aqr_skill

Overview

This skill builds investment systems in the style of AQR Capital Management, emphasizing academic rigor, transparent methodology, and systematic factor exposure. It provides patterns for factor construction, multi-factor portfolio construction, realistic backtesting, and clear performance attribution. Use it to create robust, implementation-aware quantitative strategies grounded in peer-reviewed research.

How this skill works

The skill inspects data sources and builds investment-grade factors (value, momentum, quality, etc.) by composing multiple metrics, winsorizing and z-scoring, and industry-adjusting where appropriate. It combines factor scores into portfolios using long-short weighting, risk-scaling, and turnover-aware execution, and it backtests strategies with transaction costs, market impact, and borrow costs. Reporting and attribution modules decompose returns into factor contributions and quantify alpha and risk statistics.

When to use it

• Designing factor models based on academic literature
• Building multi-factor portfolios with explicit risk targets
• Backtesting strategies with realistic transaction costs and market impact
• Producing transparent factor performance reports and return attribution
• Evaluating trade-offs between turnover and implementation cost

Best practices

• Start with peer-reviewed research and document economic rationale for each factor
• Construct composite factors (multiple metrics) and winsorize/z-score inputs
• Adjust for industry/sector effects to avoid unintended bets
• Model transaction costs, market impact, and borrow costs in backtests
• Prefer gradual rebalancing, equal-risk weighting, and long-short exposures when appropriate

Example use cases

• Implement a value composite combining book/price, earnings/price, and cash-flow metrics
• Build a 3-factor portfolio (value, momentum, quality) with risk-targeted scaling and turnover budget
• Backtest a momentum strategy using 12-1 returns with industry adjustment and realistic frictions
• Run factor attribution to explain portfolio returns and isolate alpha sources
• Optimize rebalancing schedule to trade toward targets while respecting a turnover cost cap