Microproduct data guideintermediate

CFTC Commitments of Traders

Weekly futures positioning by trader category for building commodities, rates, and speculative-position monitors.

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At a glance

Difficulty
Intermediate — some data preparation helps
Size
Small · ≤0.5 GB
Formats
JSON, CSV
Access
API or Download
API key
Not required
Provider
Commodity Futures Trading Commission
Updates
Weekly
Data terms
U.S. Government public data / federal copyright guidance

From source to product signal

Test a product idea in four steps

The COT reports break down open interest for futures markets with enough large traders. Start with one contract in the legacy combined dataset. Categories are regulatory, not strategy labels, and Tuesday positions are published later in the week.

1

Check the setup

  • Python 3.10 or newer
  • A notebook environment such as Jupyter or Google Colab
  • An internet connection
2

Access the data

  1. 1.Open the Commitments of Traders page and the public reporting environment.
  2. 2.Request a bounded page of legacy combined records for one market.
  3. 3.Keep report date, market name, and commercial versus noncommercial long/short.
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3

Run the Python example

Install the packages, then run the notebook cell.

python -m pip install pandas requests

import pandas as pd
import requests

response = requests.get(
    "https://publicreporting.cftc.gov/resource/jun7-fc8e.json",
    params={
        "$limit": 20,
        "$order": "report_date_as_yyyy_mm_dd DESC",
        "contract_market_name": "GOLD",
    },
    timeout=30,
)
response.raise_for_status()
cot = pd.DataFrame(response.json())
print(cot[[
    "report_date_as_yyyy_mm_dd",
    "contract_market_name",
    "open_interest_all",
    "noncomm_positions_long_all",
    "noncomm_positions_short_all",
]].head())
4

Test a useful signal

Track speculative positioning in one futures market

Test whether weekly COT records can power a bounded positioning monitor.

  1. 01Keep report date, market name, open interest, and noncommercial long/short.
  2. 02Compute net noncommercial positioning and note the publication lag from Tuesday.
  3. 03Explain that trader categories are CFTC reporting classes, not a forecast of price direction.

Dataset details

Commodity Futures Trading Commission is a government source. Last verified 2026-08-18. Temporal coverage: 1986-present weekly reports.

Theme

Markets & Economics

Domains

CommoditiesFinanceCapital Markets

Data types

Time SeriesTabular

Tasks

Market MonitoringPositioning AnalysisTrend Analysis

Geography

United States

Formats

JSONCSV

Provider

Commodity Futures Trading Commission

Data terms

U.S. Government public data / federal copyright guidance