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Automation
Command

/research-equity

Generate a comprehensive equity research snapshot with consensus estimates, fundamentals, and price performance

From plugin
financial-services
34k56 skills10 agents56 commands2 MCP
Install
> /plugin marketplace add anthropics/financial-services

How it fires

How this command gets triggered: by you, by Claude, or both.

  • Fires itselfClaude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/research-equity

Context preview

What this command does when you run it.

Generate a comprehensive equity research snapshot with consensus estimates, fundamentals, and price performance

Command definition

research-equity.md
description: Generate a comprehensive equity research snapshot with consensus estimates, fundamentals, and price performance
argument-hint: "<ticker e.g. AAPL> [period e.g. FY2024-FY2026]"

Research Equity

> This command uses LSEG quantitative analytics, historical pricing, and macroeconomic data tools. See [CONNECTORS.md](../CONNECTORS.md) for available tools.

Generate a comprehensive equity research snapshot combining analyst consensus estimates, historical financials, price performance, and macroeconomic context.

See the **equity-research** skill for domain knowledge on fundamental analysis and estimate interpretation.

Workflow

1. Gather Input

Ask the user for:

  • Ticker symbol (required) — IBES ticker format (e.g., AAPL, MSFT, VOD)
  • Forward period of interest (optional, default: next 2 fiscal years)
  • Any specific focus areas (e.g., earnings, revenue, dividends)

2. Gather Consensus Estimates

Call `qa_ibes_consensus` with the ticker for FY1 and FY2 estimates.

  • Measures: EPS, Revenue, EBITDA, DPS
  • Period type: "A" (annual)

Extract: median/mean estimate, analyst count, high/low range, dispersion.

3. Pull Historical Fundamentals

Call `qa_company_fundamentals` for the last 3-5 fiscal years.

Extract: revenue growth, margin trends, leverage, earnings trajectory.

4. Assess Price Performance

Call `qa_historical_equity_price` for 1Y history.

Compute: YTD return, 1Y return, 52-week range, beta.

5. Recent Price Action Detail

Call `tscc_historical_pricing_summaries` with `interval: "P1D"`, `tenor: "3M"`.

Extract: daily OHLCV, volume trends, recent momentum.

6. Macro Context

Call `qa_macroeconomic` for GDP, CPI, and policy rate in the company's primary market.

Summarize: economic environment as tailwind or headwind for the sector.

7. Synthesize the Report

Present: consensus estimates table, historical financials summary, valuation metrics (forward P/E = price / consensus EPS), price performance, macro backdrop, and investment thesis summary.

Output Format

Present as a structured research note. Lead with the investment thesis summary (1-2 sentences), then detail supporting sections with tables.

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Ships withfinancial-services

Reference agents, skills, and data connectors for the financial-services workflows we see most — investment banking, equity research, private equity, and wealth management.

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