Stock Analysis Dashboard

A full-stack web application that analyzes stock market data and generates trading signals using unsupervised machine learning clustering techniques. The application identifies market patterns through technical indicators and groups similar market conditions to generate trading signals.

Features

• Machine Learning-Based Analysis:

  • K-means clustering of market conditions
  • Feature engineering using technical indicators
  • Automated trading signal generation based on cluster performance
  • Dynamic cluster analysis and performance metrics

• Technical Analysis:

  • RSI (Relative Strength Index)
  • Bollinger Bands
  • Volatility metrics (including Garman-Klass)
  • Momentum indicators
  • Volume analysis

• Additional Features:

  • Real-time stock data via yfinance
  • Sentiment analysis using Alpha Vantage API
  • Interactive charts and visualizations
  • Custom date range analysis
  • Performance metrics (Sharpe ratio, win rate, drawdown)

Tech Stack

Frontend:

• React 18
• Vite
• TailwindCSS
• React Query v5
• Recharts for data visualization
• Lucide React for icons
• React DatePicker

Backend:

• FastAPI
• Python 3.12+
• pandas for data manipulation
• scikit-learn for machine learning
• yfinance for market data
• NumPy for numerical computations

Live site example

Website: Stock Analysis

Getting Started

Prerequisites

• Node.js (Latest LTS version)
• Python 3.12 or higher
• Alpha Vantage API key for sentiment analysis

Installation

1. Clone the repository

git clone https://github.com/Adham-Alammuri/stock.git

2. Frontend setup

cd frontend
npm install

3. Backend setup

cd backend
pip install -r requirements.txt

4. Environment setup

# Create .env file in backend directory
ALPHA_VANTAGE=your_api_key_here

Running Locally

1. Start the backend server:

cd backend
uvicorn main:app --reload

2. Start the frontend development server:

cd frontend
npm run dev

Visit http://localhost:5173 in your browser.

API Documentation

Key Endpoints

• /api/prediction/{ticker}/predict

  • Returns trading signals based on clustering analysis
  • Parameters:
    • ticker: Stock symbol (e.g., AAPL)
    • start_date (optional): Analysis start date (YYYY-MM-DD)
    • end_date (optional): Analysis end date (YYYY-MM-DD)
    • n_clusters (optional): Number of clusters (2-10, default: 5)
    • min_cluster_size (optional): Minimum size per cluster (≥3, default: 5)
    • lookback_window (optional): Historical data window (≥60, default: 252)
  • Returns comprehensive analysis including:
    • Current trading signal (BUY/HOLD/SELL)
    • Strategy performance metrics
    • Technical indicators
    • Clustering visualization

• /api/sentiment/{ticker}/analyze

  • Provides sentiment analysis from news and social media
  • Headers required:
    • X-API-KEY: Alpha Vantage API key
  • Returns:
    • Overall sentiment score
    • News volume and trends
    • Sentiment category
    • Historical sentiment data

Contact

Adham Alammuri

• LinkedIn: Adham Alammuri

Notes

This is a portfolio project created for educational and demonstration purposes. The trading signals and analysis provided should not be used as financial advice.