Trades - Futures

The BMLL Trades dataset provides the definitive factual record of past trading activity. It is a granular, chronological record of every single trade that has been executed in the market for a given instrument, available across multiple execution venues and trading mechanisms, including on and off exchange, lit and dark liquidity sources. By incorporating trade amendments, high-granularity timestamps, and consistent trade condition codes, the BMLL Trades dataset provides the most detailed view of historical trading activity available.

The core content of trade data includes:

  • Timestamp: The precise time the trade occurred, often with microsecond or nanosecond precision.

  • Ticker Symbol: The identifier for the security traded.

  • Trade Price: The price at which the trade was executed.

  • Trade Volume: The number of shares or contracts exchanged.

Product Overview

  • Price, volume and time of execution and publication for every trade in a given market

  • Exchange trade condition codes, and MMT flags (where available) included

  • A normalised view of trade information across all major futures venues

  • Linked Trades identified where supported by the venue (e.g. ASX24’s combinationTradeId

  • Participant IDs included where provided by the venue

  • Trades which originate from an implied order identified

  • BMLL Market State provides a normalised representation (of which there are 14 distinct values) of the trading phase the market is in, on a per-listing basis. Alongside this we present the exchange description to ensure maximum fidelity.

  • Timestamps at or exceeding venue matching engine precision (nanosecond or microsecond)

  • Amended or cancelled trades included

  • Aggressor side identified for lit trading using BMLL Level 3 order book data

Product Description

  • Asset Classes: Futures

  • Coverage: Americas, APAC and EMEA

  • Data available from: 2017

  • Delivery mechanisms: SFTP / S3 / Azure Storage / Snowflake

  • ​​Available via: BMLL Data Feed and BMLL Data Lab