What types of valuation methods does this skill support?

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

Is this tool suitable for professional financial advice?

No, this skill is an analytical tool intended for modeling and simulation. All financial decisions should be reviewed by a professional as models are highly dependent on user-provided assumptions.

How does the Monte Carlo simulation handle input uncertainty?

It runs between 1,000 and 10,000 iterations based on user-defined probability distributions and correlation assumptions to provide confidence intervals and statistical risk metrics.

Can the skill generate output files like Excel workbooks?

Yes, the skill is designed to generate complete Excel workbooks including financial projections, free cash flow calculations, and summary valuation tables for external review.

Financial Modeling Suite

Name: Financial Modeling Suite
Author: Microck

byMicrock

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Data Science & ML

Builds professional-grade financial models including DCF analysis, Monte Carlo simulations, and multi-scenario risk assessments.

About

The Financial Modeling Suite is a comprehensive toolkit designed to automate complex investment analysis and valuation tasks using industry-standard methodologies. It enables users to generate detailed Discounted Cash Flow (DCF) models, perform rigorous sensitivity testing with tornado charts, and run high-iteration Monte Carlo simulations to quantify financial uncertainty. Perfect for M&A analysis, LBO modeling, and project finance, this skill ensures structured projections with separated inputs and outputs, providing audit-ready insights for data-driven investment decisions.

Key Features

81 GitHub stars
Structured modeling templates for M&A, LBO, and Project Finance
Automated DCF valuation with WACC and terminal value calculations
Multi-scenario planning for best, base, and worst-case economic environments
High-iteration Monte Carlo simulations for probabilistic risk modeling
Sensitivity analysis with automated tornado chart and data table generation

Use Cases

Conducting stress tests on infrastructure project cash flows to identify critical value drivers
Valuing a growth-stage technology company using historical financials and J-curve projections
Quantifying the probability of hitting ROI targets through statistical risk distribution analysis

About

Key Features

81 GitHub stars
Structured modeling templates for M&A, LBO, and Project Finance
Automated DCF valuation with WACC and terminal value calculations
Multi-scenario planning for best, base, and worst-case economic environments
High-iteration Monte Carlo simulations for probabilistic risk modeling
Sensitivity analysis with automated tornado chart and data table generation

Use Cases

Conducting stress tests on infrastructure project cash flows to identify critical value drivers
Valuing a growth-stage technology company using historical financials and J-curve projections
Quantifying the probability of hitting ROI targets through statistical risk distribution analysis