intangible-valuation 0.1.0

Python library for intangible asset valuation implementing cost, market, and income approaches. 124+ functions for patents, brands, goodwill, PPA, and more.

Intangible Asset Valuation Engine

Complete intangible asset valuation library implementing 124+ functions from the Intangible Asset Valuation textbook. Python library + MCP server + AI-Agent Skills.

Overview

A production-grade Python library for intangible asset valuation, implementing every formula from the Intangible Asset Valuation textbook by Simon Mak, William Yuen, Paul Wu, and Wayne Hu (Valuation in Practice Series, Ascent Partners). Designed for developers, financial analysts, accountants, and AI agents who need auditable, structured valuation computations for ASC 805 / IFRS 3 compliant workflows.

Three-layer architecture:

1. Python Library — 22 modules, 124+ typed functions, all returning ValuationResult (value + assumptions + sensitivity)
2. MCP Server — 54 tools for AI agents (Claude, OpenCode, etc.) via stdio/SSE
3. AI-Agent Skills — 3 skill definitions with workflow guidance for valuation domains

Installation

pip install intangible-valuation          # library only
pip install intangible-valuation[mcp]     # + MCP server
pip install intangible-valuation[dev]     # + pytest, ruff, mypy

Quick Start

Python Library

from intangible_valuation.core.time_value import present_value
from intangible_valuation.core.discount_rates import build_up_discount_rate
from intangible_valuation.income_methods.relief_from_royalty import relief_from_royalty

# Present Value
result = present_value(future_value=500_000, discount_rate=0.10, periods=8)
print(f"PV: ${result.value:,.2f}")  # $233,253.69

# Build-Up Discount Rate
rate = build_up_discount_rate(
    risk_free_rate=0.04, equity_risk_premium=0.06,
    size_premium=0.02, industry_risk_premium=0.01, specific_risk_premium=0.03,
)
print(f"Discount rate: {rate.value:.2%}")  # 16.00%

# Relief from Royalty — Patent Valuation
value = relief_from_royalty(
    revenue_projections=[1_000_000, 1_100_000, 1_200_000, 1_300_000, 1_400_000],
    royalty_rate=0.05, discount_rate=0.12, tax_rate=0.25, useful_life=5,
)
print(f"Patent value: ${value.value:,.2f}")

MCP Server (for AI Agents)

cd mcp_server && python server.py

Connect with any MCP-compatible AI agent. All 54 valuation tools available.

AI-Agent Skills

Copy the skills/ directory to your agent's skills folder:

• asset-valuation — Patents, trademarks, technology, customer relationships, human capital
• discount-rate-construction — Build-up, CAPM, WACC, risk premiums, adjustments
• purchase-price-allocation — ASC 805 / IFRS 3 PPA workflow, goodwill calculation, impairment testing

Valuation Methods by Category

Category	Methods	Chapter
Time Value	PV, FV, annuity, perpetuity, growing annuity, terminal value	2
Discount Rates	Build-up, CAPM, WACC, TAB, control premium, DLOM, currency adjustment	2
Statistics	Monte Carlo, decision trees, regression	2
Cost Approach	Reproduction cost, replacement cost	3
Market Approach	Comparable transactions, royalty capitalization	3
Income Methods	Relief from Royalty, MPEEM, incremental cash flow	4
Intellectual Property	Patent, trademark, copyright, trade secret	5
Royalty Analysis	Benchmarking, 25% rule, adjustment	6
Technology	Developed technology, software, data assets, platforms	7
Customer-Related	Customer relationships, distribution network, non-compete	8
Human Capital	Assembled workforce, key person	9
Goodwill & PPA	Goodwill calculation, PPA waterfall	10
Impairment	Goodwill & intangible impairment (ASC 350 / IAS 36)	11
Monte Carlo	Simulation, sensitivity analysis	15
Decision Trees	Backward induction	16
Litigation	Lost profits, pre-judgment interest	17
Transfer Pricing	CUP method, OECD guidelines	18

Why This Library?

• Auditable — Every function returns ValuationResult with value, method, inputs, assumptions, and step-by-step calculation breakdown
• Textbook-accurate — All 124+ formulas verified against book example values with 698 unit tests
• AI-ready — MCP server and Skills for seamless AI agent integration
• Complete coverage — All three valuation approaches (cost, market, income) across 19 chapters
• Open source — MIT license, extensible, well-documented

Development

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Run with coverage
pytest --cov=src --cov-report=term-missing

# Lint
ruff check .

# Type check
mypy src/

Documentation

• API Reference: GitHub Pages
• PyPI: pypi.org/project/intangible-valuation
• MCP Server Guide: docs/mcp.md
• AI Skills Guide: docs/skills.md

Companion Textbook

Intangible Asset Valuation: A Comprehensive Guide to Valuing Brands, IP, Technology, and Human Capital
Theory, Methods, Regulation, and Practice — Valuation in Practice Series by Ascent Partners
By Simon Mak, William Yuen, Paul Wu, Wayne Hu · 176 pages · 19 chapters · 3 appendices

Citing This Project

@software{intangible_valuation_engine,
  author = {Mak, Simon and Yuen, William and Wu, Paul and Hu, Wayne},
  title = {Intangible Asset Valuation Engine},
  year = {2026},
  url = {https://github.com/simonplmak-cloud/intangible-valuation},
  license = {MIT},
}

Based on formulas from the Intangible Asset Valuation textbook.

License

MIT — see LICENSE for details.