# 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