Guide • Ticker Detail

How to read the Ticker Detail page

This page teaches users what each ticker module means and how to combine Technical Charts, Financials, News, Full History, and model confidence inside a structured research process.

1) Technical Charts

  • Start with trend direction first: higher highs/higher lows means bullish structure; lower highs/lower lows means bearish structure.
  • Check moving averages for context, not as standalone indicators. Price above key averages usually confirms strength.
  • Watch support and resistance zones. If price is near major resistance, upside may be capped even when the model classification is constructive.
  • Use volume to validate moves. Breakouts with low volume are lower-confidence than breakouts with strong volume.

2) Financials

  • Review revenue and earnings trend over multiple periods, not just one quarter.
  • Check margins and cash flow quality. Strong top-line growth with weak cash flow can be a warning.
  • Compare valuation metrics to peers in the same sector to avoid false comfort.
  • Use Financials as context for holding period decisions, while technicals help with timing.

3) News

  • Prioritize high-impact catalysts: earnings, guidance, regulation, legal issues, macro shocks.
  • Check timestamp freshness. Old positive news can already be priced in.
  • Separate facts from opinion headlines. Read source snippets before reacting.
  • If news tone and model output conflict, slow down and wait for confirmation.

4) Full History

  • Check how the model behaved in previous similar conditions, especially high-volatility weeks.
  • Look at confidence trend, not only latest value. Rising confidence over days is stronger than one-day spikes.
  • Review strong/weak streaks and false-positive clusters to calibrate expectations.
  • Use history to set realistic expectations for how much weight the research deserves.

5) Model Output Panel

  • Read model agreement first. When XGBoost, LSTM, and Random Forest agree, output quality is typically better.
  • Treat mixed-model output as a cue for deeper review, not immediate action.
  • Confidence is a quality indicator, not a guarantee. Keep broader risk checks active.
  • If confidence is low and macro risk is high, give the research less weight until conditions improve.