AstronAlgo
About

AstronAlgo is built around top-down market intelligence and shared scoring.

The product is moving toward an institutional workflow: Global Bias and thematic context feed market-impact maps, those maps inform scan rankings, and single-stock analysis reads the same final score row.

Top-down research stackGlobal Bias + thematic context + shared scan rows + single-stock detail.
What We Build

A research workspace for stock selection and market context.

AstronAlgo combines single-symbol analysis, bulk ranking, Global Bias, thematic context, and watchlist workflows in one app surface.

How It Thinks

The score is useful only when the drivers are visible.

The UI shows company quality, earnings, seasonality, news impact, macro, sector context, and top-down overlays instead of hiding everything behind one number.

Data Policy

Backend truth first. No invented market-impact areas.

Tailwinds, headwinds, and mixed areas are shown when the backend maps them. If the data is missing, the app shows an empty state instead of guessing.

Operating Model

Institutional direction, product-speed execution.

  1. Normalize the inputsCompany data, prices, macro, thematic context, and classified news land in backend snapshots.
  2. Score onceBulk scan and single analysis use the same public score row instead of separate logic.
  3. Expose the driversThe UI shows the score, the backdrop, and the reasons without inventing missing data.