Stock Screener Alternative

A stock screener alternative that thinks for you.

Traditional screeners apply static filters: P/E below X, dividend above Y. AdaptingAlpha applies adaptive AI that updates its factor weights based on what's actually working — and personalizes the ranking to your investor profile.

Screeners give you the same ranking as everyone else, frozen on rules that someone made up years ago. AdaptingAlpha is a screener alternative built on a different idea: factor weights should evolve. When low-P/E stocks are winning, weight goes up. When high beta is losing, weight comes down. Your profile shapes the final ranking. The same query returns a different answer next month — because the market changed and the model noticed.

The Learning Loop

Recommend → Track → Learn → Improve

The flywheel that makes AdaptingAlpha sharper every week.

01

Recommend

AdaptingAlpha scores hundreds of US stocks and A-shares against your investor profile, then surfaces personalized rankings.

02

Track

Every recommendation is saved with its entry price. Outcomes are measured against live market prices, not backtests.

03

Learn

Factor multipliers update after each resolved outcome. Winning signals get promoted; losing ones get penalized.

04

Improve

Next week's rankings are sharper because the model is informed by what actually worked, not what looked good on paper.

Inside AdaptingAlpha

Everything an AI investing platform should have

Why It's Different

Adaptive AI vs. traditional stock tools

Most stock apps apply static filters. AdaptingAlpha applies a model that updates itself.

AdaptingAlpha

  • Filters update from results
  • Personalized to your profile
  • Tracks every recommendation
  • Cross-device sync
  • Conversational AI advisor
  • Multi-market (US + A-shares)

Typical screeners

  • Static rules
  • One ranking for everyone
  • No accountability
  • Local-only
  • Search only
  • One market

FAQ

Frequently asked questions

What's wrong with traditional screeners?

Three things: (1) Filters are static — the same rules from 5 years ago apply today even if those signals stopped working. (2) Everyone gets the same ranking — no personalization. (3) No accountability — screeners surface candidates but never track whether their suggestions panned out.

How is AdaptingAlpha different?

Three matching answers: (1) Factor weights update from real recommendation outcomes — adaptive, not static. (2) Rankings are personalized to your profile (risk, horizon, growth vs value, dividend preference, sector interest). (3) Every recommendation is saved with entry price and resolved against live market prices, with the win rate published in our Trust Center.

Can I use it like a traditional screener too?

Yes. Ask the AI Advisor things like "find dividend stocks above 4% yield with low beta" and it'll search the full universe and return matches. The Personalized Picks page gives you a daily auto-ranked feed without typing anything.

Does it have all the factors I'm used to?

It tracks 15+ factors including EPS growth, revenue growth, P/E, P/B, ROE, beta, dividend yield, momentum, volume, 52-week range, and several A-share-specific factors. Each factor has a multiplier the learning engine updates from outcomes.

Is this financial advice?

No. Like any screener, this is a discovery tool — informational only. You're responsible for every investment decision. The advantage is that you can see real tracked outcomes in the Trust Center before deciding to trust the rankings.

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AdaptingAlpha is for informational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Recommendations are generated by a machine learning model and may be incorrect. Always do your own research before investing.