Real-time Trade Surveillance
Real-time trade surveillance is the automated monitoring of trading activity as it occurs to detect potential market manipulation, insider trading, and other forms of market abuse. Modern surveillance systems analyze market data, order flow, and trading patterns in real-time to identify suspicious behavior and generate alerts for compliance teams.
How real-time trade surveillance works
Real-time trade surveillance systems continuously monitor multiple data streams including:
- Order flow
- Market data
- Trading activity
- Reference data
- News and social media feeds
The surveillance process can be visualized as follows:
Key surveillance components
Pattern recognition engine
The pattern recognition engine analyzes trading behavior to detect known patterns of market abuse such as:
- Spoofing
- Front running
- Wash trading
- Layering
- Momentum ignition
Alert generation
When suspicious patterns are detected, the system generates alerts based on:
- Alert severity
- Pattern confidence level
- Historical behavior
- Market impact
Case management
Alerts are routed to compliance analysts who:
- Review alert details
- Investigate underlying activity
- Document findings
- Escalate potential violations
Market structure considerations
Real-time surveillance must account for modern market structure complexities:
- Market fragmentation
- Multiple asset classes
- High-frequency trading
- Cross-market surveillance
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.
Performance requirements
Real-time surveillance systems must process massive data volumes with minimal latency:
- Process millions of messages per second
- Analyze cross-market correlations
- Generate alerts within milliseconds
- Store historical data for replay and investigation
Regulatory drivers
Major regulations requiring trade surveillance include:
- Market Abuse Regulation (MAR)
- Dodd-Frank Act
- MiFID II
- Regulation NMS
Benefits of real-time surveillance
Effective surveillance provides:
- Early detection of market abuse
- Reduced regulatory risk
- Enhanced market integrity
- Improved investor protection
- Automated compliance workflows
Time-series considerations
Real-time trade surveillance relies heavily on time-series analysis:
- Pattern detection across multiple time horizons
- Historical baseline comparison
- Temporal correlation analysis
- Time-synchronized event processing
The ability to process and analyze time-series data efficiently is critical for effective surveillance operations.