Equal Weighting Portfolio Backtest

Built for Quantitative Finance course. Rebalances monthly across 30 randomly selected S&P 500 stocks.

Overview

• Assets: 30 randomly selected S&P 500 stocks (complete data since 2015)
• Period: 2015-2024
• Strategies: Equal-Weighted (EW), Value-Weighted (VW)
• Metrics: Sharpe Ratio, Information Ratio, Turnover vs S&P 500 benchmark
• Initial Capital: $1,000,000

Results

Performance Chart

10-Year Performance:

• Equal-Weighted: Higher volatility, potential outperformance
• Value-Weighted: Lower turnover, benchmark-aligned
• S&P 500: Market benchmark
• Risk-Free (2.5%): Conservative baseline

Key Statistics:

• Equal-Weighted Sharpe (Annual): ~0.74 | Turnover (Monthly): ~30.48%
• Value-Weighted Sharpe (Annual): ~0.38 | Turnover (Monthly): ~5.26%

Code

Project1.ipynb: Stock Selection

# Filter stocks with complete data since 2015
df_prices_2015 = df_prices[df_prices['Dates'] >= "2015-01-01"]
stocks_with_complete_data = [col for col in df_prices_2015.columns 
                              if df_prices_2015[col].notna().sum() / len(df_prices_2015) >= 0.95]

# Random selection with seed for reproducibility
np.random.seed(42)
stocks = np.random.choice(stocks_with_complete_data, 30, replace=False)

Equal-Weight Rebalancing

# Monthly rebalancing to equal weights
target_weights = np.ones(n_assets) / n_assets
target_dollar_amounts = target_weights * total_value_before
new_shares = target_dollar_amounts / current_prices

Sharpe Ratio Calculation

# Risk-adjusted return
annualized_return = (1 + avg_monthly_return) ** 12 - 1
annualized_std = monthly_std * np.sqrt(12)
sharpe_ratio = (annualized_return - 0.025) / annualized_std

Lessons

What Worked:

• Equal-weighting provides diversification benefits across 30 stocks
• Monthly rebalancing captures mean-reversion opportunities
• Outperforms in bull markets with small-cap tilt

Next Steps:

• Add momentum factor to improve trend-following performance
• Test quarterly rebalancing to reduce transaction costs
• Implement stop-loss for tail risk protection
• Explore risk parity weighting scheme