Emmanuel Isaac
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Risk Management System

Risk Management System

A comprehensive portfolio risk management system designed for quantitative analysis, risk assessment, and portfolio optimization. This tool provides advanced risk metrics, stress testing capabilities, and portfolio optimization features for institutional and individual investors.

Features

  • Portfolio Risk Analysis - Comprehensive risk assessment and analysis
  • Risk Metrics Calculation - Advanced risk metrics and performance indicators
  • Stress Testing - Scenario analysis and stress testing capabilities
  • Portfolio Optimization - Modern portfolio theory optimization
  • Real-time Monitoring - Live portfolio monitoring and alerts
  • Risk Reporting - Automated risk reporting and analytics
  • Multi-Asset Support - Support for stocks, bonds, forex, and crypto
  • Regulatory Compliance - Compliance with regulatory requirements

Risk Metrics

Volatility Metrics

  • Historical Volatility - Rolling and annualized volatility calculations
  • Implied Volatility - Option-implied volatility analysis
  • Conditional Volatility - GARCH and other volatility models
  • Realized Volatility - High-frequency volatility estimation
  • Volatility Forecasting - Volatility prediction models

Downside Risk Metrics

  • Value at Risk (VaR) - Parametric, historical, and Monte Carlo VaR
  • Expected Shortfall (CVaR) - Conditional Value at Risk
  • Maximum Drawdown - Maximum peak-to-trough decline
  • Downside Deviation - Semi-deviation and downside risk measures
  • Tail Risk - Extreme event risk analysis

Correlation and Diversification

  • Correlation Analysis - Asset correlation and cointegration analysis
  • Diversification Ratio - Portfolio diversification metrics
  • Concentration Risk - Asset concentration and sector analysis
  • Beta Analysis - Market beta and systematic risk analysis
  • Factor Analysis - Multi-factor risk model analysis

Portfolio Optimization

Modern Portfolio Theory

  • Mean-Variance Optimization - Markowitz portfolio optimization
  • Efficient Frontier - Efficient frontier calculation and analysis
  • Risk Parity - Risk parity portfolio construction
  • Black-Litterman Model - Bayesian portfolio optimization
  • Maximum Sharpe Ratio - Sharpe ratio optimization

Advanced Optimization

  • Constrained Optimization - Optimization with constraints
  • Robust Optimization - Robust portfolio optimization
  • Multi-Objective Optimization - Multi-criteria optimization
  • Dynamic Optimization - Time-varying portfolio optimization
  • Machine Learning Optimization - ML-based portfolio optimization

Tech Stack

  • Language: Python 3.8+
  • Numerical Computing: NumPy, SciPy, Pandas
  • Optimization: CVXPY, SciPy.optimize
  • Machine Learning: Scikit-learn, TensorFlow
  • Visualization: Matplotlib, Plotly, Dash
  • Database: PostgreSQL, Redis
  • Web Framework: FastAPI, Flask

Installation & Setup

  1. Clone the repository:

    git clone https://github.com/1cbyc/risk-management-system.git
cd risk-management-system

  2. Install dependencies:

    pip install -r requirements.txt

  3. Set up database:

    python setup_database.py

  4. Configure the system:

    cp config.example.yaml config.yaml
# Edit configuration with your preferences

  5. Start the application:

    python app.py

Usage Examples

Basic Risk Analysis

from risk_manager import RiskManager

# Initialize risk manager
risk_manager = RiskManager()

# Load portfolio data
portfolio = {
    'AAPL': 0.3,
    'GOOGL': 0.25,
    'MSFT': 0.25,
    'TSLA': 0.2
}

# Calculate risk metrics
risk_metrics = risk_manager.calculate_risk_metrics(
    portfolio=portfolio,
    historical_data=market_data,
    confidence_level=0.95
)

print(f"Portfolio VaR: {risk_metrics['var']:.2%}")
print(f"Expected Shortfall: {risk_metrics['cvar']:.2%}")
print(f"Volatility: {risk_metrics['volatility']:.2%}")

Portfolio Optimization

from portfolio_optimizer import PortfolioOptimizer

# Initialize optimizer
optimizer = PortfolioOptimizer()

# Define optimization constraints
constraints = {
    'min_weight': 0.0,
    'max_weight': 0.4,
    'target_return': 0.10,
    'risk_free_rate': 0.02
}

# Optimize portfolio
optimal_weights = optimizer.optimize_portfolio(
    returns=asset_returns,
    method='efficient_frontier',
    constraints=constraints
)

print("Optimal weights:", optimal_weights)

Stress Testing

from stress_tester import StressTester

# Initialize stress tester
stress_tester = StressTester()

# Define stress scenarios
scenarios = {
    'market_crash': {
        'equity_shock': -0.20,
        'volatility_shock': 2.0,
        'correlation_shock': 0.3
    },
    'interest_rate_shock': {
        'rate_change': 0.02,
        'duration_impact': -0.15
    }
}

# Run stress tests
stress_results = stress_tester.run_stress_tests(
    portfolio=portfolio,
    scenarios=scenarios
)

print("Stress test results:", stress_results)

Risk Models

Factor Models

  • CAPM - Capital Asset Pricing Model
  • Fama-French Three-Factor - Size and value factors
  • Carhart Four-Factor - Momentum factor addition
  • Multi-Factor Models - Custom factor models
  • Principal Component Analysis - PCA-based risk decomposition

Time Series Models

  • GARCH Models - Generalized Autoregressive Conditional Heteroskedasticity
  • EWMA - Exponentially Weighted Moving Average
  • ARIMA Models - Autoregressive Integrated Moving Average
  • Regime Switching - Markov regime switching models
  • Copula Models - Dependence structure modeling

Monitoring and Alerts

Real-time Monitoring

  • Portfolio Tracking - Real-time portfolio value tracking
  • Risk Limit Monitoring - Risk limit breach detection
  • Performance Tracking - Performance vs. benchmark tracking
  • Correlation Monitoring - Asset correlation monitoring

Alert System

  • Risk Limit Alerts - Risk limit breach notifications
  • Performance Alerts - Performance threshold alerts
  • Market Event Alerts - Market event notifications
  • Custom Alerts - Custom alert conditions

Reporting and Analytics

Risk Reports

  • Daily Risk Report - Daily risk summary and analysis
  • Weekly Risk Report - Weekly comprehensive risk analysis
  • Monthly Risk Report - Monthly detailed risk assessment
  • Regulatory Reports - Regulatory compliance reports

Analytics Dashboard

  • Risk Metrics Dashboard - Real-time risk metrics visualization
  • Portfolio Analytics - Portfolio performance and risk analytics
  • Stress Test Results - Stress testing results visualization
  • Optimization Results - Portfolio optimization results

Regulatory Compliance

Risk Management Standards

  • Basel III - Banking regulatory compliance
  • Solvency II - Insurance regulatory compliance
  • UCITS - European fund regulatory compliance
  • SEC Requirements - US securities regulatory compliance

Reporting Standards

  • Risk Reporting - Standardized risk reporting formats
  • Performance Attribution - Performance attribution analysis
  • Compliance Monitoring - Regulatory compliance monitoring
  • Audit Trail - Complete audit trail and documentation

Project Impact

This system has been used by:

  • Asset Managers - Portfolio risk management and optimization
  • Hedge Funds - Risk monitoring and portfolio construction
  • Banks - Regulatory compliance and risk management
  • Insurance Companies - Asset-liability management

Future Enhancements

  • AI/ML Integration - Advanced AI/ML risk modeling
  • Real-time Data - Real-time market data integration
  • Cloud Deployment - Cloud-based risk management platform
  • Mobile App - Mobile risk monitoring and alerts
  • API Integration - Third-party system integration