StockDNA — Know a Stock at a Glance
10 fundamental factors. One simple visual health profile.
What it does
StockDNA makes stock analysis simple and visual. Instead of digging through dozens of financial metrics, StockDNA evaluates a company across 10 key fundamental factors and turns the results into an easy-to-understand visual health profile. Quickly see where a stock is strong, where it needs attention, and what is driving its overall score. Built for investors who want to understand a business faster, compare companies more easily, and make better-informed decisions.
Free stock analysis for any US stock or ETF. StockDNA scores 2,000+ signals across fundamentals, valuation, technicals, momentum, sentiment, and risk into one 0-100 DNA score, plus plain-English breakdowns, an investing screener, and side-by-side stock comparisons — built for retail investors and traders.
Every company has a unique financial DNA. StockDNA analyzes 2,000+ signals across fundamentals, valuation, sentiment, momentum and risk to give you institutional-grade insights in seconds. Browse the market by persona — penny stocks, growth, value, and more — each ranked by DNA Score. Every factor orbits the composite score and feeds it in real time. Click any one to see why it moves the needle. We bypass legacy charts and endless financial ratios, delivering immediate visual clarity. See company health instantly with 10 composite category scores mapped into a dna-web layout. Our scoring engine converts multi-factor quantitative models into plain-English answers. Get an institution-grade…from stockdna.app
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Commerce · 26d ago · equitybee.com
Launched alongside, August 2026
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Life & fun · 10d ago · louisabraham.github.io
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com