- name:
- modeling-fund-economics-sensitivity
- language:
- en
- description:
- Builds fund economic models with sensitivity across deployment pace, exit multiples, and fee/carry structures for LP and GP returns. Use when modeling fund economics, projecting LP net returns, or analyzing fee-adjusted performance.
- author:
- casemark
Modeling Fund Economics Sensitivity
Builds fund economic models with sensitivity analysis across deployment pace, exit multiples, and fee/carry structures to project LP net returns and GP economics.
When To Use
- Modeling projected LP net IRR and net TVPI for a new fund's PPM or marketing materials
- Comparing fee/carry structures during LPA negotiations (e.g., 2/20 vs. 1.5/20 with catch-up variations)
- Stress-testing fund returns under different deployment and exit timing scenarios
- Evaluating GP economics (carried interest, management fee revenue) across fund life
- Presenting sensitivity tables to an LP advisory committee or investment committee
Inputs To Gather
- Fund parameters: target fund size, GP commitment percentage, fund term (investment period + harvest period), extension options
- Fee structure: management fee rate and basis (committed vs. invested capital), fee step-down timing and rate, organizational expense cap, fund expense budget
- Carry structure: carried interest percentage, preferred return (hurdle rate), catch-up split and rate (e.g., 80/20 catch-up to 20%), whole-fund vs. deal-by-deal waterfall, clawback provisions
- Deployment assumptions: number of investments, average check size, deployment pace (e.g., 3–5 year investment period), recycling percentage of returned capital
- Exit assumptions: target gross MOIC range (e.g., 1.5x–3.0x), holding period distribution (3–7 years), exit timing curve (early realizations vs. back-loaded)
- Sensitivity ranges: define low/base/high cases for each key variable
Workflow
-
Build the capital call schedule
- Model LP capital calls based on deployment pace assumptions (front-loaded, even, or J-curve profile)
- Layer in management fees drawn from commitments (or net against invested capital, depending on LPA terms)
- Account for GP co-investment and any fee offsets (e.g., portfolio company monitoring fees credited against management fees)
-
Model the portfolio and exit cash flows
- Project gross investment returns for each scenario using target MOIC and holding period
- Distribute exits across the harvest period — apply a realization curve rather than assuming a single exit date
- If recycling is permitted, model reinvestment of early proceeds within the investment period [VERIFY: confirm recycling cap in LPA, typically 100–125% of commitments]
-
Apply the waterfall distribution
- Calculate return of capital, preferred return accrual, catch-up allocation, and residual carried interest split
- For whole-fund waterfalls: aggregate all proceeds before splitting carry; track cumulative preferred return threshold
- For deal-by-deal waterfalls: compute carry on each realization separately; model escrow/holdback for clawback protection [VERIFY: escrow percentage — commonly 20–30% of carry distributions]
- Compute net distributions to LPs after carry and expenses
-
Calculate return metrics
- LP net IRR: time-weighted return on LP cash flows (calls in, distributions out) net of all fees and carry
- LP net TVPI: total value to paid-in capital (distributions + remaining NAV / total called capital)
- LP DPI: distributions to paid-in (realized returns only)
- GP carry: total carried interest dollars and as a multiple of GP commitment
- GP management fee revenue: cumulative fees over fund life, before and after step-down
-
Run sensitivity analysis
- Build a matrix varying exit multiple (rows) against deployment pace (columns) for LP net IRR and net TVPI
- Run a second matrix varying fee/carry structure against exit multiple for LP net returns
- Test specific scenarios: (a) rapid deployment with lower multiples, (b) slow deployment with higher multiples, (c) early realizations enabling recycling
- Highlight breakeven exit multiple where LP net IRR equals the preferred return hurdle
-
Stress-test edge cases
- Model a loss scenario (0.5x–0.8x gross MOIC) to show LP downside and confirm no carry is distributed
- Test the impact of fund extensions (1–2 years) on IRR drag from continued fee payments
- Verify clawback triggers under deal-by-deal waterfalls with mixed winner/loser outcomes
Output
- Summary table: base case LP net IRR, net TVPI, DPI, and GP carry for the primary scenario
- Sensitivity matrices: 2–3 tables showing LP net IRR and net TVPI across variable combinations
- Cash flow schedule: annual summary of calls, distributions, net cash flow, and cumulative metrics
- Fee analysis: total management fees, fee offsets, organizational expenses, and net fee load as percentage of committed capital
- GP economics summary: carry dollars by scenario, management fee revenue, and total GP compensation
- Assumptions register: all inputs clearly stated with sources, including any [VERIFY] flags for terms pending LPA finalization
Quality Checks
- Confirm that LP net IRR is always lower than gross IRR — if not, the fee/carry layer is misapplied
- Verify that at the preferred return hurdle, zero carry is distributed (waterfall integrity check)
- Ensure capital calls never exceed total commitments (unless recycling is modeled and within permitted limits)
- Cross-check that LP net TVPI = (total distributions + remaining NAV) / total called capital — arithmetic consistency
- Validate that management fee step-down timing matches LPA terms (commonly steps down from committed to invested capital basis after investment period) [VERIFY: confirm step-down trigger and rate]
- Compare modeled J-curve profile against industry benchmarks for the fund's strategy (e.g., buyout funds typically show positive net cash flow by years 5–6)
- Flag any scenario where GP carry exceeds 30% of total fund profits as unusual and warranting review