AI Analyst for Pennies: 10 Prompts for Claude That Are Changing the Game in the Stock Market
The market for analytical services is undergoing a tectonic shift. While traditional investment houses charge exorbitant fees for research, a new player is entering the arena — AI. And this isn't about trivial news aggregators, but a full-fledged tool capable of replacing a staff analyst. This is about Claude from Anthropic.
Recently, a collection of 10 prompts appeared in the community, turning the language model into a multi-functional stock market expert. Importantly: none of them provide "buy" or "sell" recommendations. Their task is to structure research and provide the investor with an objective picture, not ready-made trading signals.
The First Five: From Business Model to Valuation
The first prompt places Claude in the role of a senior analyst. It generates a comprehensive report on a ticker: business model, finances, competitors, growth drivers, and bull/base/bear scenarios. A critical requirement is reliance on fresh public data and a clear separation of facts and assumptions.
The second prompt breaks down the latest earnings call. The model highlights five key takeaways, analyzes management's tone, identifies pleasant and unpleasant surprises, and creates a table of key metrics with explanations. The third turns Claude into a skeptic who looks for red flags: margin decline, debt issues, insider sales. Each issue is assigned a severity rating, and an overall risk score from 1 to 10 is given at the end.
The fourth and fifth prompts are about competition and valuation. One assesses the company's "moat" (brand, network effects, intellectual property) and compares it with competitors. The second compares multiples (P/E, EV/EBITDA) and answers the main question: is the company overvalued or undervalued?
The Second Five: From DCF to a Beginner's Checklist
The sixth prompt helps build assumptions for a discounted cash flow (DCF) model. It generates bearish, base, and bullish scenarios for revenue, margin, and discount rate. The seventh creates a catalyst calendar for 3, 6, and 12 months: reports, product launches, regulatory decisions, dividends. For each event, the impact, risks, and confidence level are indicated.
The eighth prompt evaluates the management team: CFO honesty, forecast accuracy, transparency, insider transactions. The ninth simulates an investment committee meeting, where Claude creates a "bull" and a "bear," and a neutral judge summarizes which position is stronger.
The tenth prompt is for beginners. It turns Claude into a patient teacher who explains the company in simple terms: what it does, how it makes money, what the risks are. At the end, a checklist for independent study is formed.
My expert opinion: This collection is not just a set of tricks, but a prototype of a new industry. AI will not replace an experienced portfolio manager, but it democratizes access to high-quality fundamental analysis. An investor who cannot afford Goldman Sachs can now get a comparable level of primary data processing. Final verification and decision-making remain with the human, but the "grunt work" of the analyst is becoming a thing of the past. The data market is becoming a commodity, and the key competency is the ability to ask the right questions.