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Risk Guardian
Overview
The Risk Guardian service provides real-time risk monitoring and control mechanisms for the stock-bot platform. It serves as the protective layer that ensures trading activities remain within defined risk parameters, safeguarding the platform and its users from excessive market exposure and potential losses.
Key Features
Real-time Risk Monitoring
- Position Tracking: Continuously monitors all open positions
- Risk Metric Calculation: Calculates key risk metrics (VaR, volatility, exposure)
- Threshold Management: Configurable risk thresholds with multiple severity levels
- Aggregated Risk Views: Risk assessment at portfolio, strategy, and position levels
Automated Risk Controls
- Pre-trade Validation: Validates orders against risk limits before execution
- Circuit Breakers: Automatically halts trading when thresholds are breached
- Position Liquidation: Controlled unwinding of positions when necessary
- Trading Restrictions: Enforces instrument, size, and frequency restrictions
Risk Alerting
- Real-time Notifications: Immediate alerts for threshold breaches
- Escalation Paths: Multi-level alerting based on severity
- Alert History: Maintains historical record of all risk events
- Custom Alert Rules: Configurable alerting conditions and criteria
Compliance Management
- Regulatory Reporting: Assists with required regulatory reporting
- Audit Trails: Comprehensive logging of risk-related decisions
- Rule-based Controls: Implements compliance-driven trading restrictions
- Documentation: Maintains evidence of risk control effectiveness
Integration Points
Upstream Connections
- Market Data Gateway (for price data)
- Strategy Orchestrator (for active strategies)
- Order Management System (for position tracking)
Downstream Consumers
- Trading Dashboard (for risk visualization)
- Strategy Orchestrator (for trading restrictions)
- Notification Service (for alerting)
Technical Implementation
Technology Stack
- Runtime: Node.js with TypeScript
- Database: Time-series database for risk metrics
- Messaging: Event-driven architecture with message bus
- Math Libraries: Specialized libraries for risk calculations
- Caching: In-memory risk state management
Architecture Pattern
- Reactive microservice with event sourcing
- Command Query Responsibility Segregation (CQRS)
- Rule engine for risk evaluation
- Stateful service with persistence
Development Guidelines
Risk Calculation Approach
- Clear documentation of all risk formulas
- Validation against industry standard calculations
- Performance optimization for real-time processing
- Regular backtesting of risk models
Testing Strategy
- Unit tests for risk calculation logic
- Scenario-based testing for specific market conditions
- Stress testing with extreme market movements
- Performance testing for high-frequency updates
Calibration Process
- Documented process for risk model calibration
- Historical data validation
- Parameter sensitivity analysis
- Regular recalibration schedule
Future Enhancements
- Machine learning for anomaly detection
- Scenario analysis and stress testing
- Custom risk models per strategy type
- Enhanced visualization of risk exposures
- Factor-based risk decomposition