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Mean-Variance Optimization

A comprehensive financial analysis project that implements Modern Portfolio Theory (MPT) using historical stock data from 2000-2023. This project analyzes 27 selected stocks and the S&P 500 index to construct optimal portfolios based on mean-variance optimization principles.

Project Overview

This project demonstrates the application of Harry Markowitz's Modern Portfolio Theory to real financial data, focusing on:

  • Risk-Return Analysis: Statistical analysis of individual stocks and market indices
  • Portfolio Optimization: Construction of efficient portfolios using mean-variance optimization
  • Risk Management: Value at Risk (VaR) calculations and risk assessment
  • Efficient Frontier: Visualization of optimal risk-return combinations

Key Features

1. Statistical Analysis

  • Descriptive Statistics: Mean, standard deviation, skewness, and kurtosis for all assets
  • Annualized Returns: Conversion of monthly returns to annual metrics
  • Risk Metrics: 5% Value at Risk (VaR) calculations
  • Distribution Analysis: Assessment of return distribution characteristics

2. Portfolio Construction

  • Global Minimum Variance Portfolio (GMVP): Portfolio with the lowest possible risk
  • Mean-Variance Frontier: Complete efficient frontier construction
  • Optimal Asset Allocation: Risk-averse investor portfolio optimization

3. Data Visualization

  • Equal-Weighted Index Performance: Historical performance tracking (2000-2023)
  • Efficient Frontier Plot: Risk-return trade-off visualization
  • Statistical Distribution Analysis: Return distribution characteristics

Key Findings

S&P 500 Analysis (2000-2023)

  • Monthly Mean Return: 0.68%
  • Annualized Return: 8.45%
  • Annualized Volatility: 15.4%
  • 5% VaR: -6.65% (monthly)
  • Skewness: -0.46 (left-skewed, indicating higher probability of extreme losses)
  • Kurtosis: 0.70 (platykurtic, fewer extreme outliers than normal distribution)

Key Insights

  1. Market Characteristics: S&P 500 shows negative skewness, indicating higher probability of extreme losses
  2. Diversification Benefits: Portfolio optimization significantly reduces risk compared to individual stocks
  3. Risk Management: VaR provides practical risk assessment for portfolio management
  4. Optimal Allocation: Risk-averse investors should allocate approximately 46% to risky assets

About

A comprehensive financial analysis project that implements Modern Portfolio Theory (MPT) using historical stock data from 2000-2023. This project analyzes 27 selected stocks and the S&P 500 index to construct optimal portfolios based on mean-variance optimization principles.

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