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Stocks research

Deep-dive research for US Stocks, HK Stocks, and ETFs with multi-tab detail pages.

Find it at: /stock/:symbol (US), /stock-hk/:symbol (HK), /etf/:symbol (ETF). Reach any of these via top-bar symbol search, watchlist click, or chat-card ticker.


1. US Stock detail page (6 tabs)

The US Stocks detail page (/stock/:symbol) is the deepest research surface in Alphio. Tabs are URL-driven via ?tab= so any view is shareable.

TabURL paramWhat's inside
Overview?tab=overview (default)Quote, headline figures, company description, key ratios, peers, recent news strip.
Technical?tab=technicalInteractive K-line chart, indicators (MA, RSI, MACD, Bollinger), and pattern detection.
Financial?tab=financialIncome statement, balance sheet, cash flow, key indicators — see section 2 for sub-tabs.
Should I Buy?tab=should-i-buyAlphio AI's structured Buy / Hold / Avoid view with reasoning bullets and supporting signals.
News & Events?tab=news-eventsTicker-tagged news, earnings dates, congressional and institutional trades.
Stock Price Prediction?tab=stock-price-predictionShort and medium-horizon AI price-path projections with confidence bands.

Stock detail page


2. Financial sub-tabs (5)

The Financial tab splits into five sub-tabs, controlled by ?tab=financial&sub=....

Sub-tabURL paramWhat's inside
Summarysub=summary (default)Single-page financial overview with the top-line numbers from each statement.
Key Indicatorssub=key-indicatorsMargins, returns (ROE / ROA / ROIC), leverage ratios, valuation multiples vs peers.
Income Statementsub=income-statementRevenue, costs, operating income, net income — quarterly and annual.
Balance Sheetsub=balance-sheetAssets, liabilities, equity — quarterly and annual.
Cash Flowsub=cash-flowOperating / investing / financing cash flow — quarterly and annual.

Each sub-tab supports multi-period comparison and CSV export from the table actions.

Financial sub-tabs


3. HK Stock

HK Stocks live at /stock-hk/:symbol.

  • Tabs. A single Overview tab is shipped today; the layout matches US Overview (quote, headline figures, news strip).
  • Differences from US. No multi-tab Financial / Should-I-Buy / Price Prediction views — for those, ask Alphio AI directly in chat.
  • Routing. Triggered when getAssetDetailPath sees locale === 'HK'.

For an Alphio AI deep-dive on a Hong Kong name, open a chat session and ask — Alphio AI pulls the same data sources behind the scenes.


4. ETF

ETFs live at /etf/:symbol.

  • Single-page detail. Quote, performance bands, top holdings, sector / region weights, expense ratio, AUM, recent flows.
  • No multi-tab depth. Use chat for deeper drill-downs (e.g. holdings overlap, factor exposure).
  • Cross-link. Holdings rows link straight into the underlying ticker's detail page.

5. Asking Alphio AI

Stock research scales further when you stop tabbing and just ask. A few starting prompts:

  • "Should I buy NVDA?" — opens a Should-I-Buy answer with a verdict card.
  • "Compare AAPL and MSFT cash flow over the last 4 quarters." — returns a side-by-side Cash Flow table.
  • "Why did TSLA drop today?" — pulls today's news, fundamentals delta, and flow signals.
  • "Forecast SPY over the next 3 months." — emits a Price Prediction card.
  • "Earnings reminders for my watchlist this week." — surfaces an Earnings Reminder card.

See How to chat for the full prompt patterns, and Chat cards for the cards these prompts emit.


6. Adding to watchlist

You can add any symbol to your watchlist without leaving research.

  • From the detail page. Click the + / Watchlist toggle in the header — it persists immediately.
  • From a chat card. Snapshot, Rating, and Should-I-Buy cards expose an add-to-watchlist action; one click adds the ticker.
  • From the symbol search modal. Each result row has a + affordance on hover.

To see the full watchlist, open /watchlist.


Agent Instructions: Querying This Documentation

If you need information not on this page, you can query the docs dynamically by sending a GET request with the ask query parameter:

GET https://docs.alphio.ai/research/stocks-research.md?ask=<question>

The question should be specific, self-contained, and written in natural language. The response includes a direct answer plus relevant excerpts and sources.