https://github.com/ahmad-masud/quant-market-predictor
📈 Quant Market Predictor is a Python tool designed to predict stock prices from the NASDAQ
https://github.com/ahmad-masud/quant-market-predictor
altair linear-regression machine-learning numpy pandas prediction python skicit-learn stock-market stock-price-prediction stocks streamlit volatility
Last synced: 8 months ago
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📈 Quant Market Predictor is a Python tool designed to predict stock prices from the NASDAQ
- Host: GitHub
- URL: https://github.com/ahmad-masud/quant-market-predictor
- Owner: ahmad-masud
- License: mit
- Created: 2024-02-01T18:03:45.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-02-17T22:50:18.000Z (over 1 year ago)
- Last Synced: 2025-02-17T23:23:44.362Z (over 1 year ago)
- Topics: altair, linear-regression, machine-learning, numpy, pandas, prediction, python, skicit-learn, stock-market, stock-price-prediction, stocks, streamlit, volatility
- Language: Python
- Homepage: https://quantmarketpredictor.streamlit.app
- Size: 1.92 MB
- Stars: 8
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# Quant Market Predictor
## Overview
Quant Market Predictor is a Python-based tool designed to forecast future stock prices using historical market data from NASDAQ. Utilizing Linear Regression to make a Statistics Model, this project aims to provide users with insights into potential future market prices.
## Features
- **Stock Price Prediction**: Predict future stock prices based on historical data.
- **Stock Risk Volatility**: Measure how risky it is to purchase a stock.
- **Data Visualization**: Plot historical stock price data for analysis.
## Installation
To run the Quant Market Predictor, you'll need Python installed on your system. Follow these steps to set up the project:
1. Clone the repository:
```sh
git clone https://github.com/ahmad-masud/quant-market-predictor.git
```
2. Navigate to the project directory:
```sh
cd quant-market-predictor
```
3. Install the required dependencies:
```sh
pip install -r requirements.txt
```
## Usage
Run the main script from the command line:
```sh
python -m streamlit run main.py
```
Follow the on-screen prompts to enter the ticker symbol, period for historical data, and select the desired functionality (e.g., predict future stock prices or plot historical data).
## Contributing
I welcome contributions to the Quant Market Predictor! If you have suggestions for improvements or bug fixes, please feel free to open an issue or submit a pull request.
## License
Quant Market Predictor is released under the MIT License. See the [LICENSE](LICENSE) file for more details.
## Disclaimer
The predictions made by this tool are for informational purposes only and should not be considered financial advice. Always conduct your own research and consult with a financial advisor before making investment decisions.
## Acknowledgments
- Data provided by [Yahoo Finance](https://finance.yahoo.com/).