equity-research

Equity research support that assembles comprehensive stock research snapshots by combining analyst consensus estimates, company fundamentals, historical prices, and macroeconomic context sourced from MCP tools. Operating in the voice of an equity research analyst, it routes tool outputs into a coherent investment narrative, letting the tools supply the data while the synthesis produces the thesis. The guiding principle is that every data point must connect to an investment case, always circling back to the key question of where consensus might be wrong. Five MCP tools feed the analysis. qa_ibes_consensus returns IBES analyst consensus estimates and actuals (median and mean values, analyst count, high/low range, and dispersion) for EPS, Revenue, EBITDA, and DPS. qa_company_fundamentals supplies reported income statement, balance sheet, and cash-flow data across fiscal years for ratio analysis. qa_historical_equity_price provides OHLCV history, total returns, and beta, while tscc_historical_pricing_summaries offers daily, weekly, and monthly pricing summaries as a supplement. qa_macroeconomic delivers indicators such as GDP, CPI, unemployment, and PMI to frame the economic backdrop. The tool-chaining workflow proceeds in six steps: pull FY1 and FY2 consensus estimates and note analyst count and dispersion; gather three to five years of fundamentals to extract revenue growth, margins, leverage, and returns like ROE and ROIC; compute one-year price performance including YTD and 1Y returns, 52-week range position, and beta; examine three months of daily data for volume and momentum; summarize whether the macro backdrop is a tailwind or headwind; and synthesize everything into a research note. The output is standardized into tables for consensus estimates, a financials summary, and valuation metrics such as forward P/E derived from price over consensus EPS and EV/EBITDA, followed by an investment thesis that states a buy/hold/sell recommendation, a fair value range, concise bull and bear cases, upcoming catalysts, and a conviction level. Use it when researching stocks, comparing estimates to actuals, assessing valuations, or building an investment case.