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Stock Market Forecast with LLM

Overview

This project combines traditional technical analysis with artificial intelligence to provide comprehensive stock market predictions and analysis. The system processes real-time market data from major tech stocks (AAPL, MSFT, GOOGL, AMZN, TSLA) and generates actionable insights through:

What You Get:

  1. Price Predictions

    • Next-day price forecasts
    • Trend direction indicators
    • Confidence metrics for predictions

  2. Technical Analysis Visualization

    • Interactive price charts
    • Moving averages (20-day and 50-day)
    • RSI (Relative Strength Index) indicators
    • Overbought/Oversold signals

  3. AI-Powered Insights

    • Market sentiment analysis
    • Risk level assessment
    • Trading recommendations (Buy/Hold/Sell)
    • Automatic pattern recognition

  4. Performance Metrics

    • Current price vs predicted movement
    • Technical indicator status
    • Sentiment analysis scores
    • Risk assessment levels

Project Structure

Data Fetching and Processing

  • Uses yfinance to fetch real-time stock data
  • Processes historical data for technical analysis
  • Handles data cleaning and formatting for analysis

Technical Analysis

  • Calculates Moving Averages (20-day and 50-day) for trend identification
  • Implements Relative Strength Index (RSI) for overbought/oversold signals
  • Processes price movements and volume data

LLM Integration

  • Utilizes OpenAI's API for sentiment analysis
  • Processes financial news and market sentiment
  • Incorporates AI-driven insights into the analysis

Visualization Components

  • Creates interactive price charts with technical indicators
  • Displays RSI analysis with overbought/oversold zones
  • Visualizes predicted price movements
  • Shows sentiment analysis results

Features

  • Stock data fetching using yfinance
  • Technical analysis with moving averages and RSI
  • Price prediction using historical data
  • Sentiment analysis integration
  • Visualization of stock trends and indicators

Key Functions

  • fetch_stock_data(): Retrieves historical stock data
  • calculate_technical_indicators(): Computes technical analysis metrics
  • analyze_with_llm(): Processes text data using LLM
  • analyze_sentiment_batch(): Batch processes sentiment analysis
  • plot_predictions(): Creates visualization of analysis results

Dependencies

  • Python 3.x
  • pandas: Data manipulation and analysis
  • yfinance: Stock data retrieval
  • numpy: Numerical computations
  • scikit-learn: Data preprocessing
  • matplotlib: Data visualization
  • seaborn: Statistical data visualization
  • openai: LLM integration

Setup and Usage

  1. Clone the repository
  2. Install required dependencies
  3. Set up OpenAI API key in .env file
  4. Run the Jupyter notebook

Environment Setup

Create a .env file with:

OPENAI_API_KEY=your_api_key_here