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API Overview

Base URL & Versioning

https://data.financialresearch.gov/hf/v1

The API version (v1) is required in the URL path. Currently only v1 is available.

Protocol & Format

  • All requests use HTTPS
  • All responses are JSON (except /categories which returns CSV)
  • No authentication, API keys, or registration required
  • No documented rate limits — data updates at most once per day; avoid hammering the API

Response Patterns

Most endpoints return one of:

  • An array of [date, value] pairs for time series data
  • A JSON object keyed by mnemonic for full series (timeseries + metadata)
  • A JSON array of objects for search/metadata listings

Timeseries array

[
  ["2013-03-31", -3.0],
  ["2013-06-30", -2.0],
  ["2013-09-30", -2.05]
]

Null values appear as null in the value position.

Full series object

{
  "FPF-ALLQHF_NAV_SUM": {
    "timeseries": {
      "aggregation": [["2013-03-31", 1143832916], ...]
    },
    "metadata": {
      "mnemonic": "FPF-ALLQHF_NAV_SUM",
      "description": {
        "name": "All funds: net assets (sum dollar value)",
        "description": "...",
        "notes": "...",
        "vintage_approach": "Current vintage, as of last update",
        "vintage": "",
        "subsetting": "None",
        "subtype": "None"
      },
      "schedule": {
        "observation_period": "Quarterly",
        "observation_frequency": "Quarterly",
        "seasonal_adjustment": "None",
        "start_date": "2013-03-31",
        "last_update": ""
      }
    }
  }
}

Mnemonic Format

Mnemonics are unique identifiers for each time series. Format varies by dataset:

Dataset Pattern Example
fpf FPF-{SCOPE}_{METRIC}_{STAT} FPF-ALLQHF_NAV_SUM
ficc FICC-{SERIES} FICC-SPONSORED_REPO_VOL
tff TFF-{SERIES} TFF-DLRINDEX_NET_SPEC
scoos SCOOS-{SERIES} varies

Mnemonics are case-insensitive in query parameters (the API normalizes to uppercase in responses).

Subseries (label)

Each mnemonic can have multiple subseries labeled:

  • aggregation — the main data series (always present, default returned)
  • disclosure_edits — version of the data with certain values masked for disclosure protection

Installation

uv add requests pandas

No dedicated Python client exists — use requests directly.