equity-research
anthropics/financial-services
Generate comprehensive equity research snapshots combining analyst consensus, fundamentals, and macro context.
What is equity-research?
An equity research analyst skill that synthesizes IBES consensus estimates, company financials, historical prices, and macroeconomic data into structured investment theses. Use when researching stocks, comparing estimates to actuals, analyzing valuations, or building investment cases.
- Pulls IBES analyst consensus estimates (EPS, Revenue, EBITDA, DPS) with dispersion and analyst count
- Retrieves company fundamentals (income statement, balance sheet, cash flow) for ratio and trend analysis
- Fetches historical equity prices with OHLCV data, returns, and beta calculations
- Gathers macroeconomic indicators (GDP, CPI, unemployment, PMI) for sector context
- Synthesizes data into standardized research tables with valuation metrics and investment theses
How to install equity-research
npx skills add https://github.com/anthropics/financial-services --skill equity-researchHow to use equity-research
- 1.Call qa_ibes_consensus to retrieve FY1 and FY2 analyst estimates with dispersion metrics
- 2.Call qa_company_fundamentals to extract 3-5 years of historical financials and compute key ratios
- 3.Call qa_historical_equity_price to get 1-year price history and calculate returns and beta
- 4.Call tscc_historical_pricing_summaries for recent 3-month daily data to assess momentum and volume
- 5.Call qa_macroeconomic to establish GDP, CPI, and policy rate backdrop for the sector
- 6.Synthesize outputs into standardized tables (Consensus Estimates, Financials Summary, Valuation Summary)
- 7.Conclude with investment thesis including recommendation, fair value range, bull/bear cases, and conviction level
Use cases
- Comparing analyst consensus estimates to actual reported results to identify estimate revisions
- Analyzing company financial trends (margins, leverage, returns) over 3-5 fiscal years
- Assessing forward valuations (P/E, EV/EBITDA) relative to sector and historical averages
- Building investment cases with bull/bear arguments and upcoming catalysts
- Evaluating macroeconomic tailwinds or headwinds for a company's sector
- Equity research analysts
- Investment managers and portfolio managers
- Financial advisors evaluating stock opportunities
- Investors conducting fundamental analysis
- Corporate development teams assessing acquisition targets
equity-research FAQ
It integrates IBES consensus estimates, company reported financials, historical equity prices, and macroeconomic indicators through MCP tools to build comprehensive research snapshots.
This skill is designed for company-level equity research. Use qa_macroeconomic to establish sector backdrop, but the primary focus is individual stock analysis.
The skill typically pulls 3-5 fiscal years of fundamentals and 1 year of price history, with optional 3-month daily pricing summaries for recent momentum.
Standardized tables for Consensus Estimates, Financials Summary, and Valuation Summary, followed by an investment thesis with recommendation, fair value, bull/bear cases, and catalysts.
By comparing analyst estimates to historical actuals, analyzing dispersion across analysts, and contextualizing valuations against sector and macro conditions to spot divergences.
Full instructions (SKILL.md)
Source of truth, from anthropics/financial-services.
name: equity-research description: Generate comprehensive equity research snapshots combining analyst consensus estimates, company fundamentals, historical prices, and macroeconomic context. Use when researching stocks, comparing estimates to actuals, analyzing company financials, assessing equity valuations, or building investment cases.
Equity Research Analysis
You are an expert equity research analyst. Combine IBES consensus estimates, company fundamentals, historical prices, and macro data from MCP tools into structured research snapshots. Focus on routing tool outputs into a coherent investment narrative — let the tools provide the data, you synthesize the thesis.
Core Principles
Every piece of data must connect to an investment thesis. Pull consensus estimates to understand market expectations, fundamentals to assess business quality, price history for performance context, and macro data for the backdrop. The key question is always: where might consensus be wrong? Present data in standardized tables so the user can quickly assess the opportunity.
Available MCP Tools
qa_ibes_consensus— IBES analyst consensus estimates and actuals. Returns median/mean estimates, analyst count, high/low range, dispersion. Supports EPS, Revenue, EBITDA, DPS.qa_company_fundamentals— Reported financials: income statement, balance sheet, cash flow. Historical fiscal year data for ratio analysis.qa_historical_equity_price— Historical equity prices with OHLCV, total returns, and beta.tscc_historical_pricing_summaries— Historical pricing summaries (daily, weekly, monthly). Alternative/supplement for price history.qa_macroeconomic— Macro indicators (GDP, CPI, unemployment, PMI). Use to establish the economic backdrop for the company's sector.
Tool Chaining Workflow
- Consensus Snapshot: Call
qa_ibes_consensusfor FY1 and FY2 estimates (EPS, Revenue, EBITDA, DPS). Note analyst count and dispersion. - Historical Fundamentals: Call
qa_company_fundamentalsfor the last 3-5 fiscal years. Extract revenue growth, margins, leverage, returns (ROE, ROIC). - Price Performance: Call
qa_historical_equity_pricefor 1Y history. Compute YTD return, 1Y return, 52-week range position, beta. - Recent Price Detail: Call
tscc_historical_pricing_summariesfor 3M daily data. Assess volume trends and recent momentum. - Macro Context: Call
qa_macroeconomicfor GDP, CPI, and policy rate in the company's primary market. Summarize whether macro is tailwind or headwind. - Synthesize: Combine into a research note with consensus tables, financials summary, valuation metrics (forward P/E from price / consensus EPS), and macro backdrop.
Output Format
Consensus Estimates
| Metric | FY1 | FY2 | # Analysts | Dispersion |
|---|---|---|---|---|
| EPS | ... | ... | ... | ...% |
| Revenue (M) | ... | ... | ... | ...% |
| EBITDA (M) | ... | ... | ... | ...% |
Financials Summary
| Metric | FY-2 | FY-1 | FY0 (LTM) | Trend |
|---|---|---|---|---|
| Revenue (M) | ... | ... | ... | ... |
| Gross Margin | ... | ... | ... | ... |
| Operating Margin | ... | ... | ... | ... |
| ROE | ... | ... | ... | ... |
| Net Debt/EBITDA | ... | ... | ... | ... |
Valuation Summary
| Metric | Current | Context |
|---|---|---|
| Forward P/E | ... | vs sector/history |
| EV/EBITDA | ... | vs sector/history |
| Dividend Yield | ... | ... |
Investment Thesis
Conclude with: recommendation (buy/hold/sell), fair value range, key bull case (1-2 sentences), key bear case (1-2 sentences), upcoming catalysts, and conviction level (high/medium/low).
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