COT reports: Compensated (spread) positions held by leveraged money managers in NZD/USD FX futures: NZ DOLLAR - CHICAGO MERCANTILE EXCHANGE (number of contracts) - United States - CFTC - Weekly
This series is part of the dataset: NZD/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), compensated (spread) positions held by leveraged money managers in NZD/USD FX futures of the kind "NZ DOLLAR - CHICAGO MERCANTILE EXCHANGE" were 810 contracts on 29 September 2026, compared to 759 on 22 September 2026.
Sample. There are 717 records overall in the weekly series displayed in the plot above. The time range covered by the series stretches from January 2013 to September 2026.
History. Here's a peek at some statistics we calculated on the full sample: positions averaged 1,045 contracts; they reached their highest level of 13,337 on 9 December 2025; they recorded a bottom of 3 on 5 November 2013.
Latest values
| Date | Value - Number of contracts |
|---|---|
| 2026-09-15 | 776.0 |
| 2026-09-22 | 759.0 |
| 2026-09-29 | 810.0 |
Tip. To simplify complex analyses, we group time series into worksheets and datasets. By scrolling down, you will find how we arranged further material related to the statistics found here.
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Series Metadata
| Field | Value |
|---|---|
| Description | Compensated (spread) positions held by leveraged money managers in futures on the NZD/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: "NZ DOLLAR - CHICAGO MERCANTILE EXCHANGE |
| FSR temporal aggregation code | LW1 |
Series in the same data set
Discover the other time series included in this data set.