NASDAQ Historical Daily Prices Dataset

This repository refers to the work of Oleh Onyshchak from Kaggle (https://www.kaggle.com/datasets/jacksoncrow/stock-market-dataset), which contains historical daily prices for all tickers currently trading on the NASDAQ. The data has been sourced from Yahoo Finance using the yfinance Python package. An up-to-date list of NASDAQ tickers is available at nasdaqtrader.com.

📅 Dataset Summary

• Coverage: Historical prices up to todayJanuary 23, 2025.
• File Format: CSV files for each ticker.
• Data Update: To retrieve more recent data, fork this repository and run the included data collection script.

📂 Data Structure

Each ticker's data is stored in a CSV file with the following fields:

Field	Description
Date	Trading date
Open	Opening price of the trading day
High	The highest price reached during the day
Low	The lowest price reached during the day
Close	Closing price, adjusted for stock splits
Adj Close	Adjusted closing price, accounting for both dividends and splits
Volume	Total number of shares traded during the day

📁 Folder Organization

• ETFs: Contains CSV files for exchange-traded funds.
• Stocks: Contains CSV files for individual stocks.
• etfs: Contains CSV files for exchange-traded funds without format changes (Oleh Onyshchak's version).
• Stocks: Contains CSV files for individual stocks without format changes (Oleh Onyshchak's version).
• Each file is named after its corresponding ticker symbol (e.g., AAPL.csv for Apple Inc.).
• Metadata for all tickers, such as their full names, is available in the symbols_valid_meta.csv file.

🚀 How to Use

1. Browse the CSV files to access historical price data for specific tickers.
2. Refer to the symbols_valid_meta.csv file for ticker metadata and identification.
3. To get updated data:
   • Fork this repository.
   • Execute the data collection script available in the repository.

💡 Applications

This dataset is suitable for:

• Financial analysis
• Backtesting trading strategies
• Stock market trend exploration
• Machine learning models for market prediction

📜 License

This project is licensed under the MIT License. Feel free to use, modify, and distribute this dataset as needed.

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⭐ Contributions

Contributions are welcome! Feel free to submit a pull request or raise issues for any suggestions or improvements.

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📧 Contact

For questions or support, feel free to contact the repository maintainer via GitHub or leave a comment in the Issues section.