Skill.md
Common Sense Investing: Bogle's Index Fund Framework
This skill distills John Bogle's The Little Book of Common Sense Investing into an AI analysis tool. Bogle's core thesis is simple and mathematically irrefutable: costs are the only reliable predictor of long-term fund performance. By owning the entire market through a low-cost index fund and holding it forever, investors are guaranteed to capture their fair share of whatever returns businesses generate.
Core Framework: 5 Dimensions
| # | Dimension | One-Sentence Rule |
|---|---|---|
| 1 | The Cost Imperative | Every dollar in fees is permanently removed from compounding wealth; expense ratio is the single most reliable long-term predictor |
| 2 | Index Fund Advantage | Owning the whole market cheaply guarantees beating most active managers — the math is unavoidable |
| 3 | Business vs. Speculative Returns | Long-term returns come from dividends + earnings growth (reliable), not P/E expansion (unpredictable) |
| 4 | Reversion to the Mean | Yesterday's top fund is tomorrow's average fund; chasing past performance is counterproductive |
| 5 | Stock/Bond Allocation | Asset allocation drives 94% of return differences; low-cost conservative beats high-cost aggressive |
Supported Query Types
- Fund evaluation: "Is this fund worth buying?" → Cost analysis + RTM test + long-term wealth projection
- Asset allocation: "How should I split stocks and bonds?" → Age/horizon/risk → two-fund portfolio recommendation
- Market timing: "Is now a good time to invest?" → Investment return vs. speculative return decomposition
- Performance chasing: "This fund had great returns — should I buy it?" → RTM pattern + cost breakdown + driver analysis
How to Use
- Describe your investment question or the fund you want to evaluate
- Provide specific data (expense ratio, historical returns, time horizon) for more precise analysis
- For allocation questions, share your age and rough risk tolerance
Limitations
This skill applies Bogle's long-term index investing framework and is not suited for short-term trading or individual stock analysis. Bogle's methodology is grounded in U.S. market historical data; applicability to other markets should be considered carefully. Nothing here constitutes personal investment advice.