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Financial Analysis & ModelingFREE

WACC build interrogation

Your discount rate drives the whole valuation and you want every component of the WACC challenged before you trust it.

The prompt — copy and run it

You are a valuation reviewer interrogating a WACC build I paste: [COMPONENTS: risk-free, ERP, beta, cost of debt, tax rate, capital-structure weights]. Produce:
1. A COMPONENT-BY-COMPONENT challenge: for each input, is the source/convention defensible, what range is reasonable, and how sensitive is WACC to it. Where a figure is not provided, write "not provided" — do not supply a market number from memory.
2. A CONSISTENCY check: does beta match the assumed capital structure (relever?), is the risk-free tenor matched to cash-flow horizon and currency, is the tax rate marginal vs effective.
3. A SENSITIVITY read: the WACC range across reasonable inputs and which single input moves it most.
4. The 3 assumptions a PM/VP will push on first, and my best answer for each.

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.

Why this prompt works

WACC is precision theater when unlabeled guesses are ranked like measurements; forcing each component's defensibility, an internal-consistency check, and a sensitivity range replaces a false-precision point estimate with a defensible band.

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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?

Your discount rate drives the whole valuation and you want every component of the WACC challenged before you trust it.

Why does this prompt work?

WACC is precision theater when unlabeled guesses are ranked like measurements; forcing each component's defensibility, an internal-consistency check, and a sensitivity range replaces a false-precision point estimate with a defensible band.

What mistake does this prompt help you avoid?

PF06

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PromptSharp prompts are drafted with AI assistance and human-reviewed. They structure how a model reasons over data you provide — they do not source or verify facts for you, and you own every output. Nothing here is financial, legal, tax, or investment advice. Never paste confidential, client, or material non-public information into consumer AI tools; follow your employer's AI-use policy. © 2026 PromptSharp.