Calculate IRR and MOIC for private equity deal evaluations.
npx skills add https://github.com/smrik/ai-fund --skill returns-analysis-smrik
Please help me install this Agent Skill. Skill: Returns Analysis Source: https://github.com/smrik/ai-fund/tree/main/skills/private-equity/skills/returns-analysis Command: npx skills add https://github.com/smrik/ai-fund --skill returns-analysis-smrik
This Skill removes the manual friction of building complex private equity return models, allowing for rapid iteration on deal assumptions and stress-testing of investment outcomes.
Use the returns analysis skill to model a deal with 8x entry multiple and 3x leverage to generate a sensitivity table for exit multiples.
High-intent search queries and answers about installing and using this skill.
To calculate IRR and MOIC for private equity deal evaluations, input structured financial data like entry multiples and leverage to generate formatted returns waterfalls and sensitivity matrices.
Generating sensitivity tables for private equity returns requires modeling multi-scenario variables like entry/exit multiples, leverage, and growth to produce 2-way matrices that stress-test investment outcomes.
A returns waterfall attributes private equity performance by decomposing overall returns into growth, multiple expansion, and debt paydown to isolate the drivers of MOIC and IRR.
Yes, you can model leverage and hold period variables for deal sensitivity analysis. The tool supports multi-scenario sensitivity analysis incorporating these variables to produce formatted returns matrices.
Private equity returns modeling requires structured financial inputs such as entry multiples, leverage ratios, EBITDA assumptions, and hold periods to calculate IRR and generate sensitivity tables.
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