modeling-credit-fund-portfolios

name	modeling-credit-fund-portfolios
description	Builds credit fund portfolio models with yield attribution, default/recovery scenarios, and portfolio-level return analysis. Use when modeling credit funds, projecting portfolio returns, or analyzing yield components.
tags	["modeling","credit-and-institutional-lending","portfolio","credit"]
metadata	{"author":"casemark","practice_areas":["Credit Markets","Leveraged Lending","Direct Lending"],"document_types":["Financial Model"],"skill_modes":["Modeling","Forecasting"]}

Modeling Credit Fund Portfolios

Builds credit fund portfolio models with yield attribution, default/recovery scenarios, and portfolio-level return analysis for direct lending, broadly syndicated loan, and private credit strategies.

When To Use

• Projecting net returns for a credit fund across base, stress, and downside scenarios
• Decomposing portfolio yield into coupon, OID, fee income, and PIK components
• Modeling default waterfalls with recovery timing and severity assumptions
• Evaluating the impact of leverage (subscription lines, asset-level facilities) on equity returns
• Preparing LP reporting models or IC memoranda that require portfolio-level return attribution

Inputs To Gather

• Portfolio composition: loan tape or representative pool (borrower, commitment size, drawn %, spread, floor, OID, maturity, asset type)
• Fund terms: management fee rate, incentive fee / carried interest structure, hurdle rate, preferred return, catch-up, GP commitment %
• Leverage assumptions: advance rate, cost of borrowing on credit facility, commitment fee on undrawn, covenant headroom
• Credit assumptions: annual default rate, loss given default (LGD) or recovery rate, recovery lag (months), prepayment rate (CPR or voluntary)
• Deployment schedule: ramp period, reinvestment period end, harvest / wind-down timeline
• Fee income: upfront origination fees, amendment/waiver fees, prepayment penalties, LIBOR/SOFR floor benefit [VERIFY: confirm current reference rate and transition status]

Workflow

1. Build the loan tape model

   • Populate each position with par amount, spread (S + margin), SOFR floor, OID amortization schedule, maturity, and PIK toggle if applicable
   • Calculate weighted-average spread, weighted-average life (WAL), and cash vs. PIK yield split
   • Flag any floating-rate mismatches between assets and liabilities

2. Construct yield attribution

   • Separate gross portfolio yield into: (a) cash coupon, (b) OID accretion, (c) origination/amendment fee amortization, (d) PIK accrual, (e) SOFR floor benefit
   • Sum to gross asset yield; subtract cost of fund-level leverage to arrive at net asset yield
   • Layer in management fees and fund expenses to compute net investment income (NII)

3. Model default and recovery scenarios

   • Define scenarios — e.g., base (1–2% annual default, 60–70% recovery), stress (4–5% default, 40–50% recovery), severe (8%+ default, 25–35% recovery) [VERIFY: adjust ranges to match fund vintage and asset class norms]
   • Apply defaults as random or front-loaded timing vectors across the portfolio life
   • Model recovery cash flows with a lag (typically 12–24 months post-default) and haircut to par
   • Calculate net credit losses per period and cumulative loss rate

4. Layer leverage and compute equity returns

   • Model subscription-line draws during ramp, converting to term asset-level leverage post-ramp
   • Calculate interest expense on drawn leverage, undrawn commitment fees, and facility amortization
   • Compute levered vs. unlevered returns: gross ROA → levered gross return → net-of-fee return to LPs
   • Derive gross and net IRR, MOIC, and DPI across the fund life for each scenario

5. Build the waterfall and carried interest schedule

   • Map cash flows through the distribution waterfall: return of capital → preferred return → GP catch-up → carried interest split
   • Compute GP economics (management fees + carry) and LP net returns separately
   • Sensitivity-test the waterfall on deployment pace, default timing, and prepayment speed

6. Run sensitivity and scenario tables

   • Two-way tables: default rate vs. recovery rate → net IRR to LPs
   • Two-way tables: spread compression vs. prepayment speed → gross yield
   • Toggle leverage on/off to isolate leverage contribution to returns
   • Stress-test SOFR path scenarios (parallel shift, inversion) on floating-rate NIM

Output

• Portfolio summary: position count, total commitments, drawn balance, WAL, WA spread, WA OID, cash/PIK mix
• Yield attribution table: line-item decomposition from gross asset yield to LP net return
• Scenario matrix: base / stress / severe cases showing gross IRR, net IRR, MOIC, DPI, cumulative loss rate
• Leverage impact summary: unlevered vs. levered returns with advance rate and borrowing cost shown
• Waterfall schedule: period-by-period cash flows to LP and GP, with carry crystallization timing
• Sensitivity tables: two-way grids on key drivers (default/recovery, spread/prepay, SOFR path)

Quality Checks

• Confirm WAL and WA spread match the loan tape; reconcile any differences from PIK or OID treatment
• Verify that gross-to-net bridge is fully traceable (no unexplained leakage between gross yield and LP net return)
• Ensure default timing vectors sum to the stated cumulative default rate over fund life
• Check that recovery cash flows are lagged correctly and do not exceed par
• Validate waterfall math: LP preferred return accrues correctly; catch-up and carry split match fund LPA terms [VERIFY: confirm specific waterfall mechanics against the fund's LPA]
• Cross-check levered return math — leverage should amplify both upside and downside symmetrically relative to the advance rate and spread-over-borrow differential
• Confirm SOFR floor benefit is calculated only when reference rate falls below the contractual floor
• Test edge cases: 100% prepayment in year 1, zero defaults, and full portfolio wipeout to ensure model stability