preparing-quantitative-strategy-reports
Structures systematic strategy performance reporting with factor exposure, attribution, and risk analytics for investor communication. Use when preparing quant reports, documenting strategy performance, or presenting systematic strategy results.
Best use case
preparing-quantitative-strategy-reports is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Structures systematic strategy performance reporting with factor exposure, attribution, and risk analytics for investor communication. Use when preparing quant reports, documenting strategy performance, or presenting systematic strategy results.
Teams using preparing-quantitative-strategy-reports 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/preparing-quantitative-strategy-reports/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How preparing-quantitative-strategy-reports Compares
| Feature / Agent | preparing-quantitative-strategy-reports | 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?
Structures systematic strategy performance reporting with factor exposure, attribution, and risk analytics for investor communication. Use when preparing quant reports, documenting strategy performance, or presenting systematic strategy results.
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
# Preparing Quantitative Strategy Reports Structures systematic strategy performance reporting with factor exposure, attribution, and risk analytics for investor communication. ## When To Use - Preparing monthly, quarterly, or annual performance reports for a systematic or factor-based strategy - Communicating strategy results to LPs, allocators, or investment committees - Documenting factor exposure changes, attribution breakdowns, or risk regime shifts - Building tear sheets or strategy updates for due diligence or marketing materials - Responding to investor requests for detailed quantitative performance analytics ## Inputs To Gather - **Return series**: Daily or monthly strategy NAV/returns, gross and net of fees, with exact reporting period dates - **Benchmark data**: Returns for the relevant benchmark(s) (e.g., S&P 500, MSCI World, Russell 2000) over the same period - **Factor exposure snapshots**: Current and historical loadings on standard factors (market beta, size, value, momentum, quality, low volatility) from the risk model in use [VERIFY factor model provider—Barra, Axioma, internal] - **Attribution output**: Return attribution by factor, sector, region, or signal grouping from the strategy's attribution engine - **Risk metrics**: Realized volatility, Sharpe ratio, Sortino ratio, max drawdown, VaR/CVaR at stated confidence level, tracking error vs. benchmark - **Portfolio characteristics**: Number of holdings, turnover rate, average holding period, concentration metrics (top 10 weight, HHI) - **Capacity and AUM**: Current strategy AUM, estimated capacity, and any soft/hard close thresholds - **Fee structure**: Management fee, performance fee, hurdle rate, high-water mark terms for net-of-fee calculations - **Compliance constraints**: Any regulatory or internal limits on what can be disclosed (e.g., performance advertising rules under SEC Marketing Rule, GIPS compliance status) [VERIFY applicable regulatory regime] ## Workflow 1. **Confirm reporting scope** - Lock the reporting period (e.g., Q4 2025, trailing 12 months, since inception) - Identify the audience: LP quarterly letter, allocator due diligence deck, internal IC memo - Determine which return series to present (gross vs. net, multiple share classes, composite vs. fund-level) 2. **Compile and reconcile performance data** - Pull strategy returns from the portfolio management or accounting system - Reconcile against the administrator's NAV statements; flag any discrepancies > 1 bp - Calculate standard performance statistics: cumulative return, annualized return, annualized volatility, Sharpe, Sortino, max drawdown, drawdown duration, win/loss ratio (monthly) - Build performance comparison table against primary and secondary benchmarks 3. **Prepare factor exposure analysis** - Extract current factor loadings from the risk model; compare to prior period and inception averages - Present factor exposures in a table or time-series chart showing how tilts have evolved - Highlight any material shifts in exposure (e.g., beta drift, unintended sector concentration) and provide brief commentary on the cause (signal changes, market regime, rebalance timing) 4. **Build return attribution section** - Decompose returns into systematic factor contribution, alpha residual, and trading/implementation costs - If multi-signal strategy, attribute performance to individual signals or signal groups - Provide sector and/or geographic attribution if relevant to the strategy's investable universe - Clearly label the attribution methodology (Brinson-Fachler, factor-based, holdings-based) [VERIFY methodology matches what was disclosed in offering documents] 5. **Document risk analytics** - Report realized risk metrics alongside ex-ante risk model estimates; comment on any divergence - Include tail risk measures: VaR and CVaR at 95% and 99% confidence, worst N-day drawdown - Present correlation to major risk factors and asset classes (equity, rates, credit, commodities, USD) - Note any stress test or scenario analysis results if part of standard reporting (e.g., 2020 COVID shock replay, rates +200 bps) 6. **Add portfolio characteristics and operational details** - Summarize current portfolio composition: number of longs/shorts, gross/net exposure, sector weights - Report turnover, trade count, and implementation shortfall or slippage for the period - State current AUM, capacity utilization, and any changes to the strategy's investment process or model 7. **Draft narrative commentary** - Write a concise market environment overview (2–3 sentences) relevant to the strategy's factor exposures - Explain performance drivers and detractors in plain language tied to the quantitative attribution - Address any underperformance directly; avoid vague language—cite specific factors or market conditions - Note forward-looking positioning changes only if permissible under compliance guidelines [VERIFY whether forward-looking statements require specific disclaimers] 8. **Apply disclosures and formatting** - Include required legal disclaimers: past performance language, fee disclosure, risk warnings - If GIPS-compliant, include the GIPS compliance statement and composite disclosures [VERIFY GIPS verification status and composite definition] - Add footnotes for any non-standard calculations (e.g., annualization method for periods < 1 year, geometric vs. arithmetic linking) - Format tables for readability: consistent decimal places (2 for returns, 2 for ratios), date labels, source citations ## Output The final report should include: - **Performance summary table**: Period returns (MTD, QTD, YTD, 1Y, 3Y, 5Y, SI) gross and net, with benchmark comparisons - **Factor exposure exhibit**: Current loadings vs. historical average, presented as a table or bar chart - **Attribution breakdown**: Factor, sector, and/or signal attribution for the reporting period - **Risk dashboard**: Volatility, Sharpe, drawdown, VaR/CVaR, correlation matrix - **Portfolio snapshot**: Holdings count, exposure levels, turnover, AUM - **Narrative commentary**: 1–2 pages explaining results in the context of market conditions - **Disclosures**: Regulatory disclaimers, fee disclosures, GIPS statement if applicable ## Quality Checks - Returns reconcile to administrator NAV within ±1 bp; any variance is footnoted - All statistics use the same return series (no mixing gross and net within a single comparison) - Factor exposures and attribution sum correctly (factor contributions + residual ≈ total return) - Benchmark selection matches the strategy's stated benchmark in offering documents [VERIFY] - Sharpe and Sortino ratios use the correct risk-free rate for the reporting period [VERIFY current risk-free rate assumption] - Annualized figures for periods under one year are either avoided or clearly labeled as annualized with a footnote - Drawdown calculations use peak-to-trough on a daily (not monthly) basis unless stated otherwise - All forward-looking language has been reviewed by compliance - Disclosures match the current regulatory requirements and the fund's most recent offering documents [VERIFY] - Turnover and slippage figures are consistent with what the execution desk reports