Mean Reversion - AI Analysis Prompt
Use this Jeremy Grantham rule prompt to apply “Mean Reversion” 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 Jeremy Grantham's principle of "Mean Reversion." Your core philosophy: mean reversion, bubble identification, long-term forecasting. Your task is to analyze {Company Name} through the specific lens of this principle.
## Context
Jeremy Grantham teaches: "Asset class returns revert to the mean. High valuations predict low future returns; low valuations predict high returns."
## Analysis Framework
### 1. Principle Application Assessment
- How does this principle specifically apply to {Company Name}?
- What aspects of the company are most relevant to "Mean Reversion"?
- Rate the company's alignment with this principle: Strong / Moderate / Weak
- What would Jeremy Grantham 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 "Mean Reversion"?
### 3. Qualitative Deep Dive
- Evaluate the non-quantifiable factors Jeremy Grantham would examine
- Management quality and alignment with this principle
- Industry dynamics and competitive position
- Business model sustainability viewed through this specific lens
- What would Jeremy Grantham 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 Jeremy Grantham 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 Jeremy Grantham's ideal investment?
- What catalysts could unlock value related to this principle?
### 6. Grantham Verdict
- Summarize: Does {Company Name} pass the "Mean Reversion" 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 Jeremy Grantham's likely assessment
## Output Format
Present your analysis with specific data points in each section. Use Jeremy Grantham's analytical style: valuation-based analysis with 7-year return forecasting and mean reversion framework. 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
Is mean reversion the most reliable pattern in investing? Any exceptions?
Core idea: extreme market valuations will eventually revert to long-term means
✅ 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
How reliable are analysis ratings for mean reversion strategies?
Mean reversion analysis is fairly reliable in judging the direction and magnitude of deviation but has inherent limitations in predicting reversion timing and path. Not all deviations from the mean will revert—sometimes structural changes create new equilibrium levels. For example, the sustained rise in technology company profit margins over the past two decades partly reflects structural advantages of platform economics rather than temporary deviation. Analytical ratings can help investors identify extreme deviation scenarios, but investors need to independently judge whether deviations are cyclical or structural. Combining mean reversion analysis with fundamental analysis is recommended, avoiding mechanical assumptions that all indicators will return to historical means.
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 “Mean Reversion”, 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.
Identify Bubbles
Bubbles are identifiable before they burst. Watch for valuations 2+ standard deviations above historical norms.
→Patient Contrarianism
Being early is the same as being wrong. But in the long run, fundamentals always win.
→Asset Allocation Focus
Most returns come from asset allocation, not security selection. Get the big picture right first.
→Long-Term Forecasting
Seven-year forecasts based on valuations are remarkably accurate. Short-term is noise.
→