About Stocker

Stocker started as a personal project to spot unusual movement, volume changes, and emerging trends before they are easy to notice manually.

Why this approach

The data pipeline here is intentionally built to minimize AI dependency in the core workflow: data collection, filtering, enrichment, querying, and report generation.

Relying on an LLM for exact required outputs is like expecting exact values from a raffle draw. If you are serving raffle numbers at all, you should tightly control the pool of possible outputs first.

Personal context

Many early stock ideas come from structured research, paid tools, or disciplined screening. Stocker aims to make that workflow lighter and more repeatable.

I am subscribed to one paid research service myself (at the cheapest tier), and from experience, some of my best-performing picks came from independent research outside paid services.

Stocker is not financial advice. Reports and alerts are for informational purposes only and may be incomplete, delayed, or inaccurate. Always make your own investment decisions.