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Startup Valuation Engine

80+ valuation formulas. Scientific rigor. Open source.

A production-grade Python library implementing every formula from the Startup Valuation textbook. Designed for analysts, developers, students, and AI agents who need auditable, transparent valuation computations.

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Who are you?

If you want to...	Start here
Learn how startup valuation works	Start Here — installation, 5-minute example
Understand a specific valuation method	Methods — pick a method below
Value a real startup	How to Value a Startup — step-by-step workflow
Use the Python library	API Reference — auto-generated docs
Use the MCP server with AI agents	MCP Server — 60+ tools
Contribute a new method	Contributing

Methods

Foundation

• Probability & Time Value — Expected value, NPV, Poisson, annuities
• CAPM — Capital Asset Pricing Model, startup-adjusted beta

Core Valuation

• Core Methods — Scorecard, Berkus, Risk Factor Summation, VC Method

Advanced

• Advanced Methods — Black-Scholes, Binomial Trees, Monte Carlo, Scenario Analysis
• Comparables — P/E, P/S, EV/EBITDA, regression-adjusted multiples

Industry-Specific

• SaaS Metrics — LTV, CAC, NRR, Magic Number, Rule of 40
• Biotech — rNPV, decision trees, peak sales, pipeline valuation
• Fintech — Payment revenue, lending, neobank, network effects
• Marketplace — GMV, take rate, liquidity, network density
• Hardware — TRL-adjusted, break-even, probability-weighted DCF

Cross-Cutting

• International — PPP, CRP, currency-adjusted DCF
• Stakeholders — Dilution, OPM, PWERM, liquidation preferences
• Emerging — SAFE, MV=PQ (crypto), ESG, Metcalfe's Law

Resources

Resource	Link
📦 PyPI	pypi.org/project/startup-valuation
📖 API Docs	simonplmak-cloud.github.io/startup-valuation
💻 Source Code	github.com/simonplmak-cloud/startup-valuation
📚 Textbook	Startup Valuation on Amazon
🛠️ MCP Server	mcp_server/server.py
📝 Changelog	CHANGELOG.md

Notation

See the Glossary for the canonical symbol table mapping mathematical notation to code variables.

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Last verified: 2026-08-11 | Version: 1.0.2