不會寫程式，用 Claude Code 做股票研究
案例摘要
一名非工程師把研究資料全放本地純文字檔（Obsidian 管理），SEC 文件從 EDGAR 存好，頂層 CLAUDE.md 寫明檔案結構與規則；Claude Code 只讀這些檔、用原文引句＋編號萃取數字、跑第二遍驗證。它從 Accenture 近五年財報挖出單看難發現的模式：bookings 指標從 30 億到 59 億，然後從後續財報消失。方法成立的關鍵是第二遍糾錯，但第一遍從不清爽。
實際結果
挖出財報中消失的指標；雙遍驗證是關鍵。
台灣／大陸場景對照
🇹🇼 台灣
台灣可用於公開資訊觀測站財報研究：搭配財報數據＋本地檔案＋雙遍驗證；數字一律要求原文出處。
🇨🇳 大陸
大陸可用巨潮資訊公告＋本地知識庫：同樣雙遍驗證；注意研報合規，僅個人研究。
英文原文
Do equity research with Claude Code without coding
A non-engineer keeps all research in one local folder of plain-text files, managed through Obsidian, with SEC filings from EDGAR saved there and a top-level CLAUDE.md that tells Claude Code how the files are organized and what rules to follow. Claude Code reads only those files, extracts figures with exact quoted lines and accession numbers, reruns a second verification pass, and writes small Python scripts or Excel files for any math while the person reviews and corrects mistakes.
It surfaced a pattern across Accenture's last five earnings releases that the poster says was hard to see one-by-one: a bookings metric went from $3B to $5.9B, then disappeared from later releases. They say the method works because the second pass catches errors, but the first pass is never clean and the model will estimate or summarize from memory unless constrained.
來源
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