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