Valuing Company

Valuing Company

When to use this skill

• When the user asks "Is this company undervalued or overvalued?"
• When a long-term thesis needs valuation discipline.
• When comparing base, bull, and bear assumptions.

Workflow

1. Plan

• Define valuation methods (DCF plus relative multiple cross-check).
• Define scenario set (bear/base/bull) and key drivers.

2. Validate

• Verify assumptions have source support or explicit user-provided hypothesis.
• Verify terminal assumptions are economically plausible.
• Verify units and share counts align with normalized statements.

3. Execute

• Build scenario outputs with implied value per share.
• Run sensitivity checks (growth, margin, discount rate, terminal multiple).
• Report valuation range, not single-point certainty.

Instructions

• Always disclose assumptions before conclusions.
• Use both intrinsic and relative lenses when possible.
• Include downside case and probability-weighted interpretation.
• Treat valuation as conditional, not deterministic.

Minimum assumption table

• Revenue growth path
• Operating margin path
• Reinvestment or capex intensity
• Discount rate / cost of capital
• Terminal growth or exit multiple
• Net debt and diluted shares

Valuation checklist

• Bear/base/bull scenarios included
• Sensitivity matrix included
• Margin of safety explicitly computed
• Risks that break the model identified
• Data recency timestamp included

Output template

## Valuation Summary: <Company>

### Assumptions
| Driver | Bear | Base | Bull |
|---|---:|---:|---:|
| Revenue CAGR | ... | ... | ... |
| Operating Margin | ... | ... | ... |
| Discount Rate | ... | ... | ... |

### Implied Value Per Share
- Bear: ...
- Base: ...
- Bull: ...

### Current Price Comparison
- Current: ...
- Base upside/downside: ...
- Margin of safety status: <Pass/Fail>

### Key Model Risks
- <risk 1>

Error handling

• If critical inputs are missing, return a partial framework and list required inputs.
• If assumptions are internally inconsistent, stop and correct assumptions first.
• If results are highly sensitive, emphasize uncertainty and avoid definitive language.

Resources

• normalizing-financial-statements
• analyzing-business-quality