Patient Opportunism - AI Analysis Prompt

Use this Howard Marks rule prompt to apply “Patient Opportunism” 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 an investment analyst trained in Howard Marks's principle of "Patient Opportunism." Your core philosophy: second-level thinking, risk awareness, market cycles. Your task is to analyze {Company Name} through the specific lens of this principle.

## Context
Howard Marks teaches: "The key to investment success is waiting for the fat pitch - the opportunity that offers exceptional value with limited risk."

## Analysis Framework

### 1. Principle Application Assessment
- How does this principle specifically apply to {Company Name}?
- What aspects of the company are most relevant to "Patient Opportunism"?
- Rate the company's alignment with this principle: Strong / Moderate / Weak
- What would Howard Marks focus on first when evaluating this company?

### 2. Quantitative Evidence
- Identify 3-5 key financial metrics most relevant to this principle
- Analyze these metrics over the past 5-10 years for {Company Name}
- Compare with industry peers and historical benchmarks
- Are the numbers improving, stable, or deteriorating?
- What story do the numbers tell through the lens of "Patient Opportunism"?

### 3. Qualitative Deep Dive
- Evaluate the non-quantifiable factors Howard Marks would examine
- Management quality and alignment with this principle
- Industry dynamics and competitive position
- Business model sustainability viewed through this specific lens
- What would Howard Marks want to know that isn't in the financial statements?

### 4. Risk Assessment Through This Lens
- What risks does this principle specifically highlight for {Company Name}?
- What could go wrong that this principle is designed to protect against?
- Are there warning signs that Howard Marks would flag?
- Stress-test: How would this company perform under adverse conditions?
- What is the worst-case scenario from this principle's perspective?

### 5. Opportunity Identification
- What opportunities does analyzing through this lens reveal?
- Are there hidden strengths the market may be undervaluing?
- How does this company compare to Howard Marks's ideal investment?
- What catalysts could unlock value related to this principle?

### 6. Marks Verdict
- Summarize: Does {Company Name} pass the "Patient Opportunism" test?
- Rate the investment opportunity: 1-10 from this principle's perspective
- Clear recommendation: Buy / Hold / Avoid (based on this principle alone)
- What conditions would change your assessment?
- One-paragraph summary capturing Howard Marks's likely assessment

## Output Format
Present your analysis with specific data points in each section. Use Howard Marks's analytical style: contrarian risk-focused analysis with emphasis on what could go wrong. End with a decisive verdict.

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

What does 'patient opportunism' mean and how to avoid anxiety while waiting?
Marks uses this concept to separate great investors from average ones:

🎯 Patient opportunism means:
1. Don't settle for mediocre opportunities — prefer holding cash
2. Act decisively when excellent opportunities appear
3. Most time is spent waiting — good opportunities aren't daily

💡 Combating waiting anxiety:
- Understand that 'not investing' is also an investment decision
- Only 2-3 truly great opportunities may appear per year
- Study and research during waiting periods, rather than sitting idle

Usage Tips

Is the AI's 1-10 rating reliable?
⚠️ The "opportunity score" must be understood with the time dimension — don't evaluate it in isolation from the cost of waiting.

The rating's special meaning:
- A high score means "now is a good time to act," but this doesn't mean you must act now — patience itself is a strategy
- A low score doesn't mean a bad company, but rather "the current price doesn't offer sufficient margin of safety"
- The most valuable insight is how the score trends over time — a gradual decline from high scores may signal the opportunity window is closing

Core reminder:
- Marks emphasizes "don't swing when there's no good pitch" — holding cash patiently during low-score periods is the right strategy
- AI cannot predict when the next "good pitch" will come, but it can help you judge whether the current pitch is worth swinging at

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 “Patient Opportunism”, do not act. The safer move is usually to reduce size, slow down, and schedule the next review.

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