Claude as Your Personal Analyst: 10 Prompts for Professional Market Analysis
The cryptocurrency and traditional asset markets require deep analysis, which was previously only accessible to large funds and expensive consulting firms. Today, the situation is changing: with properly configured prompts, AI models like Claude can perform the functions of an entire analytics department. I have studied a selection of 10 prompts that structure the company research process from A to Z — from a general business overview to a detailed assessment of risks and management quality.
The First Five: From General Overview to Valuation
The first prompt turns Claude into a senior analyst preparing a clear research report on any ticker. It covers the business model, revenue sources, industry trends, competitors, financial results, and bull/base/bear scenarios. The key requirement is to rely on fresh public data, clearly separating facts from assumptions.
The second prompt breaks down the latest earnings call: five main takeaways, revenue and margin dynamics, management guidance, management tone, and unexpected surprises. A table of key metrics is formed with explanations of why each is important.
The third prompt sets a skeptical tone: Claude looks for "red flags" in revenue quality, margins, cash flow, debt, dilution, insider actions, and management wording. 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 focus on competitive advantages and valuation. One assesses the company's "moat" — brand, network effects, switching costs, scale, intellectual property — and compares it with competitors. The second compares multiples (P/E, EV/Revenue, EV/EBITDA) and determines whether the company is overvalued or undervalued.
The Second Five: From DCF Model to Beginner's Checklist
The sixth prompt helps build realistic assumptions for a discounted cash flow (DCF) model. It creates bear, base, and bull 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, deadlines, impact, upside and downside risks, confidence level, and source are indicated.
The eighth prompt evaluates the management team: CEO track record, CFO credibility, forecast accuracy, transparency, capital allocation, M&A, insider ownership, and compensation. The ninth simulates an investment committee debate, where Claude creates a bull analyst and a bear analyst, and a neutral judge explains whose position is stronger.
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 the state of profitability, growth, debt, and valuation. A beginner's checklist is formed at the end.
My expert opinion: This selection is a powerful tool for structuring research, but it does not eliminate the need for independent data verification. AI can generate hypotheses and identify patterns, but the final investment decision always remains with the human. This is especially critical for cryptocurrencies, where volatility and information asymmetry are higher than in traditional markets.