company-valuation

Estimates public company intrinsic value via DCF, relative multiples, and SOTP triangulation.

3.3k|382|Updated Mar 13, 2026
One-click install
npx skills add https://github.com/himself65/finance-skills --skill company-valuation-himself65
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: company-valuation
Source: https://github.com/himself65/finance-skills/tree/main/plugins/market-analysis/skills/company-valuation
Command: npx skills add https://github.com/himself65/finance-skills --skill company-valuation-himself65

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires yfinance, numpy, pandas, and includes references (resource) components.

What problem does it solve? Answering "what is this stock worth" requires pulling financials, building a DCF, selecting peers, and reconciling multiple valuation methods — a slow, error-prone manual process. This Skill automates the full workflow using yfinance data and produces a blended implied share price with sensitivity analysis. ## Core Features & Use Cases - Three-Method Triangulation: Builds a 5-year FCFF DCF, applies peer median P/E, EV/Revenue, and EV/EBITDA multiples, and runs sum-of-the-parts for multi-segment companies, then blends them into one implied price. - Sensitivity & Scenarios: Outputs a 5×5 WACC × terminal-growth sensitivity matrix plus Bull/Base/Bear scenarios with explicit assumption levers. - Edge-Case Handling: Adapts methodology for banks, REITs, pre-revenue companies, and cyclicals with appropriate fallbacks like P/B, P/FFO, or mid-cycle normalization. - Use Case: Ask "what is NVDA worth" and receive a structured briefing with a headline verdict, DCF build, peer comparison table, sensitivity grid, and key risks. ## Quick Start Ask the agent to estimate the fair value of a ticker, for example: run a DCF and relative valuation on AAPL and tell me if it is overvalued or undervalued.

Frequently Asked Questions about company-valuation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a DCF valuation for a stock in Python?▼

Use yfinance to pull income statements, cash flow, and balance sheet data, then project five years of FCFF using historical margins and consensus growth. Discount at WACC derived from CAPM, add a terminal value, and bridge enterprise value to equity per share.

What valuation methods should I use to find a stock's fair value?▼

Triangulate three methods: a 5-year DCF for intrinsic value, peer median multiples like P/E and EV/EBITDA for market-anchored pricing, and sum-of-the-parts for multi-segment companies. Blend them with weights such as 50/50 or 40/30/30 when SOTP applies.

Can DCF valuation be used for banks or REITs?▼

Standard DCF is inappropriate for banks, insurers, and REITs because debt is operational funding. Use dividend discount or excess return models for financials, P/B or P/TBV multiples for banks, and NAV or P/FFO approaches for REITs instead.

How do I choose peer companies for relative valuation?▼

Select 4-6 peers sharing the same GICS industry, business model, and similar growth and margin profiles, then use the median multiple rather than the mean. Adjust the implied multiple by 10-30% when the target's growth, margins, or leverage diverges materially from peers.

Why does my DCF terminal value dominate the valuation?▼

Terminal value exceeding 80% of enterprise value means the model is effectively a multiple-expansion bet on distant assumptions. Cross-check the Gordon growth TV against an exit-multiple TV, and flag the result if the two diverge by more than 30%.

What data source does this valuation workflow rely on?▼

It uses yfinance for financial statements, analyst estimates, beta, and live 10-year Treasury yields via the ^TNX ticker. The data is unofficial, so any investment decision should be cross-checked against primary filings.