Interactive chart of the NASDAQ Composite stock market index since 1971. Historical data is inflation-adjusted using the headline CPI and each data point represents the month-end closing value. The current month is updated on an hourly basis with today's latest value.

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.

Graph and download economic data for NASDAQ Composite Index (NASDAQCOM) from 1971-02-05 to 2025-06-20 about NASDAQ, composite, stock market, indexes, and USA.

Get Nasdaq real-time and historical data with support for fast market replay at over 19 million book updates per second. Test our data for free with only 4 lines of code.

Nasdaq TotalView-ITCH is a proprietary data feed that disseminates full order book depth and last sale data from the Nasdaq stock market (XNAS). It delivers every quote and order at each price level, along with any event that updates the order book after an order is placed, such as trade executions, modifications, or cancellations. Nasdaq is the most active US equity exchange by volume and represented 13.03% of the average daily volume (ADV) as of January 2025.

With its L3 granularity, Nasdaq TotalView-ITCH captures information beyond the L1, top-of-book data available through SIP feeds and enables more accurate modeling of book imbalances, trade directionality, quote lifetimes, and more. This includes explicit trade aggressor side, odd lots, auction imbalance data, and the Net Order Imbalance Indicator (NOII) for the Nasdaq Opening and Closing Crosses and Nasdaq IPO/Halt Cross—the best predictor of Nasdaq opening and closing prices available. Other key advantages of Nasdaq TotalView-ITCH over SIP data include faster real-time dissemination and precise exchange-side timestamping directly from Nasdaq.

Real-time Nasdaq TotalView-ITCH data is included with a Plus or Unlimited subscription through our Databento US Equities service. Historical data is available for usage-based rates or with any subscription. Visit our pricing page for more details or to upgrade your plan.

Breadth of coverage: 20,329 products

Asset class(es): Equities

Origin: Directly captured at Equinix NY4 (Secaucus, NJ) with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP.

Supported data encodings: DBN, CSV, JSON Learn more

Supported market data schemas: MBO, MBP-1, MBP-10, BBO-1s, BBO-1m, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Statistics, Status, Imbalance Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

Graph and download economic data for NASDAQ 100 Index (NASDAQ100) from 1986-01-02 to 2025-06-18 about NASDAQ, stock market, indexes, and USA.

Nasdaq BX TotalView-ITCH is a proprietary data feed that provides full order book depth and last sale information. It displays every quote and order at each price level on the BX market (formerly the Boston Stock Exchange) and captures all order book activity, including trade executions, order modifications, cancellations, and other events that update the book's state. This L3 granularity offers data not found in SIP feeds—such as explicit trade aggressor side and odd lots—and enable accurate modeling of quote lifetimes and queue dynamics.

This dataset covers all securities traded or routed through the BX exchange platform, including those listed on the Nasdaq, NYSE, NYSE American, NYSE Arca, and Cboe exchanges under Reg NMS. As of January 2025, the Nasdaq BX exchange represented 0.13% of the average daily volume (ADV).

Nasdaq BX attracts retail-focused brokers and traders with its inverted pricing model, offering rebates for liquidity removers and its Retail Price Improvement (RPI) program. It disseminates the Retail Price Improvement Indicator (RPII) to signal the availability of RPI orders, which are designed to improve upon the NBBO and promote better pricing opportunities for retail investors.

Historical data is available for usage-based rates or with any Databento US Equities subscription. Visit our pricing page for more details.

Breadth of coverage: 11,544 products

Asset class(es): Equities

Origin: Directly captured at Equinix NY4 (Secaucus, NJ) with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP.

Supported data encodings: DBN, CSV, JSON Learn more

Supported market data schemas: MBO, MBP-1, MBP-10, TBBO, Trades, BBO-1s, BBO-1m, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Imbalance, Statistics, Status Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

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

Get comprehensive coverage for 70+ trading venues with Databento's historical data APIs. Available in multiple data formats including MBO, MBP, and more.

Graph and download economic data for Dow-Jones Industrial Stock Price Index for United States (M1109BUSM293NNBR) from Dec 1914 to Dec 1968 about stock market, industry, price index, indexes, price, and USA.

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.

Graph and download economic data for Dow Jones Industrial Average (DJIA) from 2015-06-22 to 2025-06-20 about stock market, average, industry, and USA.

AMEX, NYSE, and NASDAQ stocks histories

Update every Satur... Sun... I mean Friday... >_< sometime during the weekend. I lied, I've been too busy the past few months and haven't updated in forever until today (2020.6.14) - Last scrape 2020.06.12 Friday evening (p.s. Download shows 3GB unzipped, zipped file is ~600MB)

Full history of stock symbols:

• Unzip fh_< version_date >.zip
• Each stock symbol has a .csv file under full_history/
  • i.e. AMD.csv
• Columns in .csv
  • date - year-month-day, 2018-08-08
  • volume - int, volume of the day
  • open - float, opening price of the day
  • close - float, closing price of the day
  • high - float, highest price of the day
  • low - float, lowest price of the day
  • adjclose - float, adjusted closing price of the day

Other files:

• all_symbols.txt - All the stock symbols with history
• excluded_symbols.txt - All the ones that I couldn't retrieve data for
• NASDAQ.txt - NASDAQ listing
• NYSE.txt - NYSE listing
• AMEX.txt - AMEX listing

Disclaimer

This dataset contains almost all the stocks listed on these exchanges as of the date shown in the file name. Some of the symbols cannot be found on Yahoo Finance, which I plan on using CNN Money to scrape. There are other symbols that have different classes that require some modification before I can make them queryable... I have yet to decide on the best course of action. If you want to know what these excluded symbols are, see excluded_symbols.txt.

Note: there used to be some tickers missing because of poor connection, that's been solved now.

I've also been asked why I don't put everything into one table, and here's my rationale (copy/pasted from my email):

It is possible and I've debated this before, but I've decided to go with individual files for quite a number of reasons, and I highly recommend you consider these before combining them: 1) I don't need to load everything into memory or search for the right rows if I only want to work with particular sets, 2) easier and faster to manipulate (append, remove, or whatever) when all the data of a ticker is in the same place, 3) I don't need to repeat ticker names for each row just to know which row belongs to which ticker, 4) reduce risk, latency, and waits during parallel processing of different ticker data, 5) in case of any unforeseen bad writes or termination, this way reduces the chances of affecting the entire dataset and allows for restart anytime without the need to keep backup things up every 5 minutes. I get all these benefits only at the cost of slightly larger compressed file and a few more lines of code. To me it's worth it, but I can understand if you are frustrated, but it is possible to concatenate everything.

Github - for you to DIY:

https://github.com/qks1lver/redtide

Data source

Listing files (i.e. NYSE.txt) are from http://eoddata.com/symbols.aspx

Daily historical data compiled from Yahoo Finance

Need someone to talk to?

If you have questions, e-mail me: jiunyyen@gmail.com

Happy mining!

Download Historical NASDAQ 100 Futures Data. CQG daily, 1 minute, tick, and level 1 data from 1899.

Download real-time and historical stock price data, including all buy and sell orders at every price level. Get each trade tick-by-tick and order queue composition at all prices. Access high-fidelity US equities stock market data using our Python, Rust, and C++ APIs. Providing full order book depth (MBO), OHLC aggregates, and more.

Graph and download economic data for Index of Common Stock Prices, New York Stock Exchange for United States (M11007USM322NNBR) from Jan 1902 to May 1923 about New York, stock market, indexes, and USA.

The latest closing stock price for Tesla as of June 17, 2025 is 316.39. An investor who bought $1,000 worth of Tesla stock at the IPO in 2010 would have $197,650 today, roughly 198 times their original investment - a 42.30% compound annual growth rate over 15 years. The all-time high Tesla stock closing price was 479.86 on December 17, 2024. The Tesla 52-week high stock price is 488.54, which is 54.4% above the current share price. The Tesla 52-week low stock price is 179.66, which is 43.2% below the current share price. The average Tesla stock price for the last 52 weeks is 291.40. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

Tracking United HealthCare Stock Performance Since IPO

Dataset Description

This dataset provides historical stock data for UnitedHealth Group (UHG), one of the largest healthcare and insurance companies in the world. It covers stock prices, market capitalization, and trading volumes from the company's IPO to the present. As a Fortune 500 company with a significant market presence, analyzing UHG's stock performance can provide valuable insights into healthcare market trends, investment opportunities, and economic indicators.

Dataset Features

• Date – The trading date for the stock data.
• Open Price – Stock price at market open.
• Close Price – Stock price at market close.
• High – Highest stock price during the trading day.
• Low – Lowest stock price during the trading day.
• Volume – The number of shares traded on that day.
• Market Cap – The total market capitalization of UnitedHealth Group.

Dataset Distribution

• Data Volume: Number of records depends on trading days from IPO to present.
• Format: CSV, Excel, or other structured data formats.
• Update Frequency: Weekly.

Usage

This dataset is useful for:

• Stock Market Analysis – Analyzing historical stock price trends.
• Financial Forecasting – Predicting future stock price movements using machine learning.
• Investment Research – Assessing UnitedHealth Group’s stock as part of a portfolio.
• Market Trends – Understanding broader trends in the healthcare insurance sector.

Coverage

• Geographic Coverage: United States (NYSE).
• Time Range: From IPO to present.
• Economic Indicators: Healthcare sector, insurance market trends.

License

CC0 (Public Domain) – This dataset is freely available for public and commercial use.

Who Can Use This Dataset?

• Investors & Traders – To analyze market trends and make informed decisions.
• Economists & Researchers – To study healthcare market impacts.
• Data Scientists – To develop predictive stock models.

Graph and download economic data for CBOE Volatility Index: VIX (VIXCLS) from 1990-01-02 to 2025-06-23 about VIX, volatility, stock market, and USA.

Download Historical NASDAQ 100 (Globex) Futures Data. CQG daily, 1 minute, tick, and level 1 data from 1899.