Never Lose Money - Prompt d'Analyse IA

Use this Warren Buffett rule prompt to apply “Ne Perdez Jamais d Argent” 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 de gestion des risques formé au principe de Warren Buffett : « Never Lose Money » (Ne Jamais Perdre d'Argent). Votre tâche est d'analyser {Nom de l'Entreprise} sous l'angle de la préservation du capital et de la protection contre les pertes.

## Cadre d'Analyse
### 1. Évaluation de la Solidité du Bilan
- Analyse du ratio courant, ratio rapide et position de trésorerie
- Ratio dette/capitaux propres et ratio de couverture des intérêts
- Passifs hors bilan et risques contingents
- Comment se compare le bilan par rapport aux pairs du secteur ?
- L'entreprise pourrait-elle survivre à une récession sévère ?

### 2. Analyse du Risque Baissier
- Quel est le pire scénario réaliste ?
- Combien un investisseur pourrait-il perdre dans le pire des cas ?
- Existe-t-il des risques existentiels (réglementaire, technologique, concurrentiel) ?
- Historique : Quelle a été la plus grande chute et l'entreprise s'est-elle redressée ?

### 3. Évaluation de la Marge de Sécurité
- Quelle est la valorisation actuelle vs. la valeur intrinsèque conservatrice ?
- Quelle est l'ampleur du coussin si les estimations sont erronées ?
- Le prix actuel compense-t-il adéquatement les risques identifiés ?

### 4. Note de Protection du Capital
- Notez de 1 à 10 la capacité de protection du capital
- Recommanderiez-vous cet investissement à quelqu'un qui ne peut pas se permettre de perdre ?

Fournissez une analyse détaillée avec des données spécifiques et une conclusion claire.

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

Why does Buffett make "never lose money" his Rule #1?
This isn't meant literally — it's an investing mindset:

1. Math of compounding: A 50% loss requires a 100% gain to break even
2. Psychological protection: Large losses lead to panic decisions
3. Opportunity cost: Lost capital can't be deployed into the next great opportunity

Buffett means: Before every investment decision, first ask "how much could I lose?" rather than "how much could I gain?"

Usage Tips

Is the AI's "Safety Scale" rating (1-10) reliable?
⚠️ AI's "safety score" should be used as a risk screening tool, not a buy/sell signal.

How to interpret correctly:
- **8-10 points**: Financial fortress companies with extremely low permanent loss risk, but still check if valuation is excessive
- **5-7 points**: Some defensive strength but with weak spots — focus on reviewing the specific risk items AI identified
- **1-4 points**: Significant risk of permanent capital loss — avoid unless you have a special informational edge

Key reminder: AI may underestimate "black swan" risks (fraud, sudden policy changes). A high score doesn't mean zero risk. Combine AI scoring with your own judgment on management integrity.

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 “Ne Perdez Jamais d Argent”, do not act. The safer move is usually to reduce size, slow down, and schedule the next review.

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