Hedge Fund Monitor

SkillMonitoring & ops

A skill for monitoring & ops by lamm-mit.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Hedge Fund Monitor skill

What this skill tells your AI

The instructions your AI receives, as published by lamm-mit/scienceclaw in skills/hedgefundmonitor/SKILL.md and read by ahel’s review.

OFR (Office of Financial Research) Hedge Fund Monitor REST API. Free, no authentication required. Provides regulatory data from SEC Form PF, CFTC futures positions, and FICC repo market.

Base URL

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

Available Datasets

EndpointSourceDescription
/pfdataSEC Form PFHedge fund AUM, leverage, liquidity, strategy
/cftcdataCFTCFutures/options positions by trader category
/ficcdataFICC/DTCCRepo market volumes and rates

API Usage

Form PF Data (Hedge Fund Fundamentals)

import requests

BASE = "https://data.financialresearch.gov/hf/v1"

# Get available series/metrics
r = requests.get(f"{BASE}/pfdata/series")
series = r.json()
print([s["seriesId"] for s in series])

# Fetch a specific series (e.g., total AUM)
r = requests.get(f"{BASE}/pfdata/series/data", params={
    "seriesId": "pf_total_nav",     # Net Asset Value
    "startDate": "2020-01-01",
    "endDate": "2024-12-31",
    "frequency": "quarterly"
})
data = r.json()

# Available Form PF series include:
# pf_total_nav          - Total AUM across reporting funds
# pf_gross_leverage     - Gross leverage ratios
# pf_net_leverage       - Net leverage ratios
# pf_liquidity_profile  - Fund liquidity metrics
# pf_counterparty_conc  - Counterparty concentration
# pf_strategy_breakdown - AUM by strategy (equity L/S, macro, credit, etc.)
# pf_redemption_terms   - Redemption notice periods, gates

CFTC Futures Data

# Trader category positions (large trader reporting)
r = requests.get(f"{BASE}/cftcdata/series/data", params={
    "seriesId": "cftc_hf_net_positions",  # Hedge fund net futures positions
    "commodity": "equity_index",
    "startDate": "2023-01-01",
    "endDate": "2024-12-31"
})

# Available CFTC series:
# cftc_hf_net_positions   - HF net long/short in futures
# cftc_hf_gross_long      - Gross long positions
# cftc_hf_gross_short     - Gross short positions
# cftc_leverage_ratio     - Leverage by contract type

FICC Repo Market Data

# Repo market participation by hedge funds
r = requests.get(f"{BASE}/ficcdata/series/data", params={
    "seriesId": "ficc_hf_repo_volume",
    "startDate": "2023-01-01",
    "endDate": "2024-12-31"
})

# Available FICC series:
# ficc_hf_repo_volume     - HF repo borrowing volumes
# ficc_hf_repo_rates      - Weighted average repo rates
# ficc_clearing_volumes   - Total FICC clearing volumes

Response Format

{
  "seriesId": "pf_total_nav",
  "description": "Total Net Asset Value - All Reporting Funds",
  "unit": "billions USD",
  "frequency": "quarterly",
  "data": [
    {"date": "2024-09-30", "value": 4823.6},
    {"date": "2024-06-30", "value": 4712.1},
    {"date": "2024-03-31", "value": 4598.4}
  ]
}

Full Workflow Example

import requests
import json
from datetime import datetime

BASE = "https://data.financialresearch.gov/hf/v1"

def get_hf_series(series_id, start="2020-01-01", end=None):
    if end is None:
        end = datetime.now().strftime("%Y-%m-%d")
    r = requests.get(f"{BASE}/pfdata/series/data", params={
        "seriesId": series_id,
        "startDate": start,
        "endDate": end
    })
    r.raise_for_status()
    return r.json()

# Fetch leverage and AUM data
leverage = get_hf_series("pf_gross_leverage")
aum = get_hf_series("pf_total_nav")

# Correlate with market stress periods
for period in leverage["data"]:
    print(f"{period['date']}: Leverage = {period['value']}x")

Use Cases for Scientific Research

  • Systemic risk analysis: Track leverage buildup before market disruptions
  • Strategy evolution: How hedge fund strategies shift over economic cycles
  • Repo market stress: FICC data shows funding market pressures
  • Cross-market analysis: Correlate HF positioning with commodity/biotech sector movements

Data Coverage

  • Form PF: Quarterly, from 2012 (JOBS Act requirement)
  • CFTC: Weekly Commitments of Traders, from 1986
  • FICC: Daily repo data, from 2014
  • Update frequency: Quarterly (PF), weekly (CFTC), daily (FICC)
  • Authentication: None required
  • Rate limits: None published; be reasonable (< 100 req/min)

Signals

GitHub stars
242
Forks
42
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
hedgefundmonitor-lamm-mit
Source
github.com/lamm-mit/scienceclaw