modeling-growth-equity-returns
Builds growth equity return models with minority/majority economics, participation rights, and preference stack analysis. Use when modeling growth equity returns, projecting minority investment outcomes, or analyzing preference structures.
Best use case
modeling-growth-equity-returns is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Builds growth equity return models with minority/majority economics, participation rights, and preference stack analysis. Use when modeling growth equity returns, projecting minority investment outcomes, or analyzing preference structures.
Teams using modeling-growth-equity-returns should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/modeling-growth-equity-returns/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How modeling-growth-equity-returns Compares
| Feature / Agent | modeling-growth-equity-returns | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Builds growth equity return models with minority/majority economics, participation rights, and preference stack analysis. Use when modeling growth equity returns, projecting minority investment outcomes, or analyzing preference structures.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Modeling Growth Equity Returns ## When To Use - Projecting gross and net returns for a minority or majority growth equity investment - Analyzing how liquidation preference stacks, participation rights, and anti-dilution provisions affect investor economics across exit scenarios - Comparing return profiles between participating preferred, non-participating preferred, and common equity structures - Stress-testing entry valuation, hold period, and exit multiple assumptions for an expansion-stage deal - Evaluating co-invest or follow-on allocation decisions within a growth equity portfolio ## Inputs To Gather - **Deal terms**: Investment amount, pre-money valuation, ownership percentage, share class, liquidation preference multiple (1x, 1.5x, etc.), participation cap (if any), anti-dilution mechanism (broad-based weighted average vs. full ratchet) - **Capital structure**: Existing cap table with all prior preferred rounds, option pool size, outstanding convertible instruments (SAFEs, notes), any pay-to-play provisions - **Operating forecasts**: Revenue, EBITDA/EBIT, or net income projections for each year of hold period; gross margin trajectory; expected cash burn or free cash flow profile - **Exit assumptions**: Target hold period (typically 3–7 years), exit revenue/EBITDA multiples, probability-weighted exit scenarios (IPO, strategic sale, secondary, recap) - **Follow-on / dilution**: Expected future funding rounds, anticipated dilution per round, pro-rata rights and whether the fund intends to exercise them - **Fee and carry structure** (for fund-level returns): Management fee rate, carry percentage, preferred return/hurdle rate, GP catch-up, fund-level recycling assumptions ## Workflow 1. **Map the cap table** — Build the current ownership waterfall including all preferred layers, common, and option pool. Confirm conversion ratios and any ratchet triggers. [VERIFY] anti-dilution provision language from the term sheet or charter. 2. **Construct the preference stack** — Order liquidation preferences by seniority (pari passu vs. stacked). Model each layer's claim: preference amount, accrued dividends (if cumulative), and participation rights. Calculate the "as-converted" breakpoint where preferred holders would elect to convert to common. 3. **Build exit waterfall scenarios** — For each exit value (e.g., 0.5×–5× of post-money): - Pay senior preferences first, then junior preferences - Distribute remaining proceeds per participation rights (uncapped, capped, or non-participating) - Compare participating vs. as-converted payout at each exit value to determine optimal election - Output investor cash-on-cash and IRR at each scenario point 4. **Model the operating case** — Project revenue and margin over the hold period using management forecasts and comparable company benchmarks. Apply a base, upside, and downside case. Tie exit enterprise value to exit-year revenue or EBITDA × selected multiple. 5. **Layer in dilution and follow-on** — Simulate future rounds with estimated pre-money valuations. Reduce ownership proportionally unless pro-rata is exercised. Recalculate waterfall economics post-dilution. 6. **Calculate return metrics** — For each scenario compute: - Gross MOIC (multiple on invested capital) - Gross IRR - Net MOIC and net IRR (after management fees and carried interest) - DPI (distributions to paid-in) if modeling interim liquidity events 7. **Run sensitivity analysis** — Build two-way data tables varying entry multiple vs. exit multiple, and hold period vs. revenue growth rate. Highlight breakeven and target-return thresholds (e.g., 3× MOIC, 25% IRR). ## Output - **Waterfall summary table**: For each exit scenario, show total proceeds, preference payouts by layer, common distribution, and investor share - **Return matrix**: Gross and net MOIC/IRR across base, upside, and downside cases - **Sensitivity tables**: Two-way tables on key variable pairs (entry valuation vs. exit multiple; growth rate vs. hold period) - **Breakeven analysis**: Minimum exit value required to achieve 1× return, target MOIC, and target IRR - **Key assumptions register**: Itemized list of every assumption with source or [VERIFY] flag ## Quality Checks - Waterfall total distributions equal total exit proceeds in every scenario (zero residual) - As-converted breakpoint is correctly identified — preferred holders convert only when common payout exceeds preference + participation - IRR and MOIC are internally consistent (IRR derived from actual cash flow timing, not approximated) - Dilution math is additive across rounds — total ownership percentages sum to 100% after each modeled round - Participation cap, if present, is correctly applied so that capped holders stop receiving pro-rata above the cap threshold - Sensitivity ranges bracket realistic outcomes — entry and exit multiples aligned to comparable transaction data [VERIFY] - Net return calculations correctly sequence management fees (on committed vs. invested capital) and carry (American vs. European waterfall) per fund terms [VERIFY]
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