Futures Positioning: CFTC Commitment of Traders

Weekly positioning snapshots (Tuesday; released Friday at 3:30 PM ET) for CME / ICE / CBOT futures, broken down by trader category. Free and public domain. Used in Ch4 NB 10 for sentiment/positioning features and in Ch8 / Ch16 for futures strategy inputs.

Dataset

Report type	Trader categories	Products
TFF (Traders in Financial Futures)	Dealers, Asset Managers, Leveraged Money	Financial futures (ES, NQ, 6E, ZN, …)
Disaggregated	Commercials, Managed Money, Swap Dealers	Commodity futures (CL, GC, ZC, …)

Product mapping + report-type dispatch live in the ml4t.data.cot library (ml4t.data.cot.PRODUCT_MAPPINGS). The downloader here wraps that library and persists one parquet per product to the local data store.

Download

# Default: all products in PRODUCT_MAPPINGS, 2020 through current year
uv run python data/futures/positioning/cot_download.py

# Subset of products + longer history
uv run python data/futures/positioning/cot_download.py --products ES,NQ,CL,GC --start-year 2010

# Override output root
uv run python data/futures/positioning/cot_download.py --data-path /tmp/ml4t-data

Directory Layout

$ML4T_DATA_PATH/futures/positioning/cot/
└── {PRODUCT}.parquet    # one parquet per product code (e.g., ES.parquet)

Schema

Columns vary by report type but always include:

Column	Notes
`product`	Exchange product code (ES, CL, GC, …)
`report_type`	CFTC report that produced the row
`report_date`	Tuesday snapshot date
`open_interest`	Total open interest

Per-trader long/short/net columns by report type:

Financial (TFF): dealer_long/short/net, asset_mgr_long/short/net, lev_money_long/short/net
Commodity (disaggregated): commercial_long/short/net, managed_money_long/short/net, swap_long/short/net

Loading

from data import load_cot, list_cot_products

# Everything available locally
df = load_cot()

# Subset + date filter
df = load_cot(products=["ES", "NQ"], start_date="2020-01-01", end_date="2024-12-31")

# Enumerate what's been downloaded
list_cot_products()  # -> ['CL', 'ES', 'GC', 'NQ', ...]

load_cot() uses diagonal_relaxed concat so financial and commodity products can be combined in one frame despite their different schemas.

Release Lag

CFTC publishes reports Friday at 3:30 PM ET; the snapshot is as-of Tuesday of the same week (3-day lag). For daily-bar backtests a conservative +6 calendar-day availability lag from Tuesday is standard.

Consumers

Ch4 NB 10 — positioning analysis, z-scores, contrarian signals
Ch8 — futures_features.py (positioning feature family)
Ch16 — futures strategies using CoT signals

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