lbo-model

Build leveraged buyout models in Excel with debt schedules, cash sweeps, and IRR/MOIC sensitivity tables.

Updated Jun 5, 2026
One-click install
npx skills add https://github.com/xu1713/openhorse --skill lbo-model-xu1713
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: lbo-model
Source: https://github.com/xu1713/openhorse/tree/main/openhorse/openhorse/optional-skills/finance/lbo-model
Command: npx skills add https://github.com/xu1713/openhorse --skill lbo-model-xu1713

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openpyxl.

What problem does it solve? Building an LBO model from scratch in Excel is error-prone: circular interest references, unbalanced Sources & Uses, broken cash sweeps, and sensitivity tables that don't tie to the base case. This Skill produces formula-driven, template-based LBO models in .xlsx format with validated calculations and professional formatting. ## Core Features & Use Cases - Template-Driven Modeling: Populates a provided LBO template or a standard structure covering Sources & Uses, Operating Model, Debt Schedule, and Returns Analysis, with every calculation written as a live Excel formula via openpyxl. - Returns & Sensitivity Analysis: Computes IRR and MOIC with correct cash flow signs, and builds odd-dimension sensitivity grids whose center cell ties exactly to the model's base case. - Section-by-Section Verification: Checks in with the user after each major section and runs a recalculation pass before delivery to catch errors early. - Use Case: A private equity analyst needs an illustrative LBO for a pitch. Provide the entry multiple, leverage, and operating assumptions, and receive a formatted .xlsx model with a debt waterfall, cash sweep, and 5x5 IRR sensitivity table. ## Quick Start Build an LBO model in Excel using my attached template with a 10x entry multiple, 5x leverage, and a 5-year hold, including IRR and MOIC sensitivity tables.

Frequently Asked Questions about lbo-model

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

FAQPage Schema
How do I build an LBO model in Excel with Python?

Use openpyxl to write formula strings like ws["D20"] = "=B5*B6" into a template workbook, never hardcoding computed values. After populating Sources & Uses, the debt schedule, and returns, run a recalculation script to validate all formulas before delivery.

How do I avoid circular references in an LBO debt schedule?

Calculate interest on the beginning debt balance rather than the average or ending balance. This breaks the circle where interest affects cash flow, which affects paydown, which affects the ending balance that interest would otherwise reference.

Can openpyxl create Excel sensitivity tables for IRR?

Excel's native DATA TABLE function does not work reliably with openpyxl, so write explicit formulas in each cell using mixed references like $A5 and B$4. Use odd grid dimensions such as 5x5 so the center cell equals the model's base-case IRR.

Why does my LBO sensitivity table show the same value in every cell?

Identical values mean the formulas are not varying with the row and column inputs. Check that each cell uses mixed references pointing to the axis headers, and confirm the axis values are symmetric around the base case assumption.

What formatting conventions do professional LBO models use?

Hardcoded inputs use blue font, calculated formulas black, same-tab links purple, and cross-tab links green. Fills stay minimal with dark blue section headers, light blue column headers, and medium blue for key outputs like IRR and MOIC.