COT reports: Net long positions held by leveraged money managers in EUR/USD FX futures: EURO FX - CHICAGO MERCANTILE EXCHANGE (number of contracts) - United States - CFTC - Weekly
This series is part of the dataset: EUR/USD exchange rate COT reports (CFTC)
Download Full Dataset (.xlsx)Latest updates. According to the Commitments of Traders (COT) reports published by the Commodity Futures Trading Commission (CFTC), net long positions held by leveraged money managers in EUR/USD FX futures of the kind "EURO FX - CHICAGO MERCANTILE EXCHANGE" stood at 3,947 contracts on 31 March 2026, compared to -13,538 on 24 March.
Sample. There are 691 records in the weekly time series shown in the figure above. The series covers the time range extending from January 2013 to March 2026.
History. Check out a few descriptive statistics we calculated on the entire sample: positions reached a maximum of 86,055 contracts on 8 October 2013; they registered a minimum of -170,230 on 24 March 2015; they had an average value of -32,018.
Latest values
| Date | Value - Number of contracts |
|---|---|
| 2026-03-17 | -6952.0 |
| 2026-03-24 | -13538.0 |
| 2026-03-31 | 3947.0 |
Suggestion. For easier exploration, we group indicators into worksheets and datasets. By scrolling down, you will discover how we arranged further material related to the statistics provided here.
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Series Metadata
| Field | Value |
|---|---|
| Description | Net long positions held by leveraged money managers in futures on the EUR/USD exchange rate |
| Country | United States |
| Economic concept | Stock |
| Data type | Quantity |
| Seasonally adjusted | No |
| Deflation method | Not applicable |
| Rescaling | None |
| Measure type | Level |
| Frequency | Weekly |
| Unit | Number of contracts |
| Source | Commodity Futures Trading Commission (CFTC) |
| Source type | Government agency |
| Data licence | Public domain information |
| Other information | Specific future: EURO FX - CHICAGO MERCANTILE EXCHANGE |
| FSR temporal aggregation code | LW1 |
Series in the same data set
Discover the other time series included in this data set.