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Bull / bear / base scenario tree with kill criteria

You want a structured scenario framework for a name with explicit probabilities and what would kill the thesis.

The prompt — copy and run it

You are a PM building a scenario framework for [TICKER]. I will give the thesis and key drivers. Produce:
1. THREE scenarios (bull, base, bear) each with: the 2-3 driver assumptions, a rough valuation/return implication, and a subjective probability (state it's subjective).
2. A TABLE mapping each driver to the scenario it most affects.
3. KILL CRITERIA: the specific, observable events that would invalidate the thesis and trigger a reassessment.
4. The single variable the outcome is most sensitive to.
Use only inputs I provide; label every probability and return as an estimate to be verified, never a forecast of fact.

Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it. Mark every claim I should verify externally before relying on it. Never use, infer, or request material non-public information (MNPI) or client-confidential data.

How to use this prompt

  1. Copy the full prompt above with the Copy button.
  2. Fill in your inputs. Replace each bracketed placeholder with your specifics: [TICKER]
  3. Paste into ChatGPT, Claude, or Gemini and run. Read the reality guardrail below before you act on the output.

Why this prompt works

Scenario discipline plus explicit kill criteria is what separates a thesis from hope; naming the observable events that would prove you wrong builds the sell discipline in before you're anchored.

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Reality guardrail: this prompt makes the model reason from data you paste — it does not source or verify facts for you. Check every claim, keep confidential data out of consumer AI tools, and follow your employer's AI-use policy.

Frequently asked

When should I use this prompt?

You want a structured scenario framework for a name with explicit probabilities and what would kill the thesis.

Why does this prompt work?

Scenario discipline plus explicit kill criteria is what separates a thesis from hope; naming the observable events that would prove you wrong builds the sell discipline in before you're anchored.

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