> ## Documentation Index
> Fetch the complete documentation index at: https://docs.driven.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Valuation Matrix

> Driven's Valuation Matrix Skill runs structured valuation with multiple methods, cross-checks against peers and management guidance, and flags data confidence.

Valuation Matrix is Driven's structured valuation workflow. It does not just run one model and hand you a number; it applies multiple valuation approaches, cross-checks the result against peers and management guidance, and flags how much confidence to place in the inputs.

## Framework

A Skill is not a prompt — it is a repeatable capability built on a specific, citable framework and run as real code. Valuation Matrix is grounded in **DCF and reverse DCF**: it discounts projected cash flows to an intrinsic value, then inverts the model to back out the growth and margin assumptions the current price already embeds. It cross-checks that output against **Damodaran valuation multiples** so the result is anchored to peer-implied benchmarks rather than free-form guesswork.

## When to use it

* Putting a defensible value on a company
* Pressure-testing whether a stock is cheap or expensive
* Building the valuation section of an investment thesis
* Comparing a company's valuation against its own history and its peers

## What it does

Valuation Matrix pulls the financial data, applies relevant valuation methods, and, importantly, runs the cross-checks a careful analyst would: it compares the output against peer valuations, checks it against management guidance, and notes the confidence level of the underlying data. This is the difference between a model that produces a number and a workflow that produces a number you can trust.

Because the cross-checks are built into the workflow, you get the peer comparison and guidance reconciliation automatically rather than having to ask for them separately.

## Prompt template

```text theme={null}
Run a Valuation Matrix on [TICKER]. Use multiple valuation methods, cross-check against peers and management guidance, state the key assumptions, and flag data confidence.
```

## Example

```text theme={null}
Value XIAOMI (1810.HK). Use appropriate methods for its business mix, cross-check against peers, be explicit about assumptions, and flag where the data is uncertain.
```

## Tips

* **Check the assumptions first.** A valuation is only as good as its inputs; ask the Agent to surface the key assumptions so you can challenge them.
* **Mind accounting standards and units.** For cross-market names, confirm the analysis is not mixing accounting standards or mismatching reporting periods. Ask the Agent to state which standard and period it used.
* **Re-run with your own assumptions.** If you disagree with a growth or margin assumption, give the Agent yours and have it re-run.

## Related

* [Research a stock](/guides/research/research-a-stock) — the broader single-stock workflow
* [Competitor Analysis](/skills/competitor-analysis) — peer context for the valuation
* [Stock research prompts](/prompts/stock-research-prompts) — more templates
* [Analyze before earnings](/guides/research/analyze-before-earnings) — apply the valuation ahead of an earnings report