This dataset contains Apple's (AAPL) stock data for the last 10 years (from 2010 to date). I believe insights from this data can be used to build useful price forecasting algorithms to aid investment. I would like to thank Nasdaq for providing access to this rich dataset. I will make sure I update this dataset every few months.

Title: Stock Prices of 500 Biggest Companies by Market Cap (Last 5 Years)

Description: This dataset comprises historical stock market data extracted from Yahoo Finance, spanning a period of five years. It includes daily records of stock performance metrics for the top 500 companies based on market capitalization.

Attributes: 1. Date: The date corresponding to the recorded stock market data. 2. Open: The opening price of the stock on a given date. 3. High: The highest price of the stock reached during the trading day. 4. Low: The lowest price of the stock observed during the trading day. 5. Close: The closing price of the stock on a specific date. 6. Volume: The volume of shares traded on the given date. 7. Dividends: Any dividend payments made by the company on that date (if applicable). 8. Stock Splits: Information regarding any stock splits occurring on that date. 9. Company: Ticker symbol or identifier representing the respective company.

Usefulness: - Investors and analysts can leverage this dataset to conduct various analyses such as trend analysis, volatility assessment, and predictive modeling. - Researchers can explore correlations between stock prices of different companies, sector-wise performance, and market trends over the specified duration. - Machine learning enthusiasts can employ this dataset for developing predictive models for stock price forecasting or anomaly detection.

Note: Prior to using this dataset, it's recommended to perform data cleaning, handling missing values, and verifying the consistency of data across companies and time periods.

License: The dataset is sourced from Yahoo Finance and is provided for analytical purposes. Refer to Yahoo Finance's terms of use for further details on data usage and licensing.

This comprehensive dataset curated by Stocksphi presents the 1-minute interval historical stock data for Apple Inc. (AAPL) spanning from 2006 to 2024. The dataset encapsulates key metrics such as opening price, high price, low price, closing price, adjusted close price, and trading volume for each minute of trading throughout this extensive period.

Insights and Applications:

Intraday Analysis: Delve into the intricate price movements and trading dynamics of AAPL stock on a minute-by-minute basis, gaining insights into short-term trends and patterns. Algorithmic Trading: Utilize the dataset to develop and backtest algorithmic trading strategies tailored for intraday trading, leveraging historical price and volume data. Quantitative Analysis: Conduct quantitative analysis to explore statistical properties, correlations, and anomalies within the dataset, facilitating data-driven decision-making. Financial Modeling: Employ the dataset for constructing predictive models and forecasting AAPL stock behavior at a fine-grained temporal resolution. Academic Research: Serve as a valuable resource for academic research in finance, enabling scholars to investigate market microstructure, liquidity dynamics, and other relevant topics. This meticulously curated dataset offers a wealth of information and opportunities for quantitative analysis, strategy development, financial research, and more, empowering traders, analysts, researchers, and enthusiasts to unlock valuable insights and enhance their understanding of AAPL stock dynamics over nearly two decades.

Free historical options data, dataset files in CSV format.

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

Full historical data for the S&P 500 (ticker ^GSPC), sourced from Yahoo Finance (https://finance.yahoo.com/).

Including Open, High, Low and Close prices in USD + daily volumes.

Info about S&P 500: https://en.wikipedia.org/wiki/S%26P_500

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Historical dataset of the United States Stock Market Index (S&P 500), covering values from 1928-01-01 to 2025-11-28, with the latest releases and long-term trends. Available for free download in CSV format.

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🥤 Coca-Cola (KO) Stock Price History (1919–2025)

This dataset provides daily historical stock price data for The Coca-Cola Company (ticker: KO) from January 2, 1962 to April 6, 2025. It captures Coca-Cola’s stock performance through decades of economic cycles, technological shifts, and global events — making it a rich resource for time-series analysis, investment research, and machine learning projects.

📂 Dataset Overview

🧮 Dataset Dimensions

• Total Rows: 15,922
• Total Columns: 7
• Missing Values: None ✅
• Date Range: 1962-01-02 to 2025-04-06

📊 Summary Statistics

• Highest Close Price: $73.18
• Lowest Close Price: $0.19
• Max Volume: 124M+ shares
• Average Close Price: ~$18.45
• Adjusted Prices: Range from $0.03 to $73.18

💡 Use Cases

• Time-series forecasting with LSTM, ARIMA, Prophet
• Volatility analysis and pattern detection
• Financial data visualization across decades
• Backtesting trading strategies on long-term data
• Comparing adjusted vs. raw stock prices

🧠 Project Ideas

• Predict future stock prices using ML models
• Visualize price trends during major economic events
• Analyze the effect of dividends and stock splits
• Build a financial dashboard using Plotly or Streamlit

📎 License

This dataset is for educational and research purposes only. For financial trading or commercial use, always consult a licensed data provider.

🙌 Acknowledgment

This dataset was compiled to support learning in data science, finance, and AI fields. Feel free to use it in your projects — and if you do, share your work! 📬 Contect info:

You can contect me for more data sets any type of data you want.

-E_mail

-Linkdin

-Kaggle

-X

-Github

The Dow Jones Industrial Average (DJIA) is a stock market index used to analyze trends in the stock market. While many economists prefer to use other, market-weighted indices (the DJIA is price-weighted) as they are perceived to be more representative of the overall market, the Dow Jones remains one of the most commonly-used indices today, and its longevity allows for historical events and long-term trends to be analyzed over extended periods of time. Average changes in yearly closing prices, for example, shows how markets developed year on year. Figures were more sporadic in early years, but the impact of major events can be observed throughout. For example, the occasions where a decrease of more than 25 percent was observed each coincided with a major recession; these include the Post-WWI Recession in 1920, the Great Depression in 1929, the Recession of 1937-38, the 1973-75 Recession, and the Great Recession in 2008.

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📊 NIFTY500 Stocks Data

Get comprehensive historical stock data for the NIFTY 500 index! 📈 This dataset includes stock prices at various time intervals for each NIFTY 500 company, organized into Excel files.

📁 File Naming Convention

• Files named by NSE code, e.g., RELIANCE.xlsx

📜 Data Description

Each sheet in an Excel file contains: - 📅 Date: Date and time - 🏦 Open: Opening price - 📈 High: Highest price - 📉 Low: Lowest price - 🔒 Close: Closing price - 🔄 Volume: Shares traded

🎯 Usage

Ideal for: - Financial analysts 📊 - Data scientists 🤖 - Market researchers 🔍 Analyze stock trends, develop trading strategies, or conduct research with varied timeframes for both long-term and short-term analysis.

📝 Licensing

• MIT License: Free to use for any purpose, even commercially 🌐

📥 How to Access

1. Download from Kaggle ⬇️
2. Unzip the file 🗂️
3. Open Excel files to explore 📂

Happy analyzing! 📊🚀

Dataset Overview

This dataset contains historical stock price data for Tesla, Inc. (TSLA) spanning from June 2010 to the present. The data includes daily records of Tesla's stock prices, covering various financial metrics for each trading day.

File Information

• File Name: TSLA.csv
• Number of Entries: 3499
• Number of Columns: 7
• File Size: 191.5 KB

Columns

1. Date (object): The date of the trading day in YYYY-MM-DD format.
2. Open (float64): The opening price of the stock on the given day.
3. High (float64): The highest price of the stock during the trading day.
4. Low (float64): The lowest price of the stock during the trading day.
5. Close (float64): The closing price of the stock on the given day.
6. Adj Close (float64): The adjusted closing price, accounting for corporate actions like stock splits and dividends.
7. Volume (int64): The total number of shares traded during the day.

Sample Data

Here are the first few rows of the dataset to give you a glimpse of the data structure:

Example Chart

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12685278%2F9479dbe596f198163a6641a5606bea6b%2FTS.png?generation=1716412477393105&alt=media" alt="">

(If you want to get the code for the chart, please access the [Tesla Stock Historical Data - Chart Examples] https://www.kaggle.com/code/girumwondemagegn/tesla-stock-historical-data-updated-may-2024) in my notebooks.)

Acknowledgements

The data has been sourced from publicly available financial records and is intended for educational and research purposes.

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