Reversion to the Mean - Prompt d'Analyse IA
Use this John Bogle rule prompt to apply “Retour à la Moyenne” 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 John Bogle : « Reversion to the Mean ». Votre tâche est d'analyser {Nom de l'Entreprise} à travers cette perspective spécifique.
## Contexte
John Bogle enseigne : « Fund returns tend to revert to the mean. Yesterday's winners become tomorrow's losers, and vice versa. »
## 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 « Reversion to the Mean » ?
- Évaluez l'alignement : Fort / Modéré / Faible
- Sur quoi John Bogle 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 John Bogle 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 John Bogle 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. Bogle Verdict
- {Nom de l'Entreprise} passe-t-elle le test de « Reversion to the Mean » ?
- 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
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 “Retour à la Moyenne”, 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.
Assez
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