Overview

Developed a comprehensive portfolio optimization platform that implements multiple investment strategies and provides real-time analytics for investment decision-making. The system combines advanced financial modeling with intuitive user interfaces.

Investment Strategies

• Modern Portfolio Theory (Markowitz): Classic mean-variance optimization for efficient frontier construction
• Black-Litterman Model: Bayesian approach incorporating investor views and market equilibrium
• Risk Parity: Equal risk contribution allocation across portfolio components
• Custom Strategies: Flexible framework for implementing additional optimization approaches

Key Features

• Real-Time Data Integration: Live market data feeds for accurate portfolio valuation
• Interactive Analytics: Dynamic dashboards with drill-down capabilities and customizable views
• Risk Analysis: Comprehensive risk metrics including VaR, CVaR, and stress testing
• Backtesting Engine: Historical performance analysis and strategy validation
• Multi-Asset Support: Stocks, bonds, commodities, and alternative investments

Technologies Used

• Python: Backend development with Flask/Django framework
• Financial Libraries: NumPy, SciPy, PyPortfolioOpt for mathematical optimization
• Database: PostgreSQL for storing historical data and portfolio configurations
• Frontend: React.js with D3.js for interactive data visualization
• APIs: Integration with financial data providers (Alpha Vantage, Yahoo Finance)
• Cloud Deployment: AWS/Azure for scalable hosting and data processing

Architecture

• Data Layer: Real-time market data ingestion and historical data management
• Optimization Engine: Core algorithms for portfolio optimization and risk calculation
• API Layer: RESTful APIs for frontend communication and external integrations
• Frontend Dashboard: Responsive web application with real-time updates
• Analytics Module: Advanced reporting and performance attribution analysis

Results

The platform successfully provides sophisticated portfolio optimization capabilities typically found in institutional investment management systems, making advanced portfolio theory accessible through an intuitive interface.

Business Applications

This system demonstrates practical applications of quantitative finance and showcases the integration of complex mathematical models with modern web technologies to create powerful financial tools.