Enrichment Engine

Time vs. Timing: $1 Million Lost Trying to Beat the Market


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Dive into a comparative analysis of two distinct SPY ETF investment strategies from 2000 to today. We explore Portfolio #1, featuring consistent monthly contributions, versus Portfolio #2, which waits for market volatility (VIX hitting 30) to deploy capital. Uncover the methodologies behind calculating their compounded annual returns and the key considerations for each approach.

Please note: Due to data acquisition limitations, the specific compounded annual returns cannot be presented in this overview, but the strategic frameworks are thoroughly discussed.

Show Notes:

  • Introduction: Overview of the two SPY ETF investment strategies being analyzed since 2000.
  • Portfolio #1: Consistent Monthly Contributions
    • Initial investment: $100,000 fully invested in SPY.
    • Additional contributions: $1,000 at the beginning of each calendar month.
    • Methodology for tracking portfolio value.
  • Portfolio #2: Volatility-Triggered Lump Sum Contributions
    • Initial investment: $100,000 fully invested in SPY.
    • Additional contributions: $1,000 kept in cash each month.
    • Investment trigger: Cash is invested into SPY only when the VIX (Volatility Index) hits 30 or above.
    • Methodology for tracking portfolio value and cash reserves.
  • Calculating Compounded Annual Return (CAGR):
    • Formula: (Ending Value / Beginning Value)^(1 / Number of Years) - 1
    • Importance of consistent data for accurate calculation.
  • Data Acquisition Challenges (Important Note):
    • Discussion on the challenge of obtaining comprehensive, programmatically accessible historical SPY ETF daily data from 2000 to present.
    • Acknowledgment that a full numerical calculation of CAGR for both portfolios is not possible within the current constraints due to this data limitation.
    • VIX historical data was successfully acquired from FRED (Federal Reserve Economic Data).
  • Strategic Insights (General Discussion):
    • Brief overview of the potential pros and cons of dollar-cost averaging (Portfolio #1) versus a volatility-based timing strategy (Portfolio #2).
    • Factors influencing portfolio performance (market trends, individual stock/ETF performance, timing).
  • Conclusion: Summary of the analytical framework and the importance of robust historical data for investment simulations.
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Enrichment EngineBy Matt Hagemann