Scalar Field
Be invested in global equity markets during November - April period, stay in cash during May-October period (alternatively go long in stocks from countries from northern hemisphere during winter period and long in stocks from countries from southern hemisphere during summer period; alternatively go long in cyclical companies during winter period and short defensive stocks and switch positions during the summer period)

Thank you for sharing this interesting seasonal trading strategy! Before I proceed with the analysis, I need some clarifications:

Required Information:

  1. Study Period: What time period would you like me to analyze? (e.g., last 10 years, 20 years, since 2000, etc.)

  2. Strategy Variant: You mentioned three different approaches. Which one would you like me to analyze, or should I compare all three?

    • Variant A: November-April in equity markets, May-October in cash
    • Variant B: Northern hemisphere stocks during their winter (Nov-Apr) vs Southern hemisphere stocks during their winter (May-Oct)
    • Variant C: Long cyclicals during winter (Nov-Apr), short defensives; reverse during summer (May-Oct)

  3. Equity Market Proxy:

    • For Variant A: Which equity index/ETF should I use? (e.g., SPY for S&P 500, VT for global markets, ACWI, etc.)
    • For Variant B: Which specific country indices/ETFs for Northern and Southern hemispheres?
    • For Variant C: Which specific cyclical and defensive sector ETFs/indices?

  4. Cash Rate: For the cash periods, should I assume:

    • 0% return (pure cash)
    • Risk-free rate (e.g., 3-month T-bills)
    • Money market fund returns

  5. Benchmark: What should I compare the strategy against? (e.g., buy-and-hold the equity index)

Please provide these details so I can conduct a comprehensive analysis of your seasonal strategy!

Do the last 20 years. Do Variant A. Do SPY. Do a cash rate that investors commonly use. Benchmark against buy and hold the equity index

Perfect! I have all the information I need. Let me plan the analysis:

Analysis Plan:

  1. Fetch SPY daily data for the last 20 years (2005-2025)
  2. Implement Variant A Strategy:
    • Long SPY from November 1st through April 30th each year
    • Hold cash (will use 3-month T-bill rate as proxy - commonly used by investors) from May 1st through October 31st
  3. Calculate returns for:
    • The seasonal strategy
    • Buy-and-hold SPY benchmark
  4. Performance metrics:
    • Total return
    • Annualized return
    • Volatility (standard deviation)
    • Sharpe ratio
    • Maximum drawdown
    • Win rate by year
  5. Visualizations:
    • Cumulative returns comparison
    • Year-by-year performance
    • Monthly return patterns

Let me proceed with the analysis:

Now let me prepare the data and implement the seasonal strategy:

Now let me calculate performance metrics:

Let me calculate year-by-year performance and create visualizations:

Let me show the full year-by-year table properly and then create visualizations:

Now let me create comprehensive visualizations:

Let me also analyze the specific periods to understand when the strategy works best:

Summary

I've completed a comprehensive analysis of the "Sell in May and Go Away" seasonal trading strategy over the past 20 years (2005-2025). Here are the key findings:

Overall Performance

  • Seasonal Strategy: 239.76% total return (6.32% annualized) with 14.24% volatility
  • Buy & Hold SPY: 440.68% total return (8.82% annualized) with 19.43% volatility
  • The seasonal strategy underperformed buy-and-hold by about 201 percentage points in total returns

Risk Metrics

  • Maximum Drawdown: Seasonal strategy (-36.65%) vs Buy & Hold (-56.47%)
    • The strategy provided 35% less drawdown during the 2008 financial crisis
  • Sharpe Ratio: Nearly identical (0.444 vs 0.454) - similar risk-adjusted returns
  • Volatility: 27% lower for the seasonal strategy (14.24% vs 19.43%)

Key Insights

  1. The Strategy Works as Intended: Winter months (Nov-Apr) delivered 11.36% annualized returns vs. summer months (May-Oct) at 6.44% - a 4.9% annual premium

  2. Win Rate: The seasonal strategy only outperformed in 6 out of 21 years (28.6%)

    • Major wins: 2008 (+27.06%), 2011 (+8.71%), 2022 (+6.41%)
    • Big misses: 2009 (-19.17%), 2020 (-12.76%), 2024 (-11.66%), 2025 (-19.80% YTD)

  3. Trade-off: Lower returns but significantly lower risk - ideal for risk-averse investors who want to avoid major bear markets

  4. Recent Underperformance: The strategy has struggled particularly in recovery years (2009, 2020) and strong bull markets (2024, 2025 YTD) when summer months also performed well

The seasonal strategy validates the "sell in May" phenomenon but comes at the cost of missing summer rallies in strong bull market years. It's best suited for investors prioritizing capital preservation over maximum returns.