Reversion to the Mean - AI Analysis Prompt
Use this John Bogle rule prompt to apply “Reversion to the Mean” to a specific company. It turns a vague opinion into a repeatable checklist: what facts you must verify, which assumptions matter most, what would invalidate the thesis, and the common misreads that create false certainty. Expect a written output you can save: a thesis summary, key risks, and next-step questions for filings and earnings calls. If a claim matters, require primary-source citations before you act. Educational only — not investment advice.
Full Prompt
You are an investment analyst trained in John Bogle's principle of "Reversion to the Mean." Your core philosophy: index investing, low costs, long-term simplicity. Your task is to analyze {Company Name} through the specific lens of this principle.
## Context
John Bogle teaches: "Fund returns tend to revert to the mean. Yesterday's winners become tomorrow's losers, and vice versa."
## Analysis Framework
### 1. Principle Application Assessment
- How does this principle specifically apply to {Company Name}?
- What aspects of the company are most relevant to "Reversion to the Mean"?
- Rate the company's alignment with this principle: Strong / Moderate / Weak
- What would John Bogle focus on first when evaluating this company?
### 2. Quantitative Evidence
- Identify 3-5 key financial metrics most relevant to this principle
- Analyze these metrics over the past 5-10 years for {Company Name}
- Compare with industry peers and historical benchmarks
- Are the numbers improving, stable, or deteriorating?
- What story do the numbers tell through the lens of "Reversion to the Mean"?
### 3. Qualitative Deep Dive
- Evaluate the non-quantifiable factors John Bogle would examine
- Management quality and alignment with this principle
- Industry dynamics and competitive position
- Business model sustainability viewed through this specific lens
- What would John Bogle want to know that isn't in the financial statements?
### 4. Risk Assessment Through This Lens
- What risks does this principle specifically highlight for {Company Name}?
- What could go wrong that this principle is designed to protect against?
- Are there warning signs that John Bogle would flag?
- Stress-test: How would this company perform under adverse conditions?
- What is the worst-case scenario from this principle's perspective?
### 5. Opportunity Identification
- What opportunities does analyzing through this lens reveal?
- Are there hidden strengths the market may be undervaluing?
- How does this company compare to John Bogle's ideal investment?
- What catalysts could unlock value related to this principle?
### 6. Bogle Verdict
- Summarize: Does {Company Name} pass the "Reversion to the Mean" test?
- Rate the investment opportunity: 1-10 from this principle's perspective
- Clear recommendation: Buy / Hold / Avoid (based on this principle alone)
- What conditions would change your assessment?
- One-paragraph summary capturing John Bogle's likely assessment
## Output Format
Present your analysis with specific data points in each section. Use John Bogle's analytical style: cost-conscious analysis emphasizing simplicity and long-term discipline. End with a decisive verdict.Related reading (close the loop)
Pick one path below to turn the output into a checkable, repeatable decision policy.
- Read the matching principleDefinition, boundaries, pitfalls, and a minimal checklist.
- Master profileMethodology summary + common misreads for this framework.
- Practice in scenariosTranslate conclusions into “what I do under stress”.
- More prompts from this masterTriangulate with multiple rules instead of anchoring on one prompt.
Educational only. Verify facts with primary sources and apply your own constraints.
Basic Questions
How does mean reversion theory help identify extreme market valuations?
Core idea: extreme market performance will eventually revert to the mean
✅ Using this AI prompt, you can systematically analyze any company or investment opportunity from this principle's perspective.
The prompt guides you to:
1. Assess whether the investment target meets this principle's core requirements
2. Identify key risks and blind spots
3. Provide a 1-10 comprehensive rating
Start by analyzing companies you know well for practice, then apply the framework to new investment decisions.
✅ Using this AI prompt, you can systematically analyze any company or investment opportunity from this principle's perspective.
The prompt guides you to:
1. Assess whether the investment target meets this principle's core requirements
2. Identify key risks and blind spots
3. Provide a 1-10 comprehensive rating
Start by analyzing companies you know well for practice, then apply the framework to new investment decisions.
Usage Tips
Is the AI's 1-10 rating reliable?
⚠️ The mean reversion score helps identify deviations that "will eventually normalize" but cannot tell you "when."
The rating's unique value:
- Bogle's core insight: Whether stock returns, fund manager performance, or market valuations, all mean-revert over the long term
- A high score means your invested asset is near historical averages — risk is relatively manageable
- A low score (whether deviation is too high or too low) is a warning: the current state is unsustainable
Important understanding:
- Mean reversion isn't a clock — "it will revert eventually" doesn't mean "it will revert soon," as markets can remain irrational for extended periods
- Bogle used mean reversion to argue against performance chasing — past top-performing funds often underperform in the future
- AI can calculate deviation magnitude but cannot predict reversion speed — this is mean reversion's greatest uncertainty
The rating's unique value:
- Bogle's core insight: Whether stock returns, fund manager performance, or market valuations, all mean-revert over the long term
- A high score means your invested asset is near historical averages — risk is relatively manageable
- A low score (whether deviation is too high or too low) is a warning: the current state is unsustainable
Important understanding:
- Mean reversion isn't a clock — "it will revert eventually" doesn't mean "it will revert soon," as markets can remain irrational for extended periods
- Bogle used mean reversion to argue against performance chasing — past top-performing funds often underperform in the future
- AI can calculate deviation magnitude but cannot predict reversion speed — this is mean reversion's greatest uncertainty
Getting started
Does this prompt give investment advice or buy/sell calls?
No. It is a research helper that turns your thinking into checkable inputs and constraints: what evidence you must verify, what would prove the thesis wrong, and what common misreads to avoid. Treat the output as a draft, not a signal. Validate every material number against primary sources (filings, earnings releases, investor presentations, transcripts), and do not act unless you can write down (1) position-size limits and (2) explicit invalidation triggers.
What inputs should I provide for a reliable result?
At minimum: a 1-sentence business model summary, your current thesis (why it wins/loses), time horizon, and risk constraints; a valuation/price range; and the latest financial statements (profit quality, cash flow, debt/liquidity). Add context that reduces hallucinations: the exact filing period, known one-offs, key competitors, and what you do NOT know yet. If an input is missing, label it as missing evidence instead of letting the model guess.
Validation and boundaries
How do I validate the output?
Validate falsifiable claims one by one. Rewrite each key statement into something you can check: the metric, the period, and the source. Numbers must match filings; management claims must be traceable to transcripts/guidance; and “moat” claims need observable evidence (pricing power, retention, switching costs, cost structure). Anything you cannot verify becomes a follow-up task, not a decision trigger. If the model cites dates, confirm they are not beyond its knowledge cutoff.
When should I NOT act on the output?
If you cannot write down invalidation triggers, a position-size cap, or primary-source evidence for the key claims behind “Reversion to the Mean”, do not act. The safer move is usually to reduce size, slow down, and schedule the next review.
More Rule Prompts
Explore other investment principles from this master.
Enough
There is no amount of money that will ever be enough for someone who doesn't know what enough is. Define your enough.
→Don't Peek
Don't peek at your portfolio constantly. The more you look, the more likely you are to make an emotional mistake.
→Bond Allocation Rule
A rough rule: hold your age in bonds. A 30-year-old might hold 30% bonds, a 60-year-old 60% bonds.
→Asset Allocation
Your asset allocation - the mix of stocks, bonds, and cash - is the most important investment decision you'll make.
→