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fund-analysis

Evaluate public funds and ETFs using performance, risk-adjusted, and attribution metrics.

Updated May 5, 2026
Search Tags:#risk-adjusted returns#fund screening#style box analysis#rolling regression#ETF selection#FOF portfolio
One-click install
npx skills add https://github.com/wudye/traderAssistHK --skill fund-analysis-wudye
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fund-analysis
Source: https://github.com/wudye/traderAssistHK/tree/main/backend/src/skills/fund-analysis
Command: npx skills add https://github.com/wudye/traderAssistHK --skill fund-analysis-wudye

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It solves the problem of choosing funds based on consistent, risk-adjusted outperformance rather than simply picking past winners by combining performance metrics, style-box validation, and style-drift detection.

Core Features & Use Cases

  • Multidimensional performance scoring: evaluates annualized return, alpha, information ratio, Sharpe/Sortino/Treynor, maximum drawdown, volatility, and Calmar ratio against target thresholds.
  • Sharpe style-box analysis: attributes portfolio style using a regression-to-style-index framework (e.g., A-share big/mid/small value/growth proxies) and assesses clarity via R².
  • Style drift detection: runs rolling-window regression to detect significant beta changes and diagnose drift patterns (gradual, abrupt, cycle-driven).
  • FOF composition framework: supports fund-of-funds asset allocation, diversified fund selection by sleeve, and rule-based quarterly rebalancing with monitoring alerts.

Quick Start

Ask for a fund-analysis report for a set of A-share funds by comparing them on 3–5 year performance, validating declared vs realized style (including drift), and recommending FOF weights.

Frequently Asked Questions about fund-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I evaluate fund performance using risk-adjusted returns instead of just past winners?▼

Evaluating risk-adjusted returns requires computing Sharpe, Sortino, Treynor, and Calmar ratios alongside alpha and maximum drawdown. This approach scores funds against target thresholds, identifying consistent outperformance rather than simply ranking by historical returns.

What is Sharpe style-box analysis and how does it attribute fund behavior?▼

Sharpe style-box analysis attributes portfolio style by running regression against defined style indices, such as A-share big or small value proxies. It assesses style clarity using R-squared confidence to validate a fund's realized investment behavior.

How do I detect style drift in a mutual fund through rolling regression?▼

Detecting style drift involves running rolling-window regression to identify significant beta changes over time. This diagnoses drift patterns—whether gradual, abrupt, or cycle-driven—by comparing current beta behavior against historical style baselines.

Can I use this approach for FOF portfolio construction and quarterly rebalancing?▼

FOF portfolio construction is supported through a framework for fund-of-funds asset allocation and diversified sleeve selection. It enables rule-based quarterly rebalancing with automated monitoring alerts to maintain target allocations.

Does ETF selection require multidimensional performance scoring before inclusion?▼

ETF selection requires multidimensional performance scoring that evaluates annualized return, information ratio, volatility, and cost criteria. Enforcing threshold-based ranking across return and risk metrics ensures only resilient alpha sources are selected.

Why does my fund screening fail to identify consistent outperformers?▼

Fund screening fails when relying solely on past returns without style-box validation or drift detection. Combining performance metrics with rolling style regression and risk-adjusted thresholds identifies funds with durable, resilient alpha.

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