Markets by Vikram

Methodology

How the screener score is built, and what it deliberately leaves out.

Every company on Markets by Vikram gets a single 1–99 score built from four explainable inputs, each visible on its own on the stock detail page:

  • Growth — year-over-year quarterly revenue growth.
  • Profitability — trailing twelve-month operating margin.
  • Valuation — trailing P/E ratio, inverted (cheaper scores higher).
  • Momentum — the stock's latest daily change.

The composite score weights growth and profitability most heavily, applies a mild valuation penalty, and nudges for the day's momentum. It is a simple heuristic for exploring a curated universe of companies — not investment advice, and not a claim that any of these dimensions predict future returns.

This project deliberately omits technical indicators like RSI and moving averages, and balance-sheet ratios like debt/equity — those require extra API calls per symbol that would blow through the free-tier rate limits this site runs on.

News sentiment tags

The Bullish/Bearish tag on News headlines is a keyword-count heuristic (src/lib/sentiment.ts), not a machine-learning model or a third-party sentiment API. It counts how many words from a small hand-picked list of bullish terms ("surge", "beat", "upgrade", "revenue growth"...) and bearish terms ("plunge", "miss", "downgrade", "lawsuit"...) appear in the headline and summary; whichever side has more wins, a tie is Neutral.

This is a rough signal, not a claim of real sentiment analysis — it will misread sarcasm, headlines that mix good and bad news, and any phrasing outside its keyword list. It also only reads the words actually in the list, so it undercounts on unfamiliar phrasing rather than guessing. On Insider Trading, the Buy/Sell tag is different in kind: it's a literal read of whether the headline says "buys" or "sells", not a sentiment judgment about the trade.