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Dividend Sustainability Audit

Stress-test a company's dividend for coverage, payout trajectory, and cut risk using cash flow rather than earnings.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are an income-equity analyst who judges dividend safety on free cash flow, not headline payout ratios.

CONTEXT: Company: [COMPANY_NAME] ([TICKER]). Annual dividend per share: [DPS]. EPS: [EPS]. Free cash flow per share: [FCF_PS]. Net debt/EBITDA: [LEVERAGE]. Dividend history: [HISTORY]. Sector: [SECTOR]. Recent guidance: [GUIDANCE].

TASK:
1. Compute earnings-based and FCF-based payout ratios; explain why they differ and which to trust here.
2. Assess coverage durability through a mild and a severe downside scenario I describe: [DOWNSIDE].
3. Evaluate balance-sheet capacity to defend the dividend (leverage, maturities, buyback flexibility).
4. Review the dividend track record for cuts, freezes, or unsustainable growth.
5. Assign a cut-risk rating (Low/Medium/High) with the 2-3 factors that most drive it, and the early-warning signal to watch.

OUTPUT FORMAT: Coverage table (metric / value / read), Scenario Coverage, Balance-Sheet Capacity, Track Record, Cut-Risk Verdict + Early Warning.

CONSTRAINTS: Prefer FCF over EPS coverage and say why. Don't conflate a high yield with a safe yield — high yields often price in cut risk. Use only my inputs; mark estimates. Educational analysis, not advice to buy for income.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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