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docs/core-services/risk-guardian/README.md

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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