Create stock research notes combining analyst forecasts, reported financials, price history, and economic conditions. Compare market expectations with business performance, present valuation measures, and summarize an investment case with positive scenarios, risks, and potential catalysts.
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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.
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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.
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.
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.qa_ibes_consensus for FY1 and FY2 estimates (EPS, Revenue, EBITDA, DPS). Note analyst count and dispersion.qa_company_fundamentals for the last 3-5 fiscal years. Extract revenue growth, margins, leverage, returns (ROE, ROIC).qa_historical_equity_price for 1Y history. Compute YTD return, 1Y return, 52-week range position, beta.tscc_historical_pricing_summaries for 3M daily data. Assess volume trends and recent momentum.qa_macroeconomic for GDP, CPI, and policy rate in the company's primary market. Summarize whether macro is tailwind or headwind.| Metric | FY1 | FY2 | # Analysts | Dispersion |
|---|---|---|---|---|
| EPS | ... | ... | ... | ...% |
| Revenue (M) | ... | ... | ... | ...% |
| EBITDA (M) | ... | ... | ... | ...% |
| Metric | FY-2 | FY-1 | FY0 (LTM) | Trend |
|---|---|---|---|---|
| Revenue (M) | ... | ... | ... | ... |
| Gross Margin | ... | ... | ... | ... |
| Operating Margin | ... | ... | ... | ... |
| ROE | ... | ... | ... | ... |
| Net Debt/EBITDA | ... | ... | ... | ... |
| Metric | Current | Context |
|---|---|---|
| Forward P/E | ... | vs sector/history |
| EV/EBITDA | ... | vs sector/history |
| Dividend Yield | ... | ... |
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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Complete an existing financial model template by entering historical data and forecast assumptions, then linking the income statement, balance sheet, and cash flow statement with formulas. Check statement balances, cash consistency, and scenario behavior as each section is completed.
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Prepare a period-end accrual schedule for expenses incurred but not yet fully recorded. Apply company policy, subtract amounts already booked, cite supporting records, and draft journal entries for controller approval, including reversal notes where required.
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Review quarterly updates and financials across portfolio companies to identify practical AI opportunities. Rank them by estimated profit impact, speed, and feasibility, then outline first steps and approaches that other companies can reuse.
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Check spreadsheet formulas for errors, broken references, inconsistent calculations, and unit mismatches. Review a selected range, one sheet, or an entire financial model, then receive findings ranked by severity with suggested fixes.
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Analyze price differences between bond futures and cash bonds, identify the cheapest bond to deliver, and compare implied financing rates with market rates. Present valuation tables and historical context to assess potential basis trades.
中文简介正在准备中。当前显示英语简介。
Assess whether bonds are expensive, cheap, or fairly priced by comparing yields with government rates and credit risk benchmarks. Combine spread breakdowns, historical context, and interest rate scenarios into tables and a recommendation.
中文简介正在准备中。当前显示英语简介。