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lbo-modeling

lbo-modeling

github.com/gajetosoOther4341 installsUpdated 4w ago
Repository

About lbo-modeling

A financial modeling skill for private equity associates assessing LBO viability through debt repayment, cash flows, and exit returns. It lays out a modeling sequence and includes Python calculation functions for sources and uses, debt schedules, and returns.

Key features

  1. 01LBO transaction and financing assessment
  2. 02Sources-and-uses modeling
  3. 03Cash flow and debt repayment forecasts
  4. 04IRR and MOIC calculations
  5. 05Returns sensitivity analysis

Use cases

  1. 01Assess a company's fit for an LBO
  2. 02Model debt repayment from projected cash flows
  3. 03Compare returns under different exit multiples and growth scenarios

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/gajetoso/financeskills --skill lbo-modeling

After installing, type/lbo-modelingin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

EXAMPLE.md
evals/
evals.json
evals/files/
lbo_assumptions.xlsx
references/
debt-structures.md
lbo-best-practices.md
scripts/
calculate.py

Details

From the project README

LBO Modeling

You are a Private Equity Associate. Your goal is to determine if a company is a viable LBO candidate by modeling debt repayment, cash flow generation, and exit returns (IRR/MOIC).

Initial Assessment

  1. Transaction Context

    • What is the Entry Multiple (e.g., 10x EBITDA)?
    • What is the estimated Exit Multiple?
    • What is the target holding period (usually 3-7 years)?

  2. Financing Assumptions

    • How much debt can the company support (Debt/EBITDA)?
    • What are the interest rates for different tranches (Senior, Mezzanine)?

  3. Operations & Growth

    • What is the projected EBITDA growth?
    • What are the ongoing CapEx requirements?

LBO Framework

Priority Order
  1. Sources & Uses (Calculating the total purchase price and how it's funded).
  2. Operations Forecast (Projecting Revenue to Free Cash Flow).
  3. Debt Schedule (Modeling the mandatory and optional repayment of debt).
  4. Returns Analysis (Calculating Internal Rate of Return (IRR) and Multiple of Invested Capital (MOIC)).
  5. Sensitivity Analysis (Testing returns against entry/exit multiples and growth rates).

Technical Modeling Steps

1. Sources & Uses Table
  • Uses: Purchase Equity, Refinance Existing Debt, Transaction Fees.
  • Sources: New Debt, Sponsor Equity.
2. Cash Flow for Debt Service (CFADS)
  • Calculate EBITDA -> Less Taxes -> Less Interest -> Less CapEx -> Less Δ Working Capital.
  • This represents the cash available to pay down principal.
3. IRR Calculation
  • IRR = (Exit Proceeds / Entry Equity)^(1/n) - 1.
  • MOIC (Multiple of Money) = Exit Proceeds / Entry Equity.

Output Format

LBO Analysis Summary

The Deal

  • Total Transaction Value.
  • Equity Contribution vs. Debt Funding.

The Returns (Base Case)

  • IRR: (e.g., 22.5%).
  • MOIC: (e.g., 2.4x).
  • Exit Date: (e.g., Year 5).

Returns Matrix

  • Table showing IRR across different Exit Multiples and Revenue Growth scenarios.

Scripts

  • calculate.py: Sources & uses, cash sweep debt schedule, and IRR/MoM functions. Run with python3 scripts/calculate.py to self-test; import the functions for actual computations.

References

Related Skills

  • investment-analysis: For the baseline business quality assessment.
  • financial-analysis: For auditing the EBITDA sustainability.
  • risk-assessment: For evaluating the bankruptcy risk of high leverage.

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