Loading public projects…
Project detail
Stockclipper
Built with Codex · Next.js · Prisma · Clerk · Market data · SaaS
Discover early consumer trends, test their economic materiality, and track whether the signal follows through.
Stockclipper scans consumer, search, commerce, app, social, and news signals for retail investors. It ranks source independence, purchase intent, Wall Street awareness, ticker materiality, risk evidence, and later stock follow-through instead of treating raw buzz as an investment signal.
Feedback ask
Which evidence best helps you decide whether a surfaced signal belongs in a research queue, and where does the scoring still feel opaque?
Janne Ikola
@janne
Project overview
- Who this project is for
- Self-directed retail investors who want an explainable research queue built from early consumer signals rather than social-media hype alone.
- The problem it solves
- Consumer trends often reach analyst reports only after the information edge has narrowed, while most viral signals never become material business or stock-market outcomes.
- Key features
- — Multi-source consumer and market signal discovery
- — Economic materiality and ticker exposure scoring
- — Wall Street awareness and information-parity tracking
- — Visible negative evidence and saturation risks
- — 7-, 30-, and 90-day outcome follow-through
- — Research playbooks, watchlists, and edge-closing alerts
AI tool: Codex
Report project
Suggestions
Community feedback
Concrete improvements, with the owner decision visible when it is available.
Share one concrete improvementSuggestion form
Checking sign-in status…
No suggestions yet
Be the first to leave a structured improvement idea for this project.