AI Agent Skills

Screen equities with systematic value, momentum, quality, volatility, size, and growth factor frameworks.

Fast quantitative research and backtesting workflows for financial agents.

Create a structured post-earnings equity research update with key metrics, estimate changes, charts, and thesis review.

Create a global market conditions report spanning equities, rates, FX, commodities, risk appetite, and sector rotation.

Rank recent market-moving news and explain likely effects on equities, commodities, monetary policy, and earnings.

Build an upcoming US earnings calendar with dates, timing, consensus estimates, and market-impact context.

Create a multi-perspective technology-company earnings memo with evidence standards, valuation lenses, and anti-bias checks.

Audit concentration, factor exposure, correlation, liquidity, and stress-test risks in an existing portfolio.

Review portfolio-company financial packages, flag variance to plan, and prepare monitored KPI summaries.

Prepare a pre-earnings briefing with consensus estimates, beat-miss history, and current market context.

Research a US equity across fundamentals, valuation, technical context, peers, and current market data.

Analyze a ticker with AlphaGBMs five-pillar framework: fundamentals, technicals, sentiment, flows, and valuation.

Evaluate systematic strategy ideas through signal testing, statistical validation, decay, execution costs, and model-risk review.

Measure portfolio returns, risk, drawdowns, benchmarks, rolling metrics, and strategy performance from approved data.

Assess business quality, economic moats, management, competitive positioning, and durable value creation.

Research a companys valuation, growth, profitability, balance sheet, competitive moat, and management quality.