Query the OFR (Office of Financial Research) Hedge Fund Monitor API for hedge fund data including SEC Form PF aggregated statistics, CFTC Traders in Financial Futures, FICC Sponsored Repo volumes, and FRB SCOOS dealer financing terms. Access time series data on hedge fund size, leverage, counterparties, liquidity, complexity, and risk management. No API key or registration required. Use when working with hedge fund data, systemic risk monitoring, financial stability research, hedge fund leverage or leverage ratios, counterparty concentration, Form PF statistics, repo market data, or OFR financial research data.
Installation
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Query the OFR (Office of Financial Research) Hedge Fund Monitor API for hedge fund data including SEC Form PF aggregated statistics, CFTC Traders in Financial Futures, FICC Sponsored Repo volumes, and FRB SCOOS dealer financing terms. Access time series data on hedge fund size, leverage, counterparties, liquidity, complexity, and risk management. No API key or registration required. Use when working with hedge fund data, systemic risk monitoring, financial stability research, hedge fund leverage or leverage ratios, counterparty concentration, Form PF statistics, repo market data, or OFR financial research data.
license
MIT
metadata
{"skill-author":"AlterLab","version":"1.0.0"}
OFR Hedge Fund Monitor API
Free, open REST API from the U.S. Office of Financial Research (OFR) providing aggregated hedge fund time series data. No API key or registration required.
Base URL:https://data.financialresearch.gov/hf/v1
Quick Start
import requests
import pandas as pd
BASE = "https://data.financialresearch.gov/hf/v1"# List all available datasets
resp = requests.get(f"{BASE}/series/dataset")
datasets = resp.json()
# Returns: {"ficc": {...}, "fpf": {...}, "scoos": {...}, "tff": {...}}# Search for series by keyword
resp = requests.get(f"{BASE}/metadata/search", params={"query": "*leverage*"})
results = resp.json()
# Each result: {mnemonic, dataset, field, value, type}# Fetch a single time series
resp = requests.get(f"{BASE}/series/timeseries", params={
"mnemonic": "FPF-ALLQHF_LEVERAGERATIO_GAVWMEAN",
"start_date": "2015-01-01"
})
series = resp.json() # [[date, value], ...]
df = pd.DataFrame(series, columns=["date", "value"])
df["date"] = pd.to_datetime(df["date"])
Authentication
None required. The API is fully open and free.
Datasets
Key
Dataset
Update Frequency
fpf
SEC Form PF — aggregated stats from qualifying hedge fund filings
Quarterly
tff
CFTC Traders in Financial Futures — futures market positioning
Monthly
scoos
FRB Senior Credit Officer Opinion Survey on Dealer Financing Terms
Quarterly
ficc
FICC Sponsored Repo Service Volumes
Monthly
Data Categories
The HFM organizes data into six categories (each downloadable as CSV):
size — Hedge fund industry size (AUM, count of funds, net/gross assets)
