Long-term Perspective - Prompt d'Analyse IA

Use this Benjamin Graham rule prompt to apply “Perspective à Long Terme” 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 Benjamin Graham : « Long-term Perspective ». Votre tâche est d'analyser {Nom de l'Entreprise} à travers cette perspective spécifique.

## Contexte
Benjamin Graham enseigne : « The investor should be guided by long-term considerations and not by short-term market fluctuations. »

## 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 « Long-term Perspective » ?
- Évaluez l'alignement : Fort / Modéré / Faible
- Sur quoi Benjamin Graham 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 Benjamin Graham 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 Benjamin Graham 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. Graham Verdict
- {Nom de l'Entreprise} passe-t-elle le test de « Long-term Perspective » ?
- 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.

Educational only. Verify facts with primary sources and apply your own constraints.

ℹ️Ce contenu n'est disponible qu'en chinois et en anglais pour le moment.

Basic Questions

How does Graham's long-term perspective differ from modern 'long-termism'?
Graham's long-term perspective has unique characteristics:

1. Value-anchored: Long-term holding requires buying well below intrinsic value
2. Not blind holding: Sell if fundamentals deteriorate or price far exceeds value
3. Patient mean reversion: The market is a voting machine short-term, a weighing machine long-term

Modern 'long-termism' often becomes self-consolation after being trapped, while Graham's approach is built on rigorous value analysis.

Usage Tips

Is the AI's 1-10 rating reliable?
⚠️ AI's "long-term value score" reflects the company's attractiveness for long-term holding, not short-term trading value.

How to interpret:
- **8-10 (excellent long-term hold)**: Durable competitive advantages, stable financials, foreseeable growth path
- **5-7 (patience needed)**: Long-term logic holds but short-term challenges exist — suitable for gradual entry during pullbacks
- **1-4 (uncertain long-term outlook)**: Competitive advantage unclear or industry changing too fast — not suitable as core long-term holding

Graham emphasized: In the short run the market is a voting machine, in the long run a weighing machine. AI scoring helps you focus on the company's real weight, not the market's votes.

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 “Perspective à Long Terme”, do not act. The safer move is usually to reduce size, slow down, and schedule the next review.

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