Research-Based Investing - AI Analysis Prompt
Use this John Templeton rule prompt to apply “Research-Based Investing” 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 John Templeton's principle of "Research-Based Investing." Your core philosophy: global contrarian investing, maximum pessimism, spiritual approach. Your task is to analyze {Company Name} through the specific lens of this principle.
## Context
John Templeton teaches: "Never buy a stock without thorough research. Know what you own and why you own it."
## Analysis Framework
### 1. Principle Application Assessment
- How does this principle specifically apply to {Company Name}?
- What aspects of the company are most relevant to "Research-Based Investing"?
- Rate the company's alignment with this principle: Strong / Moderate / Weak
- What would John Templeton 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 "Research-Based Investing"?
### 3. Qualitative Deep Dive
- Evaluate the non-quantifiable factors John Templeton would examine
- Management quality and alignment with this principle
- Industry dynamics and competitive position
- Business model sustainability viewed through this specific lens
- What would John Templeton 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 John Templeton 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 John Templeton's ideal investment?
- What catalysts could unlock value related to this principle?
### 6. Templeton Verdict
- Summarize: Does {Company Name} pass the "Research-Based Investing" 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 John Templeton's likely assessment
## Output Format
Present your analysis with specific data points in each section. Use John Templeton's analytical style: global contrarian analysis buying at points of maximum pessimism. End with a decisive verdict.Related reading (close the loop)
Pick one path below to turn the output into a checkable, repeatable decision policy.
- Read the matching principleDefinition, boundaries, pitfalls, and a minimal checklist.
- Master profileMethodology summary + common misreads for this framework.
- Practice in scenariosTranslate conclusions into “what I do under stress”.
- More prompts from this masterTriangulate with multiple rules instead of anchoring on one prompt.
Educational only. Verify facts with primary sources and apply your own constraints.
Basic Questions
How does Templeton's deep research differ from modern quantitative analysis?
Core idea: all investment decisions must be built on thorough research
✅ 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.
✅ 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
Is the AI's 1-10 rating reliable?
⚠️ The research depth score measures "how much homework you've done," not whether conclusions are correct.
The rating's unique logic:
- Templeton believed: "The more homework you do, the luckier you get" — thorough research doesn't guarantee success but dramatically increases success probability
- A high score means your analysis is built on sufficient data foundation, though data itself may be outdated or incomplete
- A low score is a clear warning: making investment decisions without sufficient research is essentially gambling
Usage principles:
- AI can rapidly process vast data, but cannot replace your firsthand research — Templeton personally visited over a hundred countries
- Research's purpose isn't eliminating uncertainty but understanding where uncertainty lies
- Don't equate "lots of information" with "thorough research" — the key is whether you've identified the core variables affecting the investment decision
The rating's unique logic:
- Templeton believed: "The more homework you do, the luckier you get" — thorough research doesn't guarantee success but dramatically increases success probability
- A high score means your analysis is built on sufficient data foundation, though data itself may be outdated or incomplete
- A low score is a clear warning: making investment decisions without sufficient research is essentially gambling
Usage principles:
- AI can rapidly process vast data, but cannot replace your firsthand research — Templeton personally visited over a hundred countries
- Research's purpose isn't eliminating uncertainty but understanding where uncertainty lies
- Don't equate "lots of information" with "thorough research" — the key is whether you've identified the core variables affecting the investment decision
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 “Research-Based Investing”, do not act. The safer move is usually to reduce size, slow down, and schedule the next review.
More Rule Prompts
Explore other investment principles from this master.
Sell Discipline
The time to sell is before the crash, not after. Sell when optimism is at its peak and better opportunities exist elsewhere.
→Flexibility
It is impossible to produce superior performance unless you do something different from the majority. Be flexible in your approach.
→Patience and Perseverance
The only investors who shouldn't diversify are those who are right 100% of the time. For the rest of us, patience and diversification are key.
→Humility in Investing
An investor who has all the answers doesn't even understand the questions. Humility is essential for long-term success.
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