AI Analyst for Pennies: 10 Prompts for Claude That Replace an Entire Stock Research Department
The market for analytical services is undergoing a tectonic shift. A developer under the pseudonym Abhi AI has published a set of 10 prompts for Claude, which, he claims, enable deep fundamental analysis of companies at the level of leading consulting firms. This is not about superficial "buy/sell" recommendations, but about a full research cycle that previously required a team of expensive analysts.
These prompts do not provide ready-made trading signals. Their value lies in the strict structure that forces the AI to consistently go through all stages of analysis: from a general business overview to a detailed assessment of risks and management quality. Each request assigns Claude a specific role and a set of parameters for analysis.
The First Five: From Overview to Valuation
The first prompt places Claude in the role of a senior analyst preparing a beginner-friendly research report on a ticker. It covers the business model, revenue sources, industry trends, competitors, financial results, growth drivers, and bull/base/bear scenarios. Critically, the prompt requires reliance on recent public sources, specifying dates and clearly separating facts from assumptions.
The second prompt dissects the company's latest earnings call: five main takeaways, changes in revenue and margins, management guidance, management tone, analyst concerns, pleasant and unpleasant surprises. A table of key metrics with dynamics and explanations is generated.
The third prompt turns Claude into a skeptical analyst searching for red flags: in revenue, margins, cash flow, debt, dilution, insider actions, and management wording. Each issue is assigned a severity rating, and a final risk score from 1 to 10 is given.
The fourth and fifth prompts focus on competitive advantages and valuation. One assesses the company's "moat"—brand, network effects, switching costs, scale, intellectual property—on a scale and compares it with competitors. The second compares the company with peers using multiples (P/E, forward P/E, EV/revenue, EV/EBITDA) and determines whether it looks cheap, fairly valued, or expensive.
The Second Five: From DCF to a Beginner's Checklist
The sixth prompt helps build realistic assumptions for a discounted cash flow (DCF) model. It generates bearish, base, and bullish scenarios for revenue growth, margins, tax rate, capital expenditures, and discount rate, explaining the logic behind each assumption.
The seventh prompt creates a catalyst calendar for 3, 6, and 12 months: reports, product launches, investor days, regulatory decisions, lawsuits, macro events, management changes, buybacks, and dividends. For each event, it specifies timing, impact, upside and downside risks, confidence level, and source.
The eighth prompt evaluates the management team: the CEO's track record, the CFO's credibility, forecast accuracy, transparency, capital allocation, M&A, insider ownership size, and compensation.
The ninth prompt simulates an investment committee debate: Claude creates a bull analyst and a bear analyst, and at the end, a neutral judge explains which position is better supported.
The tenth prompt turns Claude into a patient teacher who explains the company in simple terms: what it does, how it makes money, what could go right and wrong, and how things stand regarding profitability, growth, debt, and valuation. A beginner's checklist is generated at the end.
My comment as an analyst: Such prompts are a powerful tool for structuring research, but they should not be seen as a replacement for critical thinking. Claude can generate logical chains of reasoning, but it cannot verify data in real-time or account for unpublished insights. The final verification of numbers and responsibility for the decision always rests with the investor. Nevertheless, for a retail trader looking to elevate their analysis to an institutional level, this is a true breakthrough in the accessibility of expertise.