AI Stock Analyzer

The Stock Analyzer project is an AI-powered stock market analysis platform. Pick a stock to see its price history, technical indicators, fundamentals, ML predictions with backtested accuracy, recent news and sentiment, and risk metrics in one place. You can also ask an AI analyst questions about the stock and download a complete PDF analysis report.

Live Demo

View Deployed App on Render

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Overview

Home Page

Stock Analysis View

Stock Predictions

Platform Features

Module	What it does
Stock dashboard	Price, chart, volume, technical indicators, fundamentals, news, AI analysis
Market data	Local historical dataset with optional live data via yfinance
ML prediction	Feature engineering, model selection, 1- and 5-day direction and price forecasts, walk-forward backtesting, prediction tracking
RAG	News and company-document ingestion, chunking, embeddings, relevance × freshness retrieval with source grounding
AI agent	Stock-specific chat that picks tools (price, indicators, fundamentals, news, documents, ML, risk, report) and returns evidence-backed answers with sources
Reports	Downloadable 14-section PDF analysis report
Risk & disclaimer	Volatility, drawdown, VaR, model-confidence warnings and an educational-use disclaimer
Scalability	Caching, background jobs, rate limiting, Docker, CI

Design documentation: HLD · LLD · API · Database · Model lifecycle · AWS deployment · Roadmap & status

⚠ Disclaimer: This platform provides AI-generated market analysis for educational and informational purposes only. Predictions are probabilistic and may be inaccurate. It is not personalized investment advice.

Technologies Used

• React: User Interface
• Plotly.js: Interactive visualizations
• Axios: API calls
• Flask: Backend Framework
• yfinance: Stock data extraction
• Pandas: Data manipulation
• scikit-learn: ML prediction and backtesting; hashed n-gram embeddings for RAG
• Claude API (optional): natural-language synthesis of agent answers
• reportlab: PDF reports
• openpyxl: Excel development database (PostgreSQL schema for production)
• Redis (optional), Docker, GitHub Actions: caching, containers, CI

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Directory Structure

Directory structure:
└── srigadaakshaykumar-stock/
    ├── LICENSE
    ├── README.md
    ├── SETUP.md
    ├── CONTRIBUTION.md
    ├── CODE_OF_CONDUCT.md
    ├── SECURITY.md
    ├── package-lock.json
    ├── package.json
    ├── static.json
    ├── backend/
        ├──app/
        ├──data/
    │   ├── app.py
    |   ├── generate_csvs.py
    │   ├── requirements.txt
    │   ├── stock-prediction.ipynb
    │   └── tf.keras
    ├── public/
    |   ├── icon.png
    │   ├── index.html
    │   ├── manifest.json
    │   └── robots.txt
    └── src/
        ├── App.css
        ├── App.js
        ├── App.test.js
        ├── index.css
        ├── index.js
        ├── reportWebVitals.js
        ├── setupTests.js
        └── components/
            ├── About.jsx
            ├── AuthContext.jsx
            ├── BackToTopBtn.jsx
            ├── ContactForm.jsx
            ├── firebase.js
            ├── Footer.css
            ├── Footer.jsx
            ├── Header.jsx
            ├── Login.css
            ├── Login.js
            ├── Prediction.jsx
            ├── SentimentChart.jsx
            ├── SignUp.css
            ├── Signup.jsx
            ├── Stockdata.jsx
            ├── StockMetricCard.jsx
            ├── StockList.jsx
            └── data/
                └── stockData.json

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API Endpoints

Endpoint	Method	Description
/api/stocks/<ticker>	GET	Fetch historical stock data
/api/predict/<ticker>	GET	Predict future stock prices

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Data Pipeline Architecture

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Project Status

Stock Analyzer is currently in the development stage and hosted on a free hosting service for testing purposes.

The latest pulls are merged every Saturday.

Future Enhancements

We have a clear roadmap for improvements:

• Allow more API calls per day
• Reduce response time for end users
• Add International stock exchanges
• Enhance the user interface for better experience
• Improve machine learning model accuracy
• Provide more insightful and interactive visualizations
• Migrate deployment from Render to Google Cloud Platform (GCP)

Contributions

We welcome all forms of open-source contributions — whether it's a:

• Bug fix
• New feature
• Enhancement or optimization

Please make sure to:

• Review our Contribution Guidelines
• Follow the Setup Instructions to run the project locally
• Join the Discord

License

This project is licensed under the MIT License.
You’re free to use, modify, and share this software under the license terms.