Market by Order (MBO)
Market by Order (MBO) is a detailed market data feed format that provides complete visibility into individual orders within an order book. Unlike aggregated feeds, MBO exposes specific information about each order, including unique order IDs, sizes, prices, and timestamps, enabling market participants to reconstruct the full order book state and track order lifecycle events.
Understanding market by order data
Market by Order data represents the highest level of market data granularity available in modern financial markets. Unlike market by price (MBP), which aggregates orders at each price level, MBO feeds maintain individual order information, providing a complete picture of the order book.
The key components of MBO data include:
- Unique order identifiers
- Individual order quantities
- Price levels
- Entry timestamps
- Order lifecycle events (modifications, cancellations)
- Execution information
Market microstructure applications
MBO data is essential for advanced market microstructure analysis and sophisticated trading strategies. The granular nature of the data enables:
Next generation time-series database
QuestDB is an open-source time-series database optimized for market and heavy industry data. Built from scratch in Java and C++, it offers high-throughput ingestion and fast SQL queries with time-series extensions.
Trading system requirements
Processing MBO data requires sophisticated infrastructure due to:
- High message rates
- Large data volumes
- Complex state management
- Order tracking requirements
Market participants must maintain order books that can:
- Track millions of individual orders
- Process thousands of updates per second
- Maintain order state consistency
- Enable quick order lookup and modification
Regulatory considerations
MBO feeds play a crucial role in market surveillance and regulatory compliance:
- Provides audit trails for order handling
- Enables detection of manipulative practices like spoofing
- Supports best execution analysis
- Facilitates regulatory reporting requirements
Performance implications
Working with MBO data presents unique challenges for time-series databases and trading systems:
- Higher storage requirements compared to MBP
- Increased processing overhead
- Greater network bandwidth consumption
- More complex data management needs
Organizations must carefully consider their infrastructure capabilities when implementing MBO-based systems, particularly in terms of:
- Data ingestion capacity
- Storage optimization
- Query performance
- Real-time processing capabilities
Market quality analysis
MBO data enables sophisticated market quality assessments:
- Precise measurement of market impact cost
- Detailed liquidity analysis
- Order resting time studies
- Queue position analysis
- Fill probability calculations
This granular information helps traders and analysts better understand market dynamics and optimize their trading strategies.
Next generation time-series database
QuestDB is an open-source time-series database optimized for market and heavy industry data. Built from scratch in Java and C++, it offers high-throughput ingestion and fast SQL queries with time-series extensions.
Future developments
The evolution of MBO feeds continues to be driven by:
- Increasing market complexity
- Growing demand for transparency
- Advancing technology capabilities
- Regulatory requirements
As markets continue to evolve, MBO data will play an increasingly important role in understanding and participating in financial markets effectively.