analyzing-credit-fund-performance
Evaluates credit fund returns with yield attribution, mark-to-market dynamics, and performance comparison across credit strategies. Use when analyzing credit fund performance, decomposing returns, or benchmarking credit strategies.
Best use case
analyzing-credit-fund-performance is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Evaluates credit fund returns with yield attribution, mark-to-market dynamics, and performance comparison across credit strategies. Use when analyzing credit fund performance, decomposing returns, or benchmarking credit strategies.
Teams using analyzing-credit-fund-performance 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/analyzing-credit-fund-performance/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How analyzing-credit-fund-performance Compares
| Feature / Agent | analyzing-credit-fund-performance | 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?
Evaluates credit fund returns with yield attribution, mark-to-market dynamics, and performance comparison across credit strategies. Use when analyzing credit fund performance, decomposing returns, or benchmarking credit strategies.
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
# Analyzing Credit Fund Performance ## When To Use - Decomposing credit fund total returns into yield income, spread movement, and credit migration components - Benchmarking a credit strategy (direct lending, broadly syndicated loans, CLO equity, distressed) against peers or indices - Evaluating manager performance across vintage years or market cycles - Preparing IC memos, quarterly LP letters, or due diligence reports that require return attribution - Assessing whether reported returns reflect genuine alpha vs. leverage, illiquidity premium, or mark-to-market lag ## Inputs To Gather - **Fund-level data**: NAV history, IRR (gross/net), MOIC, DPI, RVPI, cash yield, total return time series - **Portfolio composition**: sector/industry weights, rating distribution (BB/B/CCC split), fixed vs. floating mix, first lien vs. second lien vs. mezzanine breakdown - **Benchmark indices**: LSTA Leveraged Loan Index, ICE BofA HY indices, Cliffwater Direct Lending Index, or relevant CLO tranche benchmarks - **Fee structure**: management fee, incentive fee / carried interest, hurdle rate, catch-up, fee offsets - **Leverage profile**: fund-level leverage (subscription lines, NAV facilities), asset-level leverage (CLO issuance, repo) - **Mark-to-market policy**: frequency of third-party valuations, use of dealer marks vs. model marks, lag conventions - **Vintage and deployment timing**: capital call schedule, deployment pace, reinvestment period status ## Workflow 1. **Normalize return data** - Convert reported returns to a common basis (time-weighted vs. money-weighted) — use IRR for drawdown funds, TWR for open-ended vehicles - Strip out subscription-line effects by computing IRR from actual LP cash flows vs. fund-level cash flows - Confirm currency exposure and whether returns are hedged or unhedged 2. **Decompose total return into components** - **Carry/yield income**: coupon income, OID accretion, fee income (origination, amendment, prepayment fees) - **Spread/mark-to-market**: unrealized gains/losses from spread tightening or widening; isolate rate moves from credit spread moves for floating-rate portfolios - **Credit losses**: realized defaults, recoveries, and write-downs; compute cumulative default rate and loss-given-default - **Leverage contribution**: estimate the return uplift attributable to fund-level or structural leverage 3. **Benchmark and compare** - Match the fund's strategy to the appropriate benchmark (e.g., direct lending vs. Cliffwater DLI, BSL vs. LSTA LLI) - Compare on gross and net basis; adjust for fee drag and leverage differences - Rank within peer universe by vintage year if available - Evaluate risk-adjusted metrics: Sharpe ratio (for liquid strategies), loss ratio, Sortino ratio, max drawdown 4. **Assess valuation and reporting quality** - Check NAV volatility relative to underlying market moves — suspiciously low vol may signal stale marks - Review frequency and methodology of independent valuations [VERIFY — valuation policies differ by fund structure and jurisdiction] - Flag any positions held at cost or above par for extended periods without supporting market data - Compare reported EBITDA adjustments on underlying credits to industry norms 5. **Identify risks and red flags** - PIK concentration: high PIK income can inflate reported returns while deferring cash realization - Concentration risk: single-name, sector, or sponsor concentration exceeding stated limits - Credit migration: drift toward lower-rated credits or covenant-lite structures vs. fund mandate - Denominator effects: unfunded commitments reducing reported leverage ratios without reducing actual risk 6. **Synthesize findings** - Summarize alpha sources vs. beta/structural exposures - Provide forward-looking assessment: how the portfolio is positioned for rate changes, spread widening, or default cycle acceleration - State confidence level on marks and data completeness ## Output - **Return Attribution Table**: period-by-period breakdown of yield income, spread P&L, realized credit losses, leverage effect, and fees - **Benchmark Comparison**: side-by-side metrics (IRR, MOIC, yield, loss rate) vs. index and peer quartiles - **Portfolio Risk Dashboard**: rating migration matrix, sector concentration, top exposures, PIK percentage, covenant quality summary - **Narrative Assessment**: 1–2 page summary of key performance drivers, valuation concerns, and forward outlook - Flag items requiring [VERIFY] for data the analyst must confirm (third-party marks, borrower financials, fee calculations) ## Quality Checks - Gross-to-net reconciliation: confirm that gross-to-net spread is explainable by stated fee terms and leverage costs - Cash yield vs. total return gap: if total return materially exceeds cash yield, verify the source of unrealized gains - Benchmark alignment: ensure the selected benchmark matches the fund's risk profile (do not compare a first-lien direct lending fund to a high-yield bond index) - Time period consistency: all comparisons use the same measurement periods; do not mix inception-to-date with trailing periods - Double-count check: PIK income and OID accretion should not appear in both yield and mark-to-market components - [VERIFY] Regulatory and reporting standards applicable to the fund's domicile (e.g., ILPA reporting guidelines, AIFMD Annex IV requirements, SEC Form PF)
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