Financial news as structured, sourced data

What you get

Every article the pipeline reads is broken into statements: one-sentence facts such as "Nvidia expects to grow at a strong pace again in 2027", each with its sentiment (bullish, bearish or neutral), importance (low, medium, high, ultra), the symbols and sector it concerns, the source URL and domain, the article's post time and, when the article has one, its image.

Statements that report the same development are clustered into topics: "30-year Treasury yield breaks 5%" holds 139 statements from 43 outlets. Topics are grouped into standing themes such as Central banks & rates or Energy. Every 2 hours the API ranks the developments the most outlets picked up.

• Window: a rolling 62 days (captured 1 Oct 2026 11:34 UTC: 75,026 statements, 31,490 topics).
• Freshness: the data is rebuilt about every 2.5 minutes. Today a statement reaches the API a median 14 minutes after its article was published (90th percentile 27 minutes): minutes, not seconds.
• Access: through RapidAPI, with your RapidAPI key.

This site, fintopic.news, is a front page built entirely on the same API.

Quick start

1. Get a key. Pick a plan on RapidAPI: the free plan is enough to try every endpoint. Then copy your X-RapidAPI-Key from the endpoint playground.

2. Make a request. The newest high-importance statements about Nvidia:

curl -G https://finance-pulse.p.rapidapi.com/v2/statements \
  --data-urlencode "symbol=NVDA" \
  --data-urlencode "importance_min=high" \
  --data-urlencode "limit=3" \
  -H "X-RapidAPI-Key: YOUR_RAPIDAPI_KEY" \
  -H "X-RapidAPI-Host: finance-pulse.p.rapidapi.com"

import requests

API = "https://finance-pulse.p.rapidapi.com"
HEADERS = {"X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY", "X-RapidAPI-Host": "finance-pulse.p.rapidapi.com"}

r = requests.get(f"{API}/v2/statements", headers=HEADERS,
                 params={"symbol": "NVDA", "importance_min": "high", "limit": 3})
for s in r.json()["data"]:
    print(s["published_at"][:16], s["sentiment"], s["statement"], f"({s['source_domain']})")

const API = "https://finance-pulse.p.rapidapi.com";
const HEADERS = { "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY", "X-RapidAPI-Host": "finance-pulse.p.rapidapi.com" };

const r = await fetch(`${API}/v2/statements?symbol=NVDA&importance_min=high&limit=3`, { headers: HEADERS });
for (const s of (await r.json()).data) console.log(s.published_at.slice(0, 16), s.sentiment, s.statement);

3. Read the response. One statement, plus the snapshot block every v2 response carries:

{
  "data": [
    {
      "id": "c3341069-59d6-562d-8a9e-935cdc514665",
      "statement": "Amazon is reportedly seeking investors for an $8 billion financing structure for Nvidia chips",
      "published_at": "2026-10-02T10:29:29Z",
      "indexed_at": "2026-10-02T10:42:04.715725Z",
      "sentiment": "bullish",
      "importance": "high",
      "source_type": "news",
      "source_url": "https://finance.yahoo.com/technology/ai/articles/amazon-reportedly-seeks-investors-8-102929408.html",
      "source_domain": "finance.yahoo.com",
      "image_url": "https://s.yimg.com/ny/mysterio/api/01795bc4f58861436819644f026638cbfdd2437e6e71782cc8c2e46b97cf9a8a/ynews/resizefill_w1200/https://media.zenfs.com/en/investorshub_458/35437a5a165ffeadb112d825c6043626.png",
      "symbols": ["AMZN", "NVDA"],
      "entities": [
        {
          "code": "AMZN",
          "kind": "equity",
          "name": "Amazon.com Inc",
          "exchange": "NASDAQ",
          "country": "USA"
        },
        {
          "code": "NVDA",
          "kind": "equity",
          "name": "NVIDIA Corporation",
          "exchange": "NASDAQ",
          "country": "USA"
        }
      ],
      "sectors": ["InformationTechnology"],
      "topic_id": "f14f34e4-ebdc-407a-a189-a1d6ad9134a6",
      "topic_name": "Amazon offloads $8 billion of Nvidia chips to investors",
      "theme_id": "7059ad1e-8ecb-52cc-99fd-c8457a534fda"
    },
    … 2 more
  ],
  "next_cursor": "WzE3OTA5MzM4MjAsImMyZmE0YWU3LWQwNDEtNWEwZi1iNzc1LWNkYjMxYmY2NTlmYyJd",
  "snapshot": {
    "built_at": "2026-10-02T10:45:28.835156+00:00",
    "anchor": "2026-10-02T10:45:28.835156+00:00",
    "window_start": "2026-08-01T10:45:28.835156+00:00",
    "lag_days": 0.0
  }
}

published_at is when the article was published; indexed_at is when the statement entered the API. topic_id links the fact to its development, and next_cursor continues the list. GET /v2/meta lists every accepted filter value.

Prefer Python, or an AI assistant? pip install finance-pulse gives you a Python client and an MCP server for Claude and Cursor: see Use Finance Pulse from Claude, Cursor or Python.

The data model

Counts on topics and themes (statements, sources) cover the 62-day window; total_statements is everything the topic ever held. sources always means distinct outlets (domains), not URLs.

Sentiment is a label on a statement. A symbol's, topic's or theme's sentiment is the count of its statements' labels, and score is (bullish − bearish) / statements. A bearish sentence that names NVDA and AMD counts for both.

Conventions

• Paging. Lists return next_cursor; pass it back as ?cursor= until it is null. Cursors stay valid when the data is rebuilt, so pages never skip or repeat rows. /v2/feed always returns a cursor (see the feed guide).
• Caching. Every response has an ETag. Send it back as If-None-Match and an unchanged answer comes back as an empty 304.
• Errors are application/problem+json: {"title", "status", "detail", "param"}. Any malformed request is a 400, including an unknown query parameter (a typo never silently widens your query); an id outside the window is a 404.
• Repeatable filters. symbol, sector, sentiment and source_type accept several values: ?symbol=NVDA&symbol=AMD or ?symbol=NVDA,AMD (OR).

What this data is, and what it is not

• Symbols are entities, and only equities and ETFs are tickers. Every symbol is a canonical code with a kind: equities and ETFs under their ticker (US plain, NVDA; elsewhere with the exchange suffix, 0700.HK, SAP.DE), and indices, rates, currencies, crypto, commodities, organisations and private companies under short codes (SPX, US10Y, USD, BTC, GOLD, FED, OPENAI). The entities are read by a language model and then resolved; codes the resolver can't place are left out, so symbol counts are conservative. Old codes still filter (MIC finds Micron's MU statements). See the screener guide.
• Sectors are assigned per statement, from its text: the 11 GICS sectors (Energy, Financials, InformationTechnology, …). A sentence about Tesla's view of GDP can be tagged Financials.
• Coverage has a gap. From 20 August to 16 September 2026 news ingestion was down: series over that period show almost no statements. Don't compute baselines across it. GET /v2/meta lists every known outage and delay under incidents.
• indexed_at is point-in-time only from 24 September 2026. Older statements were backfilled and carry the backfill date.
• There is no backtest-ready history. Event studies on published_at are possible but contaminated by look-ahead: a late article is filed under the hour it was published. For honest point-in-time tests, record /v2/feed from day one; that log is your dataset.

Versions and changes

• 2.0.0 (2 Oct 2026). The unprefixed v1 endpoints (/statements, /topics, /themes, /trending, /symbols, /meta) are removed; everything they did is in /v2. The deprecated industry_group parameter and field and /v2/industry-groups are removed too: use sector, sectors and /v2/sectors. /health is unchanged.
• 1.4.0 (2 Oct 2026). /v2/themes takes symbol=, sector= and sort= (size, topics, recent, velocity). Topics carry statements_7d and revision, which changes whenever the topic or its last-7-day statements change: compare it to skip refetching unchanged topics. /v2/symbols returns up to 20,000 rows.
• 1.3.0 (1 Oct 2026). Canonical symbols, in v1 and v2: one code per entity (Micron is always MU, never MIC; SpaceX is SPACEX, not SPCE), and codes that resolve to nothing are no longer listed. v2 statements, topics and themes carry entities (code, kind, name, exchange, country); /v2/symbols rows carry kind and name and take kind= (e.g. kind=equity,etf). Old codes keep working as filters. Faster first /v2/feed call.
• 1.2.2 (1 Oct 2026). sector replaces industry_group (the values always were the 11 GICS sectors): responses carry sectors, filters take sector=, and /v2/sectors replaces /v2/industry-groups; the old names keep working for one version. /v2/meta lists data incidents (outages and delays).
• 1.2.1 (1 Oct 2026). Trending counts distinct outlets instead of URLs (a syndicated article under many URLs is one source). Readable endpoint names and descriptions.
• 1.2.0 (1 Oct 2026). The /v2 API: statement search, feed, time series, symbol and sector screeners, topics and themes with outlets and velocity, trending with newest statements, cursor paging, problem+json errors. The documented v1 calls that had stopped working (/statements?symbol=, ?industry_group=, ?source_type=, ?id= and /symbols) work again; v1 is otherwise unchanged and stays available.

Data incidents (also in GET /v2/meta → incidents): 20 Aug – 16 Sep 2026, news ingestion outage; 26–27 Sep, statement extraction up to a day late; 29 Sep 07:20–10:40 UTC and 30 Sep 14:00–15:00 UTC, short processing delays (nothing missing).