AI analyst for pennies: 10 prompts for Claude that replace expensive stock experts
The market is changing, and access to high-quality fundamental analysis no longer requires hiring a team of expensive consultants. I have analyzed a set of 10 specialized prompts for Claude that allow for comprehensive research of any public company—from startup to giant—at the level of a leading consulting firm. This is not a recommendation to buy or sell, but a powerful tool for independent analysis.
The author of this methodology, known under the pseudonym Abhi AI, has structured the full cycle of company analysis. Each prompt assigns Claude a clear role and parameters, turning it into a virtual analyst. Let's break down what exactly each of these queries does.
The First Five: From General Overview to Valuation
Prompt #1 places Claude in the role of a senior analyst preparing a research report on a ticker that is understandable for a beginner. It covers the business model, revenue sources, industry trends, competitors, financial results, valuation, growth drivers, and risks, including bull/base/bear scenarios. The key requirement is to rely on fresh public data, clearly separating facts from assumptions.
Prompt #2 focuses on the company's latest earnings call: the top five takeaways, revenue and margin trends, management guidance, management tone, analyst concerns, as well as positive and negative surprises. It also generates a table of key metrics with current and previous figures and an explanation of their significance.
Prompt #3 turns Claude into a skeptical analyst looking for red flags in revenue quality, margins, cash flow, debt, dilution, insider actions, and management language. Each issue is assigned a severity rating, and a final overall risk score from 1 to 10 is given.
Prompts #4 and #5 focus on assessing competitive advantages and valuation. The fourth analyzes the company's "moat": brand, network effects, switching costs, scale, intellectual property—and compares it with competitors. The fifth compares the company with peers using multiples (P/E, forward P/E, EV/Revenue, EV/EBITDA) and concludes whether it looks cheap, fairly valued, or expensive.
The Second Five: From DCF Model to a Beginner's Checklist
Prompt #6 helps build realistic assumptions for a discounted cash flow (DCF) model. It generates bear, base, and bull scenarios for revenue growth, margins, tax rate, capital expenditures, and discount rate, explaining the logic behind each assumption.
Prompt #7 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.
Prompt #8 evaluates the management team: the CEO's track record, the CFO's credibility, forecast accuracy, transparency, capital allocation, M&A, insider ownership, and compensation.
Prompt #9 simulates an investment committee debate, where Claude creates a bull analyst and a bear analyst, and at the end, a neutral judge explains which position is more strongly supported.
Prompt #10 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 its status regarding profitability, growth, debt, and valuation. A beginner's checklist is formed at the end.
My expert opinion: The value of this collection is not that Claude will replace a human, but that it structures the research process itself. It's like getting a ready-made Due Diligence template from top-tier consulting. However, remember: the final verification of data and responsibility for the investment decision always remain with you. AI is a powerful assistant, but not a substitute for critical thinking.