Market by Price (MBP)
Market by Price (MBP) is a method of organizing and displaying market depth data by aggregating orders at each price level. Unlike Market by Order (MBO), which shows individual orders, MBP consolidates all orders at the same price into a single aggregate quantity, providing a more condensed view of liquidity.
Understanding market by price data
MBP data represents a price-aggregated view of the order book, showing the total available volume at each price level. This format is particularly useful for traders and algorithms that need to understand overall market liquidity without the complexity of individual order tracking.
For each price level, MBP typically provides:
- Price point
- Aggregate volume
- Number of orders (optional)
- Side (bid or ask)
Market by price structure
Benefits of MBP data
Efficient market depth representation
MBP provides a more bandwidth-efficient way to distribute market depth information compared to MBO feeds. This efficiency is particularly important for:
- High-volume markets
- Wide distribution networks
- Applications requiring quick market depth assessment
Trading applications
MBP data is valuable for:
- Volume Profile analysis
- Liquidity assessment
- Order size planning
- Transaction Cost Modeling
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.
Market by price vs. market by order
The key differences between MBP and MBO approaches include:
Data volume
- MBP generates less data as it aggregates orders
- Reduced bandwidth requirements
- Lower processing overhead
Use cases
- MBP: Suitable for overall liquidity analysis
- MBO: Required for detailed order flow analysis and trade surveillance
Implementation considerations
Data processing
When implementing MBP systems, consider:
- Price level management
- Volume aggregation efficiency
- Update frequency
- Memory usage optimization
Performance implications
MBP systems must handle:
- Rapid price level updates
- Real-time aggregation
- Multiple price levels simultaneously
- High message throughput
Market impact
Understanding MBP data helps traders:
- Assess market depth accurately
- Plan order execution strategies
- Minimize market impact cost
- Optimize trading decisions
Best practices for MBP systems
Data handling
- Implement efficient price level indexing
- Maintain consistent aggregation methods
- Process updates atomically
- Handle price level creation/deletion efficiently
System design
- Focus on low-latency processing
- Implement robust error handling
- Ensure accurate timestamp management
- Maintain data consistency
Integration with trading systems
MBP data integrates with:
- Order Management System (OMS)
- Smart Order Router (SOR)
- Market analysis tools
- Risk management systems
This integration enables:
- Informed trading decisions
- Better execution quality
- Enhanced risk control
- Improved market understanding