Python Portfolio Optimization and Retirement Planning

This repository provides Python-based tools for optimizing financial portfolios and planning for retirement. Designed for personal finance enthusiasts, financial planners, and researchers, it combines data analysis, machine learning, and visualization to simplify investment strategy development and retirement forecasting.

Features

Portfolio Optimization

• Algorithms for balancing risk and return, including:
  • Markowitz efficient frontier
  • Monte Carlo simulations
• Risk-adjusted performance metrics (e.g., Sharpe Ratio, Sortino Ratio)
• Diversification analysis and asset allocation strategies

Retirement Planning

• Tools for calculating retirement savings goals
• Cash flow simulations for different timelines and scenarios
• Withdrawal strategy modeling (e.g., 4% rule, dynamic withdrawal rates)

Visualization Dashboards

• Interactive charts for:
  • Portfolio performance
  • Risk and return metrics
  • Retirement savings progress
• Customizable views for personal goals and risk tolerance

Data Integration

• Real-time financial data imports via APIs
• Historical data analysis for trends and projections

Getting Started

Prerequisites

• Python 3.8+
• Required libraries:
  • pandas
  • numpy
  • matplotlib
  • seaborn
  • scipy
  • yfinance (optional for live data)
  • plotly (optional for interactive visuals)

Install dependencies using:

pip install -r requirements.txt