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.
Recommend
AdaptingAlpha scores hundreds of US stocks and A-shares against your investor profile, then surfaces personalized rankings.
Track
Every recommendation is saved with its entry price. Outcomes are measured against live market prices, not backtests.
Learn
Factor multipliers update after each resolved outcome. Winning signals get promoted; losing ones get penalized.
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
AI Advisor
Conversational AI that takes your portfolio, watchlist, and profile into account when recommending picks.
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Personalized Picks
Daily rankings of stocks that match your risk, horizon, and goals — adjusted by the learning engine.
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Track Record
Every recommendation is logged with entry price and resolved against live market data.
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Portfolio Brain
Live P&L plus AI commentary on concentration, market exposure, and risk balance.
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Daily Briefing
What changed for the AI today — market regime, learning updates, and recommendation changes.
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Trust Center
Public win rate, average return, and AI vs S&P 500 comparison from real tracked picks.
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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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