Overview

This dataset contains historical daily prices for all tickers currently trading on NASDAQ. The up to date list is available from nasdaqtrader.com. The historic data is retrieved from Yahoo finance via yfinance python package.

It contains prices for up to 01 of April 2020. If you need more up to date data, just fork and re-run data collection script also available from Kaggle.

Data Structure

The date for every symbol is saved in CSV format with common fields:

• Date - specifies trading date
• Open - opening price
• High - maximum price during the day
• Low - minimum price during the day
• Close - close price adjusted for splits
• Adj Close - adjusted close price adjusted for both dividends and splits.
• Volume - the number of shares that changed hands during a given day

All that ticker data is then stored in either ETFs or stocks folder, depending on a type. Moreover, each filename is the corresponding ticker symbol. At last, symbols_valid_meta.csv contains some additional metadata for each ticker such as full name.

The latest closing stock price for Exxon as of June 27, 2025 is 109.38. An investor who bought $1,000 worth of Exxon stock at the IPO in 1984 would have $41,833 today, roughly 42 times their original investment - a 9.60% compound annual growth rate over 41 years. The all-time high Exxon stock closing price was 122.12 on October 07, 2024. The Exxon 52-week high stock price is 126.34, which is 15.5% above the current share price. The Exxon 52-week low stock price is 97.80, which is 10.6% below the current share price. The average Exxon stock price for the last 52 weeks is 112.58. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

The main stock market index of United States, the US500, rose to 6391 points on July 31, 2025, gaining 0.45% from the previous session. Over the past month, the index has climbed 3.12% and is up 17.34% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

The latest closing stock price for Great Ajax as of June 09, 2025 is 2.69. An investor who bought $1,000 worth of Great Ajax stock at the IPO in 2015 would have $-525 today, roughly -1 times their original investment - a -7.17% compound annual growth rate over 10 years. The all-time high Great Ajax stock closing price was 10.01 on November 05, 2021. The Great Ajax 52-week high stock price is 3.86, which is 43.5% above the current share price. The Great Ajax 52-week low stock price is 2.29, which is 14.9% below the current share price. The average Great Ajax stock price for the last 52 weeks is 3.12. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

Experience a decade of NASDAQ market dynamics with this comprehensive historical price dataset from 2014 to 2024.

The NASDAQ Composite is a benchmark index representing the performance of more than 2,500 stocks listed on the NASDAQ stock exchange, encompassing various sectors including technology, healthcare, and finance. This dataset, sourced meticulously from Yahoo Finance, offers daily insights into the index's opening, highest, lowest, and closing prices, along with adjusted close prices and daily volume.

We offer three easy-to-understand equity data packages to fit your business needs. Visit intrinio.com/pricing to compare packages.

Bronze

The Bronze package is ideal for developing your idea and prototyping your platform with high-quality EOD equity pricing data, standardized financial statement data, and supplementary fundamental datasets.

When you’re ready for launch, it’s a seamless transition to our Silver package for additional data sets, 15-minute delayed equity pricing data, expanded history, and more.

• Historical EOD equity prices & technicals (10 years history)
• Security reference data
• Standardized & as-reported financial statements (5 years history)
• 7 supplementary fundamental data sets

Bronze Benefits:

• Web API access
• 300 API calls/minute limit
• Unlimited internal users
• Unlimited internal & external display
• Built-in ticketing system
• Live chat & email support

Silver

The Silver package is ideal for startups that are in development, testing, or in the beta launch phase. Hit the ground running with 15-minute delayed and historical intraday and EOD equity prices, plus our standardized and as-reported financial statement data with nine supplementary data sets, including insider transactions and institutional ownership.

When you’re ready to scale, easily move up to the Gold package for our full range of data sets and full history, real-time equity pricing data, premium support options, and much more.

• 15-minute delayed & historical intraday equity prices
• Historical EOD equity prices & technicals (full history)
• Security reference data
• Standardized & as-reported financial statements (10 years history)
• 9 supplementary fundamental data sets

Silver Benefits:

• Web API access
• 2,000 API calls/minute limit
• Access to third-party datasets via Intrinio API (additional fees required)
• Unlimited internal users
• Unlimited internal & external display
• Built-in ticketing system
• Live chat & email support

Gold

The Gold package is ideal for funded companies that are in the growth or scaling stage, as well as institutions that are innovating within the fintech space. This full-service solution offers our complete collection of equity pricing data feeds, from real-time to historical EOD, plus standardized financial statement data and nine supplementary feeds.

You’ll also have access to our wide range of modern access methods, third-party data via Intrinio’s API with licensing assistance, support from our team of expert engineers, custom delivery architectures, and much more.

• Real-time equity prices
• Historical intraday equity prices
• Historical EOD equity prices & technicals (full history)
• Security reference data
• Standardized & as-reported financial statements (full history)
• 9 supplementary fundamental data sets

Gold Benefits:

• No exchange fees
• No user reporting or variable per-user exchange fees
• High liquidity (6%+)
• Web API & WebSocket access
• 2,000 API calls/minute limit
• Customizable access methods (Snowflake, FTP, etc.)
• Access to third-party datasets via Intrinio API (additional fees required)
• Unlimited internal users
• Unlimited internal & external display
• Built-in ticketing system
• Live chat & email support
• Access to engineering team
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Platinum

Don’t see a package that fits your needs? Our team can design premium custom packages for institutions.

Throughout the 1920s, prices on the U.S. stock exchange rose exponentially, however, by the end of the decade, uncontrolled growth and a stock market propped up by speculation and borrowed money proved unsustainable, resulting in the Wall Street Crash of October 1929. This set a chain of events in motion that led to economic collapse - banks demanded repayment of debts, the property market crashed, and people stopped spending as unemployment rose. Within a year the country was in the midst of an economic depression, and the economy continued on a downward trend until late-1932.

It was during this time where Franklin D. Roosevelt (FDR) was elected president, and he assumed office in March 1933 - through a series of economic reforms and New Deal policies, the economy began to recover. Stock prices fluctuated at more sustainable levels over the next decades, and developments were in line with overall economic development, rather than the uncontrolled growth seen in the 1920s. Overall, it took over 25 years for the Dow Jones value to reach its pre-Crash peak.

Updated daily, this data feed offers end of day prices for major US publicly traded stocks with history more than 20 years. Prices are provided both adjusted and unadjusted.

Key Features:

Covers all stocks with primary listing on NASDAQ, AMEX, NYSE and ARCA. Includes unadjusted and adjusted open, high, low, close, volume. Includes dividend history and split history. Updated at or before 5:00pm ET on all trading days. Exchange corrections are applied by 9:30pm ET.

This dataset presents an extensive record of daily historical stock prices for Tesla, Inc. (TSLA), one of the world’s most innovative and closely watched electric vehicle and clean energy companies. The data was sourced from Yahoo Finance, a widely used and trusted provider of financial market data, and covers a significant period spanning from Tesla’s initial public offering (IPO) to the most recent date available at the time of extraction.

The dataset includes critical trading metrics for each market day, such as the opening price, highest and lowest prices of the day, closing price, adjusted closing price (accounting for dividends and splits), and total trading volume. This rich dataset supports a variety of use cases, including financial market analysis, investment research, time series forecasting, development and backtesting of trading algorithms, and educational projects in data science and finance.

Dataset Features

• Date: The calendar date for each trading session (in YYYY-MM-DD format)
• Open: The opening price of TSLA shares at the start of the trading day
• High: The highest price reached during the trading session
• Low: The lowest price reached during the trading session
• Close: The last price at which the stock traded during the day
• Adj Close: The closing price adjusted for corporate actions (splits, dividends, etc.)
• Volume: The total number of TSLA shares traded on that day

Source and Collection Details

• Source: Yahoo Finance - Tesla (TSLA) Historical Data
• Collection Method: Data was downloaded using Yahoo Finance's CSV export feature for accuracy and completeness.
• Time Range: Covers from Tesla’s IPO (June 2010) to the most recent available trading day.
• Data Integrity: Minimal cleaning was performed—dates were standardized, and any duplicate or empty rows were removed; all values remain as originally reported by Yahoo Finance.

Example Use Cases

• Stock Price Prediction: Train and test time series models (ARIMA, LSTM, Prophet, etc.) to forecast Tesla’s stock prices.
• Algorithmic Trading: Backtest and evaluate trading strategies using historical price and volume data.
• Market Trend Analysis: Analyze price trends, volatility, and return rates over different periods.
• Event Study: Investigate the impact of major announcements (e.g., product launches, earnings releases) on TSLA stock price.
• Educational Projects: Use as a hands-on resource for learning finance, statistics, or machine learning.

License & Acknowledgments

• Intended Use: This dataset is provided for academic, research, and personal projects. For commercial or investment use, please verify data accuracy and consult Yahoo Finance’s terms of use.
• Acknowledgment: Data sourced from Yahoo Finance. All trademarks and copyrights belong to their respective owners.

The latest closing stock price for Piper Sandler as of July 09, 2025 is 289.78. An investor who bought $1,000 worth of Piper Sandler stock at the IPO in 2003 would have $7,298 today, roughly 7 times their original investment - a 10.10% compound annual growth rate over 22 years. The all-time high Piper Sandler stock closing price was 343.43 on November 25, 2024. The Piper Sandler 52-week high stock price is 351.80, which is 21.4% above the current share price. The Piper Sandler 52-week low stock price is 202.91, which is 30% below the current share price. The average Piper Sandler stock price for the last 52 weeks is 278.85. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

Context

Stock market data can be interesting to analyze and as a further incentive, strong predictive models can have large financial payoff. The amount of financial data on the web is seemingly endless. A large and well structured dataset on a wide array of companies can be hard to come by. Here I provide a dataset with historical stock prices (last 5 years) for all companies currently found on the S&P 500 index.

The script I used to acquire all of these .csv files can be found in this GitHub repository In the future if you wish for a more up to date dataset, this can be used to acquire new versions of the .csv files.

Content

The data is presented in a couple of formats to suit different individual's needs or computational limitations. I have included files containing 5 years of stock data (in the all_stocks_5yr.csv and corresponding folder) and a smaller version of the dataset (all_stocks_1yr.csv) with only the past year's stock data for those wishing to use something more manageable in size.

The folder individual_stocks_5yr contains files of data for individual stocks, labelled by their stock ticker name. The all_stocks_5yr.csv and all_stocks_1yr.csv contain this same data, presented in merged .csv files. Depending on the intended use (graphing, modelling etc.) the user may prefer one of these given formats.

All the files have the following columns: Date - in format: yy-mm-dd Open - price of the stock at market open (this is NYSE data so all in USD) High - Highest price reached in the day Low Close - Lowest price reached in the day Volume - Number of shares traded Name - the stock's ticker name

Acknowledgements

I scraped this data from Google finance using the python library 'pandas_datareader'. Special thanks to Kaggle, Github and The Market.

Inspiration

This dataset lends itself to a some very interesting visualizations. One can look at simple things like how prices change over time, graph an compare multiple stocks at once, or generate and graph new metrics from the data provided. From these data informative stock stats such as volatility and moving averages can be easily calculated. The million dollar question is: can you develop a model that can beat the market and allow you to make statistically informed trades!

Dataset Description:

This dataset provides historical stock price data for selected ticker symbols ['AAPL', 'MSFT', 'JPM', 'GS', 'AMZN', 'PG', 'KO', 'JNJ', 'XOM', 'CAT'] from January 1, 2014, to December 31, 2023. It contains the daily opening, highest, lowest, closing, adjusted closing prices, and trading volume for each trading day. These tickers represent a diverse range of sectors to allow comprehensive financial analysis.

Purpose and Use Case:

This dataset is ideal for financial analysis, market trend assessments, and investment decision-making. Analysts and researchers can use this dataset to: * Analyze price and market trends. * Evaluate volatility by analyzing price fluctuations and trading volume. * Use historical price movements to forecast and predict future trends. * Assess investment opportunities and portfolio performance.

Acknowledgments:

Data was collected using Python and Yahoo Finance. This dataset supports visualization, exploratory data analysis (EDA), and in-depth analysis to develop a predictive model for forecasting stock prices, aiming to gain insights, identify patterns, and improve prediction accuracy.

Potential Research Questions and Inspiration:

• What is the correlation between stock prices and trading volume over time?
• How do corporate actions and adjustments affect adjusted closing prices?
• How does volatility vary across different stocks and sectors?
• What key factors influence stock price dynamics, such as earnings reports, industry news, regulatory changes, or global economic trends?

The latest closing stock price for Ellington Credit as of June 20, 2025 is 5.74. An investor who bought $1,000 worth of Ellington Credit stock at the IPO in 2013 would have $366 today, roughly 0 times their original investment - a 2.63% compound annual growth rate over 12 years. The all-time high Ellington Credit stock closing price was 7.89 on June 14, 2021. The Ellington Credit 52-week high stock price is 7.20, which is 25.4% above the current share price. The Ellington Credit 52-week low stock price is 4.33, which is 24.6% below the current share price. The average Ellington Credit stock price for the last 52 weeks is 6.40. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

What are the most successful trading algorithms? (NTAP Stock Forecast)

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

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.

United Kingdom's main stock market index, the GB100, fell to 9133 points on July 31, 2025, losing 0.05% from the previous session. Over the past month, the index has climbed 3.96% and is up 10.25% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United Kingdom. United Kingdom Stock Market Index (GB100) - values, historical data, forecasts and news - updated on July of 2025.

China's main stock market index, the SHANGHAI, fell to 3573 points on July 31, 2025, losing 1.18% from the previous session. Over the past month, the index has climbed 3.34% and is up 21.85% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from China. China Shanghai Composite Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

The latest closing stock price for RMR Group as of June 26, 2025 is 16.64. An investor who bought $1,000 worth of RMR Group stock at the IPO in 2015 would have $1,514 today, roughly 2 times their original investment - a 9.66% compound annual growth rate over 10 years. The all-time high RMR Group stock closing price was 57.34 on September 10, 2018. The RMR Group 52-week high stock price is 26.43, which is 58.8% above the current share price. The RMR Group 52-week low stock price is 13.48, which is 19% below the current share price. The average RMR Group stock price for the last 52 weeks is 20.49. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

The latest closing stock price for Angel Oak Mortgage REIT as of July 02, 2025 is 9.59. An investor who bought $1,000 worth of Angel Oak Mortgage REIT stock at the IPO in 2021 would have $-169 today, roughly 0 times their original investment - a -4.52% compound annual growth rate over 4 years. The all-time high Angel Oak Mortgage REIT stock closing price was 11.69 on August 02, 2021. The Angel Oak Mortgage REIT 52-week high stock price is 12.94, which is 34.9% above the current share price. The Angel Oak Mortgage REIT 52-week low stock price is 7.36, which is 23.3% below the current share price. The average Angel Oak Mortgage REIT stock price for the last 52 weeks is 10.01. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

Lebanon's main stock market index, the Blom, fell to 2020 points on July 30, 2025, losing 0.18% from the previous session. Over the past month, the index has declined 8.53%, though it remains 11.51% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Lebanon. Lebanon Stock Market BLOM - values, historical data, forecasts and news - updated on July of 2025.