Stock Fundamental Analysis & AI-Powered Reports with Mistral and AlphaVantage

# Fundamental Analysis, Stock Analysis, and AI Integration in the Fundamental Analysis Tool --- ## Overview of the Tool The **Fundamental Analysis Tool** is an automated workflow designed to evaluate a stock's fundamentals using financial data and AI-driven insights. Built on the n8n automation platform, it: 1. **Collects** financial data for a user-specified stock from AlphaVantage. 2. **Processes** and structures this data for analysis. 3. **Analyzes** the data using the Mistral AI model to provide expert-level insights. 4. **Generates** a visually appealing HTML report with charts and delivers it via email. The tool is triggered by a form where users input a **stock symbol** (e.g., NVDA for NVIDIA) and their **email address**. From there, it follows a three-stage process: **data retrieval**, **data processing**, and **AI analysis with report generation**. --- ## 1. Fundamental Analysis: The Foundation Fundamental analysis involves evaluating a company's intrinsic value by examining its financial health, competitive position, and market environment. This tool performs fundamental analysis by: ### Data Retrieval - **Data Types**: Six types of data are retrieved via HTTP requests: - **Overview**: General company details (e.g., sector, industry, market cap). - **Income Statement**: Revenue, net income, and profitability metrics. - **Balance Sheet**: Assets, liabilities, and equity. - **Cash Flow**: Operating, investing, and financing cash flows. - **Earnings Calendar**: Upcoming earnings events. - **Earnings**: Historical earnings data (annual and quarterly). ### Key Metrics Analyzed The tool structures this data into **8 categories** critical to fundamental analysis, as defined in the Code1 node: 1. **Economic Moats & Competitive Advantage**: Assesses sustainable advantages (e.g., R&D spending, gross profit). 2. **Financial Health & Profitability**: Examines ROE, debt levels, and dividend yield. 3. **Valuation & Market Sentiment**: Evaluates P/E ratio, PEG ratio, and book value. 4. **Management & Capital Allocation**: Reviews market cap justification and cash allocation (e.g., R&D, buybacks). 5. **Industry & Risk Exposure**: Analyzes revenue cyclicality and geopolitical risks. 6. **Key Metrics to Probe**: Investigates net income trends and gross margins. 7. **Red Flags**: Identifies risks like inventory issues or stock dilution. 8. **Final Checklist**: Summarizes pricing power and risk/reward potential. These categories cover the core pillars of fundamental analysis, ensuring a holistic evaluation of the stock's intrinsic value and risks. --- ## 2. Stock Analysis: Tailored Insights The tool performs stock-specific analysis by focusing on the user-provided **stock symbol**. Here's how it tailors the process: ### Input and Customization - **Form Submission**: Users enter a stock symbol (e.g., NVDA) and email via the On Form Submission node. - **Dynamic Data Fetching**: The Set Variables node passes the stock symbol to the API calls, ensuring the analysis is specific to the chosen stock. ### Processing for Relevance - **Data Filtering**: The workflow limits historical data to the **last 5 years** (via the Limit node), focusing on recent trends. - **Merging and Cleaning**: The Merge and Code2 nodes combine and refine the data, removing irrelevant fields (e.g., quarterly reports) and aggregating annual reports for consistency. ### Output - The final report is titled with the stock's name (e.g., Fundamental Analysis - NVIDIA), ensuring the analysis is clearly tied to the user's chosen stock. This stock-specific approach makes the tool practical for investors analyzing individual companies rather than broad market trends. --- ## 3. AI Integration: Expert-Level Insights The integration of **AI** (via the Mistral model or others) is what sets this tool apart, automating complex analysis and report generation. Here's how AI is woven into the workflow: ### Data Preparation for AI - **Structuring**: The Code1 node organizes the raw data into a JSON schema aligned with the eight fundamental analysis categories. - This structured data is fed into the AI for analysis. ### AI Analysis - **Node**: Basic LLM Chain uses the **Mistral AI model**. - **Prompt**: The AI is instructed to act as an expert financial advisor with 50 years of experience and answer specific questions for each category, such as: - *Economic Moats*: What sustainable competitive advantages protect the company's margins? - *Financial Health*: Is ROE driven by leverage or true profitability? - *Red Flags*: Are supply chain issues a concern? - **Output**: The AI generates a JSON response with detailed insights, e.g.: ```json { "Economic Moats & Competitive Advantage": "NVIDIA's leadership in GPU technology and strong R&D investment...", "Financial Health & Profitability": "ROE of 25% is exceptional, driven by profitability rather than leverage...", ... } ```

Platform

n8n

Category

AI

Price

Free

Creator

Sebastian/OptiLever

• set
• code
• html
• gmail
• limit
• merge
• splitOut
• aggregate
• stickyNote
• formTrigger