returns-analysis

Automate IRR and MOIC returns modeling for private equity deal evaluation.

31|4|Updated Jun 13, 2026
One-click install
npx skills add https://github.com/r9412460971-cloud/OPC-skill --skill returns-analysis-r9412460971-cloud
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: returns-analysis
Source: https://github.com/r9412460971-cloud/OPC-skill/tree/main/skills/returns-analysis
Command: npx skills add https://github.com/r9412460971-cloud/OPC-skill --skill returns-analysis-r9412460971-cloud

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Private equity deal teams waste hours on manual returns calculations and assumption stress-testing, leading to inconsistent results and delayed investment committee approvals.

Core Features & Use Cases

  • Automated Returns Calculation: Computes IRR, MOIC, and cash-on-cash metrics with clear attribution to EBITDA growth, multiple expansion, and debt paydown.
  • Sensitivity & Scenario Analysis: Generates 2-way sensitivity matrices across entry/exit multiples, growth, leverage, and hold periods, plus bull/base/bear scenario comparisons for IC exhibits.
  • Use Case: A PE associate evaluating a $100M manufacturing buyout can use this skill to quickly model how a 0.5x drop in exit multiple impacts returns across different leverage levels for the investment committee deck.

Quick Start

Use the returns-analysis skill to build a sensitivity table for a $50M equity check with 8x entry EBITDA multiple, 5-year hold period, and 7x to 10x exit multiple range.

Frequently Asked Questions about returns-analysis

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

FAQPage Schema
How do I calculate IRR and MOIC sensitivity tables for a private equity deal?

To calculate IRR and MOIC sensitivity tables for private equity deals, use automated returns modeling to generate 2-way sensitivity matrices across entry/exit multiples, growth, leverage, and hold periods. This eliminates manual calculation errors during deal evaluation and due diligence.

What's the best way to stress-test PE returns for an investment committee deck?

The best way to stress-test PE returns for investment committee decks is generating bull/base/bear scenario comparisons alongside sensitivity matrices. This automated approach produces formatted IC-ready returns summaries that support investment decision-making across buyout, growth equity, and venture capital transactions.

Can I model how exit multiple drops impact returns across different leverage levels?

Yes, you can model how exit multiple drops impact returns across different leverage levels using 2-way sensitivity matrices. This functionality specifically supports pre-investment stress-testing by computing IRR and MOIC metrics with clear attribution to EBITDA growth, multiple expansion, and debt paydown.

Does returns modeling work for both buyout and growth equity transactions?

Returns modeling works for buyout, growth equity, and venture capital transactions. The skill supports deal sizing workflows across these transaction types by automating IRR, MOIC, and cash-on-cash metric calculations for comprehensive pre-investment evaluation and investment committee preparation.

How do I build a returns sensitivity table for a specific equity check size and hold period?

Build a returns sensitivity table by inputting your equity check size, entry EBITDA multiple, hold period, and exit multiple range. For example, model a $50M equity check at 8x entry EBITDA multiple over a 5-year hold period across a 7x to 10x exit multiple range.

What metrics are included in a PE deal evaluation returns analysis?

PE deal evaluation returns analysis includes IRR, MOIC, and cash-on-cash metrics with clear attribution to EBITDA growth, multiple expansion, and debt paydown. These calculations support deal sizing workflows and formatted scenario comparisons for investment committee-ready returns summaries.