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Symbol | Expiration UTC | Last price | Volume | Open interest |
|---|---|---|---|---|
MMA FMH0027! | 2027-03-19 | - | 0 | 0 |
MMA FMZ0031! | 2031-12-19 | - | 0 | 0 |
MMA FMH0028_Y | 2028-03-17 | - | 0 | 0 |
MMA FMH0028_Y-MMA FMH0027_Y | 2027-03-19 | - | 0 | 0 |
MMA FMH0028_Y-MMA FMU0027_Y | 2027-09-17 | - | 0 | 0 |
The capture-server-received timestamp expressed as the number of nanoseconds since the UNIX epoch.
The order quantity.
The matching-engine-received timestamp expressed as the number of nanoseconds since the UNIX epoch.
The channel ID assigned by Databento as an incrementing integer starting at zero.
The record type. Each schema corresponds with a single rtype value.
The order ID assigned at the venue.
The publisher ID assigned by Databento, which denotes dataset and venue.
A bit field indicating event end, message characteristics, and data quality.
The numeric instrument ID.
The matching-engine-sending timestamp expressed as the number of nanoseconds before ts_recv.
The event action. Can be Add, Cancel, Modify, cleaR book, Trade, Fill, or None.
The message sequence number assigned at the venue.
The side that initiates the event. Can be Ask for a sell order (or sell aggressor in a trade), Bid for a buy order (or buy aggressor in a trade), or None where no side is specified by the original source.
The requested symbol for the instrument.
The order price expressed as a signed integer where every 1 unit corresponds to 1e-9, i.e. 1/1,000,000,000 or 0.000000001.
ts_recv | ts_event | rtype | publisher_id | instrument_id | action | side | price | size | channel_id | order_id | flags | ts_in_delta | sequence | symbol |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2025-06-11T00:00:00.000000000Z | 2025-06-11T00:00:00.000000000Z | 160 | 97 | 7105599 | R | N | 0 | 2 | 0 | 8 | 0 | 0 | SB FMN0025! | |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874000Z | 160 | 98 | 7105599 | R | N | 0 | 2 | 0 | 8 | 0 | 0 | SB FMN0025! | |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874000Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 1 | 2 | 50000000183917 | 0 | 334566 | 1018663 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874001Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 1 | 2 | 50000000183965 | 0 | 334566 | 1018664 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874002Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 1 | 2 | 50000000184529 | 0 | 334566 | 1018665 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874003Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 1 | 2 | 50000000191170 | 0 | 334566 | 1018666 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874004Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 2 | 2 | 50000000215922 | 0 | 334566 | 1018667 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874005Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 1 | 2 | 50000000279372 | 0 | 334566 | 1018668 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874014Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 1 | 2 | 50000000373833 | 0 | 334566 | 1018669 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874018Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 2 | 2 | 50000000373840 | 0 | 334566 | 1018670 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874019Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 5 | 2 | 50000000362697 | 0 | 334566 | 1018671 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874020Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 1 | 2 | 50000000372651 | 0 | 334566 | 1018672 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874021Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 1 | 2 | 50000000373381 | 0 | 334566 | 1018673 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874022Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 1 | 2 | 50000000289201 | 0 | 334566 | 1018674 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874023Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 3 | 2 | 50000000327844 | 0 | 334566 | 1018675 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874024Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 2 | 2 | 50000000329692 | 0 | 334566 | 1018676 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874025Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 4 | 2 | 50000000372324 | 0 | 334566 | 1018677 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874026Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 1 | 2 | 50000000184070 | 0 | 334566 | 1018678 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874027Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 26 | 2 | 50000000345481 | 0 | 334566 | 1018679 | SB FMN0025! |
2025-06-11T07:30:00.188245566Z | 2025-06-11T07:30:00.000874028Z | 160 | 98 | 7105599 | T | A | 16.400000000 | 5 | 2 | 50000000368000 | 0 | 334566 | 1018680 | SB FMN0025! |
Need to see more data for MSCI All Country World Total Return (TRF) Futures? You can extract historical data and save it as a DBN, CSV, JSON, or Parquet file. Read our API guide ->
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