Module 9 · Lesson 10 of 12 · Futures · About 5 minutes

The Commitments of Traders Report: Who Holds Futures Positions

On this page
  1. What you will learn
  2. What is the COT report?
  3. What are the categories?
  4. COT diagram
  5. How are positions read?
  6. What this does not tell you about COT data
  7. Method in Practice
  8. Check yourself
  9. Reflect on your own process
  10. Sources

Before you read: Futures Contract Specifications: Size, Tick, Multiplier and Months

What you will learn

What is the COT report?

How could you learn, in broad terms, who holds positions in a futures market?

The Commitments of Traders report is published weekly by the US Commodity Futures Trading Commission. It summarizes positions held by large traders who must report to the agency, grouped into categories. The data is usually as of the close of business on Tuesday and released on Friday at 3:30 p.m. Eastern Time, with holidays shifting the schedule, so it is several days old when it appears.

What are the categories?

Is a farmer hedging a crop the same kind of participant as a fund following trends?

The report comes in several formats. The original “legacy” format splits reportable positions into commercial traders, generally those using futures to hedge a business, and noncommercial traders. Newer formats split further, and the categories depend on the report. The Disaggregated report, for physical commodities such as energy, metals and agriculture, uses producer/merchant/processor/user, swap dealers, managed money (registered commodity trading advisors and commodity pool operators, plus some unregistered funds) and other reportables. The Traders in Financial Futures report, for currencies, Treasuries and stock indexes, uses dealer/intermediary, asset manager/institutional, leveraged funds and other reportables. Smaller positions are grouped as nonreportable. The categories are based on how traders are classified, which is not always a clean match to what each one is doing.

COT diagram

Fictional weekly net positions of two COT groups moving in opposite directions. Managed money and producer/merchant net positions mirror each other around zero; data is as of Tuesday. Not real data. Illustrative diagram constructed for teaching. Not real market data.

Illustrative diagram constructed for teaching. Not real market data.

The diagram shows two fictional weekly net position lines over a year: a managed money line that rises and a commercial line that falls by a similar amount, mirroring each other around zero. A note marks that the data is as of each Tuesday. All values are made up.

How are positions read?

If a group holds 200,000 long contracts and 150,000 short, what is its net position?

Net position is longs minus shorts for a category: 50,000 net long in that example.

Here is a fictional, annotated row from a Disaggregated report:

Category (fictional) Long Short Spreading
Managed money 200,000 150,000 30,000

The spreading column holds the part of these traders’ positions that is matched long and short, for example across contract months. The long and short columns hold only what is left over, so spreading does not enter the net figure: 200,000 − 150,000 = 50,000 net long. Producer/merchant rows have no spreading column, and the Traders in Financial Futures report uses different categories, so compare rows only within the same report. Readers chart net positions over time, compare them with open interest, and note when a category’s position is large relative to its history. Those are descriptions of where positions stood on a given Tuesday. A large net position can grow larger, stay large for a long time, or shrink, and the report does not say why traders hold what they hold.

What this does not tell you about COT data

  • What happened after the Tuesday the data was collected.
  • Why any group holds its position, or whether it is hedged elsewhere.
  • Whether a large position will change. History shows every pattern.
  • Nothing here suggests buying, selling or holding based on any COT reading.

Method in Practice: a hypothesis to test, not a signal

Fictional example. John, Harbor Index futures, the prices, times, costs and results are all invented for teaching. This shows how a written plan can be built and tested. It is not a recommendation, and nothing here says how often this idea works.

Try it on a real chart. Test this idea yourself on past sessions with bar replay. Keep your own count, including the days with no trade.

The idea. The COT report shows positions by trader category, published with a lag (this lesson). John writes one hypothesis about it and counts the cases. He doesn't trade it.

John's hypothesis: "When large speculators' net position in Harbor Index futures is at a 52-week extreme, the next 4 weeks move against them more often than not."

Three outcomes (invented numbers: this shows how to count, not how the method performs)

  • Cases in 6 years: 9 extreme readings

  • What followed: 5 moved against the speculators, 4 didn't

  • Decision: 9 cases can't support a rule. No trades. Keep logging

Show the count

9 readings at a 52-week extreme. 4 weeks later: 5 moved against the speculators' position, 4 moved with it. John's journal: "Five out of nine is a coin flip with a small sample. Logging new cases as they come."

Test it yourself

  • Write the hypothesis, the time window and what "moved against" means, before counting.
  • Use the report's publication date, not its as-of date, so the test only uses what was known.
  • Count every case, including the ones that went the other way.

Where it breaks

  • The report is published days after its as-of date.
  • Trader categories are broad and can hide different strategies.
  • A few cases can't separate a pattern from chance.

Reflection question: Which of your trading beliefs have you written as a hypothesis and actually counted?

Check yourself

  1. Why is the COT report several days old when it is released? Hint: what day is the data from?
  2. A category holds 80,000 longs and 120,000 shorts. What is its net position? Hint: longs minus shorts.
  3. Why might a category label not match what a trader in it is actually doing? Hint: how are traders classified?

Reflect on your own process

For your own notes; there is no score and no right answer.

  1. When you note a COT figure, do you record the report family, the as-of Tuesday and the release date together?
  2. How does your process keep a category label separate from any assumption about why those traders hold positions?
  3. Where would you check the CFTC's definitions before comparing two COT categories in your notes?
  4. Which of your trading beliefs have you written as a hypothesis and actually counted?

Sources

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