AI analyst for pennies: 10 prompts for Claude that replace expensive stock analysts
The market for analytical services is undergoing a tectonic shift. While traditional investment banks and hedge funds spend millions maintaining a staff of qualified analysts, any retail investor can now access tools on par with top-tier consulting. This refers to a set of 10 specialized prompts for Claude that enable deep fundamental analysis of companies and cryptocurrency projects.
From General Overview to DCF Model: What These Prompts Can Do
The author of this methodology has created a sequential chain of queries that covers the full research cycle. The first prompt turns Claude into a senior analyst capable of preparing a report on a company that is understandable even to a beginner, including the business model, industry trends, financial results, and bull/base/bear scenarios. The second breaks down the latest earnings call with investors: five key takeaways, revenue dynamics, margins, management forecasts, and surprises.
The third prompt deserves special attention — it assigns Claude the role of a skeptical analyst who seeks out "red flags" in revenue quality, cash flow, debt burden, and insider actions. Each issue is assigned a severity rating, and an overall risk score from 1 to 10 is formed at the end. This is precisely what retail investors often lack — a critical perspective on the company.
Prompts four through nine delve into competitive advantages, multiples (P/E, EV/EBITDA), build realistic assumptions for a DCF model, create a catalyst calendar for 3, 6, and 12 months, assess management quality, and even simulate an investment committee debate with "bull" and "bear" arguments.
The collection concludes with a prompt that turns Claude into a patient teacher, explaining the essence of the company in simple terms and forming a checklist for a novice investor.
It is important to emphasize: none of these prompts provide "buy" or "sell" recommendations. They merely structure the research, providing the investor with an analytical foundation for making their own decision. Final data verification and responsibility for investments always remain with the human.
Expert opinion: This methodology is a powerful tool for democratizing analytics, but it does not negate the need for critical thinking. AI can brilliantly structure data and identify patterns, but it cannot assess intangible factors such as corporate culture or political risks, which often become decisive. Use these prompts as a starting point, but never delegate the final investment decision to AI.