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Context

Stock market data -- and particularly intraday price data -- can be very expensive to buy. To help more people gain access to it, here I provide daily as well as intraday price and volume data for all U.S.-based stocks and ETFs trading on the NYSE, NASDAQ, and NYSE MKT.

Content

The dataset (last updated 12/06/2017) is presented in CSV format as follows:

• Intraday data: Date,Time,Open,High,Low,Close,Volume,OpenInt

• Daily data: Date,Open,High,Low,Close,Volume,OpenInt

Acknowledgements

The dataset belongs to me. I’m sharing it here for free. You may do with it as you wish.

Inspiration

Many have tried, but most have failed, to predict the stock market's ups and downs. Can you do any better?

Dataset Information

This dataset includes daily price data for various stocks.

  Instruments Included

7000+ US Stocks

  Dataset Columns

symbol: The symbol of the stock. date: The date of the data. open: The opening price of the stock. high: The highest price of the stock. low: The lowest price of the stock. close: The closing price of the stock. volume: The volume of the stock. adj_close: The adjusted closing price of the stock.

  Data Splits

The… See the full description on the dataset page: https://huggingface.co/datasets/paperswithbacktest/Stocks-Daily-Price.

End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.

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.

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.

The Dow Jones U.S. Completion Total Stock Market Index

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

Prices for United States Stock Market Index (US1000) including live quotes, historical charts and news. United States Stock Market Index (US1000) was last updated by Trading Economics this August 2 of 2025.

Prices for United States Stock Market Index (US30) including live quotes, historical charts and news. United States Stock Market Index (US30) was last updated by Trading Economics this August 2 of 2025.

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
• Concierge customer success team
• Comarketing & promotional initiatives

Platinum

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

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United States Stock Prices: 12 Months Expectation: Increase data was reported at 36.100 % in Apr 2025. This records a decrease from the previous number of 39.900 % for Mar 2025. United States Stock Prices: 12 Months Expectation: Increase data is updated monthly, averaging 36.200 % from Jun 1987 (Median) to Apr 2025, with 455 observations. The data reached an all-time high of 57.200 % in Nov 2024 and a record low of 18.100 % in Mar 2008. United States Stock Prices: 12 Months Expectation: Increase data remains active status in CEIC and is reported by The Conference Board. The data is categorized under Global Database’s United States – Table US.H052: Consumer Confidence Index: Stock Price Expectation. [COVID-19-IMPACT]

The price of Meta (former Facebook) shares traded on the Nasdaq stock exchange fluctuated significantly but increased overall during the period from May 2012 to January 2025. After peaking at ****** U.S. dollars per share in August 2021, the price of Meta shares started to fluctuate and exceeded its previous peak in 2025. The share price stood at ****** U.S. dollars as of the end of January 2025. Substantial fluctuations in the last few years Meta's stock prices have fluctuated particularly after the rebranding announcement in late 2021. Following the announcement and through 2022, Meta's revenue remained rather stagnant, and its net income decreased considerably. Moreover, the tech giant announced one of the industry's largest layoffs in late 2022. As a result, the share price hit a low of ***** U.S. dollars in October 2022, the lowest value observed since 2016. However, Meta's share price has been steadily recovering since then. Shift in strategy for the world’s first social network Meta has shifted its focus to the metaverse, virtual reality (VR), and augmented reality (AR), with the rebranding in late 2021. As a result, Reality Labs was established as a dedicated business and research unit to focus on developing metaverse and AR/VR technologies. However, as of early 2023, Meta still relies mainly on advertising and its Family of Apps to generate most of its revenue, despite having made significant investments in virtual reality. Reality Labs generated *** billion U.S. dollars in revenue in 2024 and has been consistently incurring operating losses since 2019.

Stock prices of selected regional banks in the United States plummeted in March 2023, as investor confidence dropped due to economic uncertainties. Silicon Valley Bank failed on 10th of March 2023. The stock prices of the displayed banks fell particularly sharply on and after that day, which was the second largest bank failure since 2001. The observed period was particularly devastating for First Republic, whose stock price was more than ** percent lower on the 20th of March than on the first day of the month.

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The dataset consists of daily data from US Dow Jones for 501 large companies, over the time span 2010-2016, while monthly publicly available indexes are also used.

Dow Jones U.S. Technology index is predicted to experience a moderate bullish trend with potential for notable gains. The index may face resistance around key technical levels, but overall sentiment remains positive with ample opportunities for investors seeking growth and diversification. However, investors should be aware of potential risks such as market volatility, geopolitical uncertainties, and changes in the technology sector.