill provides a robust framework for reducing massive stock universes into curated, sector-balanced candidate lists for algorithmic trading. By integrating yfinance sector data into a local SQLite database, it employs advanced SQL window functions to filter symbols based on sector-specific volume rankings. It solves the common 'data bottleneck' problem where downloading historical data for thousands of symbols is time-prohibitive, allowing developers to reduce candidate pools by up to 70% while maintaining proportional representation across all 11 standard GICS sectors.

主要功能

01Dynamic filtering logic with configurable min/max sector bounds

020 GitHub stars

03Automated yfinance sector metadata integration and local caching

04Advanced SQL window functions for proportional sector filtering

05Cross-sector diversity preservation to prevent tech/finance over-concentration

06Automated database schema migrations for sector data storage

使用场景

01Reducing historical data ingestion time for large-scale trading strategies

02Optimizing API usage by filtering out low-probability candidates before analysis

03Maintaining sector-neutral portfolios during automated universe selection

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add smith6jt-cop/skills_registry per-sector-candidate-filtering

For use in Claude.ai and ChatGPT

Download Skill