Commodity Trading Advisors (CTAs)

Capturing alpha and optimising execution across global derivatives and futures markets requires clean, high-resolution historical data. But processing, normalising, and storing fragmented order book data across various international exchanges is highly complex and resource-intensive.

BMLL removes this barrier by delivering harmonised, nanosecond-precision historical order-book data and analytics. This empowers CTAs to backtest systematic models with absolute precision, uncover unique microstructure signals, and refine execution strategies without building or maintaining costly data infrastructure.

Key Capabilities Capture Structural Alpha and Fine-Tune Derivatives Execution

Operating in highly liquid yet volatile global derivatives markets requires deep insight into order book behaviour. BMLL provides CTAs with the granular transparency needed to understand liquidity dynamics, minimise slippage, and validate trading strategies across varying market regimes.

Alpha & Signal Generation

Identify predictive microstructure signals, such as order book imbalances, queue positioning, and cancellation rates across global futures markets.

High-Fidelity Backtesting

Validate systematic and trend-following strategies using actual historical market states to eliminate backtest drift and simulation bias.

Execution Optimisation & TCA

Measure transaction costs and market impact precisely by reconstructing the full order book around the time of execution.

Macro Event Analysis

Analyse order book behaviour and liquidity conditions during key macro releases, inventory announcements, and periods of high volatility.

Cross-Asset Liquidity Insights

Compare market depth, spreads, and liquidity dynamics across correlated contracts and alternative trading venues.

BENEFITS & USE CASES How BMLL Supports Commodity Trading Advisors (CTAs)

Platform	Benefit	Use Cases
	A secure cloud-based research environment for scalable microstructure analysis, TCA and alpha discovery.	• Quant strategy and alpha signal research • Microstructure backtesting and simulation • Order book dynamics analysis around macroeconomic events
	Delivers normalised and harmonised datasets as well as pre-computed analytics directly into your environment for seamless integration into existing workflows.	• Automated backtesting pipelines • Internal execution model training • Continuous large scale risk and liquidity metric ingestion
	A no-code analytics platform that provides instant visibility into market quality and liquidity dynamics.	• Pre-trade market regime diagnostics • Liquidity and fragmentation tracking • Post-trade execution analysis visuals

BMLL ECOSYSTEM Explore the BMLL Platform

Access to our full range historical harmonised and normalised level 3, equities, futures, options and prediction markets market data, built in analytics and compute that scales across CPU and GPU. Built for alpha, insights, research, development and data science. Designed by quants.

Petabytes of historical market data and derived analytics, securely delivered to your environment by API, files, cloud warehouse or data platform. Level 3 order book granularity, normalised across venues and geographies, research-ready schema.

Intuitive no code visual application bringing all market participants exceptional granular insights over 500 metrics derived from BMLL best in class Level 3.

LATEST INSIGHTS Case Studies and Client Insights

21 April 2026

Decoding Geopolitical Risk: A Level 3 Market Microstructure Analysis of Crude Oil at the Start of the Iran War

Geopolitical risk in financial markets is typically understood as a macro phenomenon - stress escalates, supply is threatened, prices spike. But the order book tells a different story. Using BMLL Level 3 data, containing every insert, cancel, and execution at every price level, we show that the market's response to the 2026 Iran war was visible in microstructure signals days before it appeared in price.

Read the Article

17 February 2026

Powering microstructure research for energy and commodity markets

A systematic trading team at a global energy firm needed a research environment to analyse microstructure and backtest strategies across energy futures. Instead of building in-house, they used BMLL’s data and tools to implement a scalable, fully operational solution within months, enabling fast and efficient strategy development.

Read the Case study

17 September 2025

Garbage In, Losses Out - What defines high-quality historical market data, and why it matters

In this article, Dr Elliot Banks explores what makes good quality, usable historical market data, and the key questions to ask when sourcing it.