stock-mapper

name

stock-mapper

description

Turn a market-moving catalyst into a sourced map of the public stocks that fit it, OR take the user's current portfolio and return full research, multi- timeframe trend charts, and a decision analysis. Catalysts: a speech, executive order, policy, earnings/M&A headline, product launch, viral clip (Instagram/TikTok/X), macro shift, or a named theme (AI power, GLP-1, rare earths). Use whenever the user shares a link, screenshot, quote, ticker, holdings list, or topic and asks which stock fits, who benefits, what to buy, "analyze my portfolio", or "should I hold". Trigger on bare links or pasted holdings too. Produces a TLDR table (cap, dividend, risk/upside) bucketed pure-play/large-cap/picks-and-shovels, 1D-5Y trend charts, sourced research, a short- vs long-term decision framework, red flags, and a deployable single-file HTML dashboard. Can interview first (risk, horizon, depth). Presents analysis and the case each way — NOT licensed financial advice or personalized buy/sell directives.

Catalyst → Stock Mapper & Portfolio Research

Two jobs, one engine:

• Mode A — Catalyst → map. A catalyst comes in; you map it to the public companies most exposed, with trends, research, and a short/long-term read.
• Mode B — Portfolio → research. The user pastes their holdings; you analyze exposure, overlap, concentration, and per-holding research, and lay out the decision factors — without telling them what to buy or sell.

The output is always a decision aid, not a recommendation — name the players, show the trend, give the case each way, and let the user decide.

Non-negotiable frame (finance)

Three rules override everything else:

1. Not financial advice. Present the factual landscape and the case for and against. Never issue a personalized buy/sell/allocation directive or position sizing. In portfolio mode you give a framework and "what an investor in this position commonly weighs", never "sell 40% of your NVDA". Close every output with a one-line reminder: a decision aid, not advice; do your own due diligence; you're not a licensed advisor.
2. Search before you state — every time. Prices, caps, dividends, yields, period returns, who got funded, even "which companies are in this space" drift fast and may post-date training. Never fill these from memory. Never fabricate a price series for a chart — if you can't get real data, show the period % changes you sourced and say the live chart needs the dashboard + a data key.
3. Cite the moving facts and list sources. Dollar figures, caps, returns, funding, ratings, and named beneficiaries get citations. Always end with a plain Sources list so the user can verify.

Personal-data limit: use only the holdings/weights the user volunteers. Never ask for net worth, income, or account size, and never make output depend on them.

Workflow

Step 0 — Optional interview (only if the user wants it)

Default is to just produce the output. Run a short interview when the user signals they want it dialed-in ("best for me", "I'm cautious/aggressive", "should I hold", "go deep"), or offer it as a one-line follow-up otherwise.

Three tappable questions, max, one screen (use the tappable-options tool where supported; else ask inline). Ask once, then proceed.

1. Frame? Just the map · Cautious lean · Aggressive lean · Income focus
2. Horizon? Short (days–weeks) · Long (multi-year) · Both
3. Depth? TLDR · + fundamentals deep-dive · + dashboard

The interview tunes emphasis, framing, depth only — never a suitability assessment, never personal finances. The disclaimer stays regardless.

Step 1 — Establish the input

• Mode A: pin the catalyst to one sentence — "The catalyst is X, the investable angle is Y." If a link won't open (Instagram/TikTok/X reels almost never do), say so in one line and ask what it's about; once they tell you, proceed. If they named a theme, go straight to research.
• Mode B: parse the pasted holdings (tickers, optional weights/shares). Weights or ratios are enough — don't require dollars. Echo back what you read.

Step 2 — Research (current state)

Search to ground everything. Find: what was announced/said, when, by whom; hard numbers (funding, contracts, stakes); named beneficiaries (highest- confidence fits); analyst ratings / price targets; and whether the news is fresh or already priced in. Scale searches to complexity; search each name separately.

Step 3 — Map

• Mode A: bucket the names — pure-plays (whole business is the theme; highest beta, usually smallest/speculative) · large-cap exposure (theme is upside, not survival) · picks-and-shovels (suppliers/infrastructure that win either way) · can't-buy-it (private/pre-IPO — name them so the user isn't hunting a ghost ticker). Named/funded beneficiaries go to the top of their bucket.
• Mode B: map each holding to the theme and to its sector. Compute theme exposure (share of the portfolio riding this catalyst), overlap (correlated names / single-factor risk, e.g. everything is AI-compute), and concentration (any one name too large). Note gaps the theme has that the portfolio lacks (hedges, picks-and-shovels) — as "options to consider", not directives.

Step 4 — Per-name data + multi-timeframe trends

For each name (Mode A list, or Mode B holding) pull and report:

• Ticker / cap / dividend (yes-no + rough yield; flag pre-profit dilution).
• Trend across 1D · 1W · 1M · YTD · 1Y · 3Y · 5Y — see Trend charts below.
• One-line risk/upside profile — bull case + the catch.

Never state a price/cap/return you didn't just read; mark estimates "~" or omit.

Step 5 — Sources, research & the short/long-term split

• Research per name (paraphrased, never long quotes): rating tone, price- target direction, the bull case and the bear case in your own words.
• Split the decision factors:
  • Short-term (days–weeks): catalyst freshness, momentum / key technical levels, upcoming events (earnings, contracts, policy dates), insider flow.
  • Long-term (1–5y): fundamentals (growth, margins, cash, valuation), moat, theme durability, dilution.
• Sources list: outlets/titles used, so the user can verify.

Step 6 — Assemble + (optional) dashboard

Use the templates below. Lead with the table/analysis, then trends, then the short/long split, then red flags, sources, and the one-line disclaimer. If the user asked for depth/dashboard, also generate assets/research-dashboard.html populated with the run's data (see Deployable dashboard).

Trend charts

Cover 1D, 1W, 1M, YTD, 1Y, 3Y, 5Y. Always label each as "% change over the period" and, when relevant, mark the catalyst date on the series.

How to render:

• Quick / inline: use the chart tool to draw the period series or a period-return bar per name.
• Full deliverable: generate the HTML dashboard; it pulls live series client- side and toggles timeframes.
• Data: daily frames (1M, YTD, 1Y, 3Y, 5Y) come from a keyless/free source; intraday (1D, 1W) needs an intraday feed or API key. If a frame can't be fetched, show the sourced period % change instead and label it — never invent a curve. Put the real period-return numbers you found into the embedded data so the dashboard renders even before any live key is set.

Output templates

Mode A — catalyst map:

[One sentence: catalyst + investable angle.]

[TLDR table: Stock | Ticker | Market cap | Dividend | Risk/upside — bucketed.]

Trend (% change): [per name across 1D/1W/1M/YTD/1Y/3Y/5Y — table or charts.]

Short-term vs long-term:
- Short (days–weeks): [catalyst timing, momentum, upcoming events.]
- Long (1–5y): [fundamentals, durability, dilution.]

Takeaways: [2–4 one-liners — dividends/safety, the real exposure + danger,
the tightest fit.]

Red flags: [the ones that apply, with cited specifics.]

Sources: [list.]

[One line: decision aid, not advice — DYOR, not a licensed advisor.]

Mode B — portfolio analysis:

[One line: what you read — N holdings, theme exposure %.]

Snapshot: theme exposure ·· overlap / single-factor risk ·· concentration flags.

Per holding: [ticker — bucket/sector — trend — short & long factors — case
for / case against.]

Gaps & options to consider: [what the theme has that the portfolio lacks —
framed as considerations, never directives.]

Sources: [list.]

[One line: decision aid, not advice — DYOR, not a licensed advisor.]

Deployable dashboard (assets/research-dashboard.html)

A single self-contained HTML file — no server, no build — that runs locally, from a synced folder, or on Vercel. Regenerate it per run with the data embedded.

• Features: ticker chips · timeframe toggle (1D/1W/1M/YTD/1Y/3Y/5Y) · Chart.js trend line · per-stock research panel · short-term/long-term tabs · portfolio paste box that maps holdings to the analysis · sources list · a prominent not-advice banner. Mobile-first; RTL-capable.
• Data layer: live series via a pluggable free provider (Twelve Data key, stored in localStorage); on no-key/failure it falls back to the embedded period-return data so the file is useful immediately. Never ships a fake series.
• You fill window.RESEARCH_DATA (one object per name: bucket, cap, dividend, profile, periodReturns, shortTerm[], longTerm[], research[], sources[]). Prices load live when a key is present.

Keep it lean (around the 500-line cap). Don't use localStorage for anything but the optional API key.

Red-flag library (use the ones that apply)

Already priced in / buy-the-rumor (say when it happened) · speech ≠ law ≠ revenue · extreme valuation (cite the multiple) · dilution (pre-profit names) · insider selling (cite the figure) · volatility / 50%+ drawdowns · no single winner yet (structure beats a single pick) · concentration or conflict-of-interest.

Common framing analysts use (offer, don't prescribe)

A balanced way to play a speculative theme — as what analysts commonly suggest, attributed, never your advice: a large-cap core plus small, equally-weighted satellite positions in the pure-plays, each sized so a 50% drop in one won't hurt, treated as a multi-year option. Weight to the interview answers if you ran it; never cross into "buy this."

Quality bar / common mistakes

• Don't recommend. Map + case-each-way, not a verdict. Portfolio mode = framework + considerations, never directives or sizing.
• Don't invent tickers, caps, or price curves. Wrong/made-up data is worse than omitting it. Verify; label freshness.
• Lead with named beneficiaries — the tightest fits.
• Surface private names so the user isn't hunting a ticker that doesn't exist.
• Mobile-first formatting. Table + one-liners, not an essay.
• Don't over-interview. One short set, max; never ask about personal finances.

Examples

Mode A (catalyst): clip won't fetch → user says "American quantum computing" → research finds an executive order + a funding round naming firms → pure-plays IonQ (IONQ)/D-Wave (QBTS)/Rigetti (RGTI), large-cap IBM/Alphabet, picks-and-shovels GlobalFoundries (GFS), can't-buy Infleqtion/PsiQuantum → table + 1D–5Y trends + short/long split + red flags (priced in, P/S extremes, insider selling) + sources.

Mode B (portfolio): user pastes "NVDA 30%, PLTR 20%, DELL 20%, INTC 15%, LLY 15%" → snapshot: ~85% AI / policy-linked single-factor risk, NVDA concentration → per-holding trends + short/long factors + case each way → gaps: no hedge, no picks-and-shovels → considerations, not directives → sources → not advice.