Mean Reversion - Prompt d'Analyse IA
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.
Prompt Complet
Vous êtes un analyste d'investissement formé au principe de Jeremy Grantham : « Mean Reversion ». Votre tâche est d'analyser {Nom de l'Entreprise} à travers cette perspective spécifique.
## Contexte
Jeremy Grantham enseigne : « Asset class returns revert to the mean. High valuations predict low future returns; low valuations predict high returns. »
## Cadre d'Analyse
### 1. Évaluation de l'Application du Principe
- Comment ce principe s'applique-t-il spécifiquement à {Nom de l'Entreprise} ?
- Quels aspects de l'entreprise sont les plus pertinents pour « Mean Reversion » ?
- Évaluez l'alignement : Fort / Modéré / Faible
- Sur quoi Jeremy Grantham se concentrerait-il en premier ?
### 2. Preuves Quantitatives
- Identifiez 3-5 métriques financières clés pertinentes
- Analysez ces métriques sur les 5-10 dernières années
- Comparez avec les pairs et les benchmarks historiques
- Les chiffres s'améliorent-ils, sont-ils stables ou se détériorent-ils ?
### 3. Analyse Qualitative
- Évaluez les facteurs non quantifiables que Jeremy Grantham examinerait
- Qualité de la gestion et alignement avec ce principe
- Dynamique de l'industrie et position concurrentielle
- Durabilité du modèle d'affaires selon cette perspective
### 4. Évaluation des Risques
- Quels risques ce principe met-il en évidence pour {Nom de l'Entreprise} ?
- Quels signaux d'alarme Jeremy Grantham identifierait-il ?
- Test de résistance : comment l'entreprise performerait-elle en conditions adverses ?
- Quel est le pire scénario selon cette perspective ?
### 5. Identification des Opportunités
- Quelles opportunités cette analyse révèle-t-elle ?
- Y a-t-il des forces cachées sous-évaluées par le marché ?
- Quels catalyseurs pourraient libérer de la valeur ?
### 6. Grantham Verdict
- {Nom de l'Entreprise} passe-t-elle le test de « Mean Reversion » ?
- Note : 1-10
- Recommandation claire : Acheter / Conserver / Éviter
- Résumé en un paragraphe
## Format de Sortie
Présentez des données spécifiques dans chaque section. Terminez par un verdict décisif.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.
Ce contenu n'est disponible qu'en chinois et en anglais pour le moment.
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.
Plus de Prompts de Règles
Explorez d'autres principes d'investissement de ce maître.
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.
→