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.
