Does it generate code or just calculations?

It provides both: the skill can perform direct financial calculations and generate reusable Python scripts for reproducible modeling and data visualization.

What types of valuation methods are supported?

The skill supports Discounted Cash Flow (DCF), M&A accretion/dilution, Leveraged Buyout (LBO), and Project Finance modeling using industry-standard methodologies.

Can I use this for risk management?

Yes, it includes advanced Monte Carlo simulation capabilities and sensitivity analysis (tornado charts) to quantify risks and model uncertainty in key inputs.

What data do I need to provide for a DCF?

You typically need 3-5 years of historical financial statements, revenue growth assumptions, operating margin projections, and capital expenditure forecasts.

Financial Modeling Suite

Name: Financial Modeling Suite
Author: LisaPullman

byLisaPullman

Data Science & ML

Builds sophisticated financial models including DCF analysis, Monte Carlo simulations, and scenario planning for investment decisions.

About

This advanced financial modeling suite empowers analysts and investors to perform professional-grade valuations and risk assessments directly within Claude Code. It automates complex calculations like Weighted Average Cost of Capital (WACC), terminal value projections, and probability-weighted scenario testing using industry-standard methodologies. Whether you are evaluating a corporate acquisition, analyzing a leveraged buyout (LBO), or projecting infrastructure project returns, this skill provides the structured frameworks and Python-based engines needed to generate robust financial insights and decision-ready outputs.

Key Features

Specialized templates for M&A, LBO, and Project Finance modeling
0 GitHub stars
Monte Carlo simulations for probabilistic risk and uncertainty modeling
Interactive sensitivity analysis with tornado charts and data tables
Automated DCF valuation with WACC and terminal value calculations
Multi-case scenario planning (Best/Base/Worst) with probability weighting

Use Cases

Valuing private or public companies using historical financial statements and growth assumptions
Evaluating the accretion/dilution impact and synergy potential of a corporate merger
Assessing investment risk through 10,000+ Monte Carlo iterations on volatile market drivers

About

Key Features

Specialized templates for M&A, LBO, and Project Finance modeling
0 GitHub stars
Monte Carlo simulations for probabilistic risk and uncertainty modeling
Interactive sensitivity analysis with tornado charts and data tables
Automated DCF valuation with WACC and terminal value calculations
Multi-case scenario planning (Best/Base/Worst) with probability weighting

Use Cases

Valuing private or public companies using historical financial statements and growth assumptions
Evaluating the accretion/dilution impact and synergy potential of a corporate merger
Assessing investment risk through 10,000+ Monte Carlo iterations on volatile market drivers