Simplicity Wins - AI Analysis Prompt

Use this Joel Greenblatt rule prompt to apply “Simplicity Wins” 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 Joel Greenblatt's principle of "Simplicity Wins." Your core philosophy: magic formula, systematic value, special situations. Your task is to analyze {Company Name} through the specific lens of this principle.

## Context
Joel Greenblatt teaches: "Complex strategies rarely beat simple ones. The best investment approach is one you can understand and stick to."

## Analysis Framework

### 1. Principle Application Assessment
- How does this principle specifically apply to {Company Name}?
- What aspects of the company are most relevant to "Simplicity Wins"?
- Rate the company's alignment with this principle: Strong / Moderate / Weak
- What would Joel Greenblatt 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 "Simplicity Wins"?

### 3. Qualitative Deep Dive
- Evaluate the non-quantifiable factors Joel Greenblatt would examine
- Management quality and alignment with this principle
- Industry dynamics and competitive position
- Business model sustainability viewed through this specific lens
- What would Joel Greenblatt 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 Joel Greenblatt 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 Joel Greenblatt's ideal investment?
- What catalysts could unlock value related to this principle?

### 6. Greenblatt Verdict
- Summarize: Does {Company Name} pass the "Simplicity Wins" 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 Joel Greenblatt's likely assessment

## Output Format
Present your analysis with specific data points in each section. Use Joel Greenblatt's analytical style: quantitative value screening using earnings yield and return on capital. 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

Why do simple investment strategies often outperform complex ones?
Core idea: simple investment strategies often outperform complex ones

✅ 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

How reliable are analysis ratings for simplicity-based investment strategies?
The reliability of simplicity-based strategy analysis comes precisely from its simplicity—the fewer variables used, the lower the risk of model overfitting, and out-of-sample performance is typically more robust. Greenblatt's research and extensive academic literature demonstrate that simple value factors (such as earnings yield and book-to-market ratio) consistently outperform complex multi-factor models over the long term. Analytical ratings are reliable in highlighting the systematic advantages of simple strategies, but investors should note that simplicity does not mean universal applicability—during momentum-driven markets or bubble periods, value strategies may fail for extended periods. The most valuable application of ratings is helping investors resist the temptation of complexity and maintain investment discipline.

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

More Rule Prompts

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