https://github.com/jiya19g/marketview

predictive model designed to forecast stock market trends by integrating historical stock price data with sentiment analysis from social media tweets. This model leverages technical indicators and real-time sentiment to provide insights into stock movements and assist in making informed investment decisions.
https://github.com/jiya19g/marketview

gan jupyter-notebook lstm machine-learning python sentiment-analysis stock-market twitter-sentiment-analysis

Last synced: 19 days ago
JSON representation

predictive model designed to forecast stock market trends by integrating historical stock price data with sentiment analysis from social media tweets. This model leverages technical indicators and real-time sentiment to provide insights into stock movements and assist in making informed investment decisions.

• Host: GitHub
• URL: https://github.com/jiya19g/marketview
• Owner: jiya19g
• Created: 2024-09-07T06:33:27.000Z (2 months ago)
• Default Branch: main
• Last Pushed: 2024-09-09T20:25:18.000Z (2 months ago)
• Last Synced: 2024-10-10T17:21:27.619Z (about 1 month ago)
• Topics: gan, jupyter-notebook, lstm, machine-learning, python, sentiment-analysis, stock-market, twitter-sentiment-analysis
• Language: Jupyter Notebook
• Homepage:
• Size: 1.16 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# MarketView

MarketView is a predictive model designed to forecast stock market trends by integrating historical stock price data with sentiment analysis from social media tweets. This model leverages technical indicators and real-time sentiment to provide insights into stock movements and assist in making informed investment decisions.

## Features

- **Stock Price Prediction**: Forecast stock prices using historical data and technical indicators.

- **Sentiment Analysis**: Analyze sentiment from social media tweets to gauge market mood.

- **Technical Indicators**: Incorporate various technical indicators like Moving Averages, Exponential Moving Averages, and Bollinger Bands to enhance prediction accuracy.

- **Real-time Insights**: Combine historical data with real-time sentiment analysis for up-to-date market predictions.

## Installation

1. Clone the repository:

   ```bash

   git clone https://github.com/jiya19g/MarketView.git

## Usage

### Jupyter Notebook

1. Open the `MarketView.ipynb` file in Jupyter Notebook or JupyterLab.

2. Run the cells in order to execute the model and generate predictions.

3. Visualize and analyze the results within the notebook.

### Python Script

1. Run the Python script `MarketView.py` to execute the model:

   ```bash

   python MarketView.py

## Technical Details

### Technical Indicators

The model uses Moving Averages (MA), Exponential Moving Averages (EMA), and Bollinger Bands to analyze stock trends.

### Sentiment Analysis 

Utilizes VADER for sentiment analysis to gauge the mood of stock market participants.

## Contributing

Feel free to contribute to this project by submitting issues or pull requests. Please follow the project's code of conduct and contribution guidelines.

## License

This project is licensed under the MIT License - see the LICENSE file for details.