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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.
The date for every symbol is saved in CSV format with common fields:
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The main stock market index of United States, the US500, fell to 6295 points on July 18, 2025, losing 0.04% from the previous session. Over the past month, the index has climbed 5.47% and is up 14.34% 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.
FinFeedAPI provides equity market data covering over 11,000 symbols, featuring historical T+1 data with an unlimited loopback period. We deliver everything from detailed trade records and multiple levels of order book depth (Level 1-3) to crucial regulatory and system messages.
Our data is engineered for performance, featuring nano-second precision timestamps. This ensures a competitive edge for high-frequency trading by enabling fair, accurate, and auditable transaction sequencing, critical for regulatory compliance. Access comprehensive equity market intelligence directly through our robust API offerings.
Why FinFeedAPI?
Market Coverage & Data Depth: - Historical Data: T+1 data on 11K+ symbols with unlimited historical lookback. - Trade Feeds: Detailed trade records including timestamps, sizes, prices, and conditions (e.g., odd lot, intermarket sweep, extended hours). - Level 1 Quotes: Best bid/ask prices, sizes, and timestamps. - Level 2 Price Book: Market depth with multiple bid/ask prices and aggregate order sizes. - Level 3 Order Book: The complete order book detailing individual orders.
Essential Messages: - Admin Messages: Trading status, official open/close prices, auction states, short sale restrictions, retail liquidity indicators, security directory. - System Events: Exchange-level notifications for key trading session phases.
Precision & Reliability: - Nano-second Timestamps: Ensuring fair, accurate, and auditable transaction sequencing for HFT and compliance. - Institutional Trust: Relied upon by financial institutions for dependable equity market information.
Financial institutions and trading firms rely on FinFeedAPI for mission-critical equity market intelligence. We are committed to delivering clean, precise, and comprehensive data when it matters most. If you require dependable and granular stock market data, FinFeedAPI provides the actionable insights you need.
We offer historical price data for equity indexes, ETFs and individual stocks in a Open/High/Low/Close (OHLC) format and can add almost any other required metric. We cover all major markets and many minor markets. Available for one-time purchase or with regular updates. Real-time/near-time (usually anything quicker than a 15min delay) requires an additional licence from the respective exchange, anything slower does not.
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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.
Bronze Benefits:
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.
Silver Benefits:
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.
Gold Benefits:
Platinum
Don’t see a package that fits your needs? Our team can design premium custom packages for institutions.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Public Service stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.
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.
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Interactive chart of the Dow Jones Industrial Average (DJIA) stock market index for the last 100 years. 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.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
B3 Historical Quotes
This dataset is a collection of historical quotes from the brazilian stock market(B3). It contains historical quotes from all stocks in the country from Jan/2015 until Oct/2023.
Dataset Details
All the data was retrieved as is from B3 Historical Data and parsed to a csv. The columns are the same as the ones from the original content. If you need more informations about the columns, it can be found in the official b3 documentation.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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 July 18 of 2025.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
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.
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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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.
Fixed full version - https://www.kaggle.com/jacksoncrow/stock-market-dataset
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
This dataset offers both live (delayed) prices and End Of Day time series on equity options
1/ Live (delayed) prices for options on European stocks and indices including:
Reference spot price, bid/ask screen price, fair value price (based on surface calibration), implicit volatility, forward
Greeks : delta, vega
Canari.dev computes AI-generated forecast signals indicating which option is over/underpriced, based on the holders strategy (buy and hold until maturity, 1 hour to 2 days holding horizon...). From these signals is derived a "Canari price" which is also available in this live tables.
Visit our website (canari.dev ) for more details about our forecast signals.
The delay ranges from 15 to 40 minutes depending on underlyings.
2/ Historical time series:
Implied vol
Realized vol
Smile
Forward
See a full API presentation here : https://youtu.be/qitPO-SFmY4 .
These data are also readily accessible in Excel thanks the provided Add-in available on Github: https://github.com/canari-dev/Excel-macro-to-consume-Canari-API
If you need help, contact us at: contact@canari.dev
User Guide: You can get a preview of the API by typing "data.canari.dev" in your web browser. This will show you a free version of this API with limited data.
Here are examples of possible syntaxes:
For live options prices: data.canari.dev/OPT/DAI data.canari.dev/OPT/OESX/0923 The "csv" suffix to get a csv rather than html formating, for example: data.canari.dev/OPT/DB1/1223/csv For historical parameters: Implied vol : data.canari.dev/IV/BMW
data.canari.dev/IV/ALV/1224
data.canari.dev/IV/DTE/1224/csv
Realized vol (intraday, maturity expressed as EWM, span in business days): data.canari.dev/RV/IFX ... Implied dividend flow: data.canari.dev/DIV/IBE ... Smile (vol spread between ATM strike and 90% strike, normalized to 1Y with factor 1/√T): data.canari.dev/SMI/DTE ... Forward: data.canari.dev/FWD/BNP ...
List of available underlyings: Code Name OESX Eurostoxx50 ODAX DAX OSMI SMI (Swiss index) OESB Eurostoxx Banks OVS2 VSTOXX ITK AB Inbev ABBN ABB ASM ASML ADS Adidas AIR Air Liquide EAD Airbus ALV Allianz AXA Axa BAS BASF BBVD BBVA BMW BMW BNP BNP BAY Bayer DBK Deutsche Bank DB1 Deutsche Boerse DPW Deutsche Post DTE Deutsche Telekom EOA E.ON ENL5 Enel INN ING IBE Iberdrola IFX Infineon IES5 Intesa Sanpaolo PPX Kering LOR L Oreal MOH LVMH LIN Linde DAI Mercedes-Benz MUV2 Munich Re NESN Nestle NOVN Novartis PHI1 Philips REP Repsol ROG Roche SAP SAP SNW Sanofi BSD2 Santander SND Schneider SIE Siemens SGE Société Générale SREN Swiss Re TNE5 Telefonica TOTB TotalEnergies UBSN UBS CRI5 Unicredito SQU Vinci VO3 Volkswagen ANN Vonovia ZURN Zurich Insurance Group
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Webster Financial stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
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.
The date for every symbol is saved in CSV format with common fields:
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.