Data Licensing for Funds & Fintechs
Build research and products on top of structured, point-in-time datasets. Deliveries include a simple schema,
a manifest with checksums, and a change log so your work is reproducible.
Who this is for
- Quant & discretionary funds (signal research, knowledge graphs, governance maps)
- Fintech teams (searchable UI, alerts, manager pages, foundations views)
Datasets
Conference Ideas (2011–present; strongest from 2024 →)
Concentrated idea flow from investor conferences and manager events.
- What’s included (high level): event/series, dates, city, session; speaker & firm (normalized); company references with identifiers; timestamps for event and publication (explicit latency); optional direction and thesis tags; links to agenda/deck/transcript when available.
- Cadence: event-driven (busy during conference weeks).
Investor Letters (2013 →)
Manager & fund, letter date/period, title, tags, tickers mentioned, source link, and a snippet (~500 characters) suitable for UI display with attribution and link.
Where rights permit, full text can be licensed under upper tiers.
- Cadence: event-driven with weekly roll-ups.
13F Signals (HFA proprietary)
A signals layer built from public filings (we do not resell raw 13F positions).
- Manager normalization, position changes, concentration metrics, crowding/overlap, simple thematic tags.
Foundations / 990-PF (positions-focused)
Normalized public-equity positions and related holdings from US foundation filings, mapped to managers/issuers, with links back to source documents.
Crosswalk (optional add-on)
A light graph connecting managers, foundations, speakers, and tickers—useful for governance views, provenance, and faster discovery across datasets.
Quick sample payloads
Illustrative JSON snippets. Full 100–500 row samples with schema & manifest available on request.
Conference Ideas — JSON
{
"event_id": "evt_20240506_milken_001",
"series": "Milken",
"event_dt": "2024-05-06T14:30:00Z",
"publish_dt": "2024-05-06T16:05:12Z",
"lag_minutes": 95,
"session_title": "AI & Infrastructure",
"speaker": {"name":"Jane Doe","firm":"Example Capital","speaker_id":"spk_123"},
"company": {"legal":"Acme Corp","ticker":"ACME","figi":"BBG000...","cik":"0000123456"},
"direction": "long",
"themes": ["AI","Capex","Data centers"],
"novelty_flag": true,
"source_url": "https://hedgefundalpha.com/conferences/..."
}Investor Letters — JSON
{
"letter_id": "ltr_2024Q4_example_001",
"manager_id": "mgr_example",
"fund": "Example Partners LP",
"letter_period": "2024-Q4",
"title": "2024 Q4 Letter",
"publish_dt": "2025-01-15T12:00:00Z",
"tickers": ["ABC","XYZ"],
"snippet": "We continue to see attractive risk/reward in...",
"rights_scope": "snippet_only",
"source_url": "https://hedgefundalpha.com/letters/..."
}13F Signals — JSON
{
"manager_id": "mgr_example",
"filing_period": "2024Q4",
"ticker": "XYZ",
"action": "new",
"weight_pct": 2.3,
"weight_delta_bps": 230,
"top10_flag": true,
"crowding_quantile": 0.82
}Foundations / 990-PF — JSON
{
"foundation_id": "fnd_abc",
"fiscal_year": 2024,
"issuer": "Acme Corp",
"cusip": "004123AA0",
"cik": "0000123456",
"mv_usd": 1250000,
"asset_class": "Public Equity",
"source_url": "https://irs.gov/..."
}Letters — CSV (micro-sample)
letter_id,manager,fund,letter_period,title,publish_dt,tickers,snippet,source_url
ltr_2024Q4_example_001,Example Manager,Example Partners LP,2024-Q4,2024 Q4 Letter,2025-01-15T12:00:00Z,"ABC|XYZ","We continue to see...",https://hedgefundalpha.com/letters/...
ltr_2023Q3_example_002,Another Manager,Alpha Fund,2023-Q3,2023 Q3 Letter,2023-10-20T09:30:00Z,"DEF","Macro headwinds easing...",https://hedgefundalpha.com/letters/...Parquet is our canonical format; CSV/NDJSON are available for quick QA or stream-style ingestion.
Delivery & Formats
- Parquet (recommended) as canonical; CSV sample included; NDJSON available.
- Transport: S3 pre-signed links or shared S3 path; secure HTTPS; Snowflake share on request.
- Schema pack:
schema.json,data_dictionary.md,manifest.json(checksums). - Point-in-time discipline: snapshot at ingest; corrections appended with a versioned change log (no silent rewrites).
Cadence & Latency
Content is event-driven by nature (some days many updates, some days none).
We include both event and publish/ingest timestamps so teams can model lag explicitly.
