84 lines
No EOL
3.3 KiB
Markdown
84 lines
No EOL
3.3 KiB
Markdown
# Risk Guardian
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## Overview
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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.
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## Key Features
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### Real-time Risk Monitoring
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- **Position Tracking**: Continuously monitors all open positions
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- **Risk Metric Calculation**: Calculates key risk metrics (VaR, volatility, exposure)
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- **Threshold Management**: Configurable risk thresholds with multiple severity levels
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- **Aggregated Risk Views**: Risk assessment at portfolio, strategy, and position levels
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### Automated Risk Controls
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- **Pre-trade Validation**: Validates orders against risk limits before execution
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- **Circuit Breakers**: Automatically halts trading when thresholds are breached
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- **Position Liquidation**: Controlled unwinding of positions when necessary
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- **Trading Restrictions**: Enforces instrument, size, and frequency restrictions
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### Risk Alerting
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- **Real-time Notifications**: Immediate alerts for threshold breaches
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- **Escalation Paths**: Multi-level alerting based on severity
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- **Alert History**: Maintains historical record of all risk events
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- **Custom Alert Rules**: Configurable alerting conditions and criteria
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### Compliance Management
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- **Regulatory Reporting**: Assists with required regulatory reporting
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- **Audit Trails**: Comprehensive logging of risk-related decisions
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- **Rule-based Controls**: Implements compliance-driven trading restrictions
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- **Documentation**: Maintains evidence of risk control effectiveness
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## Integration Points
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### Upstream Connections
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- Market Data Gateway (for price data)
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- Strategy Orchestrator (for active strategies)
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- Order Management System (for position tracking)
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### Downstream Consumers
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- Trading Dashboard (for risk visualization)
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- Strategy Orchestrator (for trading restrictions)
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- Notification Service (for alerting)
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## Technical Implementation
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### Technology Stack
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- **Runtime**: Node.js with TypeScript
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- **Database**: Time-series database for risk metrics
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- **Messaging**: Event-driven architecture with message bus
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- **Math Libraries**: Specialized libraries for risk calculations
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- **Caching**: In-memory risk state management
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### Architecture Pattern
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- Reactive microservice with event sourcing
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- Command Query Responsibility Segregation (CQRS)
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- Rule engine for risk evaluation
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- Stateful service with persistence
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## Development Guidelines
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### Risk Calculation Approach
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- Clear documentation of all risk formulas
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- Validation against industry standard calculations
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- Performance optimization for real-time processing
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- Regular backtesting of risk models
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### Testing Strategy
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- Unit tests for risk calculation logic
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- Scenario-based testing for specific market conditions
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- Stress testing with extreme market movements
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- Performance testing for high-frequency updates
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### Calibration Process
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- Documented process for risk model calibration
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- Historical data validation
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- Parameter sensitivity analysis
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- Regular recalibration schedule
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## Future Enhancements
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- Machine learning for anomaly detection
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- Scenario analysis and stress testing
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- Custom risk models per strategy type
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- Enhanced visualization of risk exposures
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- Factor-based risk decomposition |