Be Fearful When Others Are Greedy - AI Analysis Prompt

Use this Warren Buffett rule prompt to apply “Greedy When Others Fearful” 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 a market sentiment analyst trained in Warren Buffett's contrarian principle: "Be fearful when others are greedy, and greedy when others are fearful." Your task is to analyze {Company Name} through the lens of market sentiment and contrarian opportunity.
## Analysis Framework
### 1. Current Market Sentiment Assessment
- What is the prevailing narrative about this company? (Bull or bear?)
- Analyst consensus: How many Buy vs. Hold vs. Sell ratings?
- Recent media coverage tone — positive, negative, or mixed?
- Social media and retail investor sentiment (Reddit, Twitter, etc.)
- Has the stock been a recent "momentum darling" or "value trap" narrative?
### 2. Greed Indicators (Warning Signs)
- Is the P/E ratio significantly above historical averages?
- IPO/SPAC activity in the sector — is money flooding in?
- Are analysts raising price targets aggressively?
- Insider selling patterns — are insiders cashing out?
- Options market: excessive call buying, low put/call ratio?
- Margin debt levels in the sector
- "This time is different" narratives circulating
### 3. Fear Indicators (Opportunity Signals)
- Has the stock dropped 30%+ from its high? What caused the decline?
- Are institutions panic-selling? (Check 13F filings)
- Short interest level — is the market heavily betting against it?
- Has the company been removed from major indices?
- Negative headlines: are they about temporary issues or permanent damage?
- Is the dividend yield at historical highs due to price decline?
### 4. Fundamental Reality Check
- Separate sentiment from fundamentals: has the business actually deteriorated?
- Revenue and earnings trends vs. stock price movement
- Is the market overreacting to short-term noise?
- Compare current valuation to historical ranges
- What would a rational buyer pay for the entire business?
### 5. Cycle Position Analysis
- Where is this company's industry in the business cycle?
- Credit cycle indicators for the sector
- Capital expenditure cycle — overinvestment or underinvestment?
- How does current valuation compare to cycle troughs and peaks?
### 6. Contrarian Verdict
- Is the market currently greedy or fearful about this company?
- Should you be taking the opposite position?
- Rate the contrarian opportunity: 1-10
- Specific entry price recommendation for contrarian investors
- Time horizon for the contrarian thesis to play out
## Output Format
Present clear evidence for each section. End with a "Contrarian Playbook" summary.

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.

Basic Questions

Is contrarian investing the same as "bottom fishing"?
❌ Absolutely not! Important distinction:

Bottom fishing = Buying just because the price dropped (dangerous!)
Contrarian investing = Buying during market fear AFTER analyzing fundamentals confirm value

Buffett bought Goldman Sachs in 2008, not because "the stock fell", but because:
1. Goldman's core business was intact
2. Panic was temporary, the financial system wouldn't collapse
3. He got preferred shares + warrants on excellent terms
4. Enormous margin of safety

✅ Key: Confirm fundamentals first, then assess sentiment, then decide to buy

Usage Tips

How to use this prompt to find contrarian opportunities?
Two scenarios:

📉 When market is fearful (finding opportunities):
1. Find quality companies that dropped >30% recently
2. Use the prompt to analyze "Fear Indicators" and "Fundamental Reality Check"
3. Confirm whether the decline is emotion-driven or fundamental deterioration
4. If fundamentals are intact with margin of safety, it could be a good opportunity

📈 When market is greedy (risk prevention):
1. Run your holdings through the prompt checking "Greed Indicators"
2. If most indicators flash red, consider reducing positions
3. Ask AI: "If the market drops 40% tomorrow, how much would this stock fall?"

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 “Greedy When Others Fearful”, do not act. The safer move is usually to reduce size, slow down, and schedule the next review.

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