Today, I watched a demo video of #Claude AI by @AnthropicAI, and I was amazed. As a professional investor, US stock companies + #Web3 projects have to be watched hundreds every year, especially the earnings season is simply a battlefield! For example, this kind of practical case in the video is still relatively common: as soon as the office sat down, at 2 p.m., the PM (investment director) rushed in: "Sarah, the company we are focusing on, Velocity Athletic, has just released its earnings report, and its revenue has plummeted by 12%, but its stock price has actually risen by 17% to $71. Can you figure it out to me, is this wave of rise a positive strategy stimulus or a false rebound? Before today's close, you have to make a decision, whether to sell and take profit, or continue to hold. ” In fact, this logic is like the non-farm payroll data + 56 employment data revised downward for two months this Friday (260,000 jobs were cut in May + June, which is equivalent to the sudden unemployment of the entire population of Miami). In this case, you have to make a judgment and decision as soon as possible, and immediately feed back to the US stocks that have not yet opened, and crypto assets to hedge, which requires immediate response and data support, which will effectively avoid this wave of killing over the weekend. Let's take a look at the path of a normal financial analyst (expected 4-5 hours): 1️⃣Go to S&P Global to pull financial reports and meeting minutes 2️⃣ Open FactSet / Morningstar to see historical data and valuations 3️⃣ Cut Edgar to check the SEC announcement 4️⃣ Mining the history of the intranet memo and research report 5️⃣ Then make tables, draw pictures, and write memos This operation takes at least 4~5 hours, and it takes several systems to be manually cut, and the information is inconsistent and prone to errors. 💡 At this time, #Claude appeared, it really felt like I had an extra super analyst assistant: Directly give #Claude instructions: "Help me comprehensively analyze Velocity Athletic's financial report performance, whether the stock price change is reasonable, and issue an investment memo." ” 🔍 1️⃣Multi-platform synchronous pulling data + semantic understanding Claude doesn't simply crawl data, it understands the context I need: · Extract key information from S&P Global to extract key information, such as the CFO's mention in a Q&A that "margins fell by 400 basis points due to tariffs"; · Pull out historical data and opponent comparisons from Morningstar; I found the Velocity analysis framework that I had written about in the past from our company's internal documentation (box); · Scrape 8 quarters of financial data from Delupa to create trend charts directly; · All content is marked with the source, and you can click in at any time for secondary confirmation, which greatly improves compliance and trust. 📊 2️⃣ Generate visual charts + core models Q#Claude: "Help me make an annotated price chart, peer valuation comparison table, and DCF model." ” It implements step by step: · Stock price charts marking events (showing CFO reductions, emergency board meetings, financial report release times, etc.); · A clear comps table: Velocity's EV/EBITDA is 21 times, the industry average is only 16 times, and the valuation is high; · A complete DCF model: clear assumptions, freely switching scenarios, even WACC calculations are standard. · The reasonable stock price calculated by the model: $54, far lower than the current $71, indicating that the current rise is optimistic and the bubble component is large. 📝 3️⃣ Automatically generate institutional-grade investment memos Finally, I said, "Use our fund's internal template to make a memo for PM's reference." ” Claude directly calls the memo template on the intranet and automatically populates with the following: Recommended conclusion: It is recommended to sell at a high point to make a profit, and wait for the price to pull back before opening a position; Logical support: quantitative support from financial fundamentals, market reactions, industry comparisons, valuation deviations and other dimensions; Potential risks: For example, if tariffs are eased in the future and CFOs reduce their holdings for other reasons, it may lead to further fluctuations in stock prices; Clear citations: All data with links to the original source for PM or legal review. Watching the entire video demo, I think #Claude is completely the "#AI nuclear weapon" of financial report analysis, and there are still relatively few API data interfaces supported by encrypted data, which can become the killer feature of #Web3 investment research if it is improved in the later stage. If we used to do project analysis to "fly with ten fingers + nine screens to check data + use five heads together", now with #Claude, it is like having a gold medal analyst who does not go offline 24 hours a day, and does not shout overtime, and efficiency takes off 📈!