100+ datasets found
  1. US NASDAQ

    • lseg.com
    Updated Nov 25, 2024
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    LSEG (2024). US NASDAQ [Dataset]. https://www.lseg.com/en/data-analytics/financial-data/pricing-and-market-data/equities-market-data/us-nasdaq
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    csv,delimited,gzip,html,json,pcap,pdf,parquet,python,sql,string format,text,user interface,xml,zip archiveAvailable download formats
    Dataset updated
    Nov 25, 2024
    Dataset provided by
    London Stock Exchange Grouphttp://www.londonstockexchangegroup.com/
    Authors
    LSEG
    License

    https://www.lseg.com/en/policies/website-disclaimerhttps://www.lseg.com/en/policies/website-disclaimer

    Description

    Browse LSEG's US NASDAQ market data and find real-time trade and quote information in NASDAQ listed instruments from all regulated US exchanges and venues.

  2. f

    Association between Stock Market Gains and Losses and Google Searches

    • figshare.com
    • datadryad.org
    doc
    Updated Jun 4, 2023
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    Eli Arditi; Eldad Yechiam; Gal Zahavi (2023). Association between Stock Market Gains and Losses and Google Searches [Dataset]. http://doi.org/10.1371/journal.pone.0141354
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    docAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Eli Arditi; Eldad Yechiam; Gal Zahavi
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Experimental studies in the area of Psychology and Behavioral Economics have suggested that people change their search pattern in response to positive and negative events. Using Internet search data provided by Google, we investigated the relationship between stock-specific events and related Google searches. We studied daily data from 13 stocks from the Dow-Jones and NASDAQ100 indices, over a period of 4 trading years. Focusing on periods in which stocks were extensively searched (Intensive Search Periods), we found a correlation between the magnitude of stock returns at the beginning of the period and the volume, peak, and duration of search generated during the period. This relation between magnitudes of stock returns and subsequent searches was considerably magnified in periods following negative stock returns. Yet, we did not find that intensive search periods following losses were associated with more Google searches than periods following gains. Thus, rather than increasing search, losses improved the fit between people’s search behavior and the extent of real-world events triggering the search. The findings demonstrate the robustness of the attentional effect of losses.

  3. NYSE and Nasdaq monthly market cap of listed companies comparison 2018-2025

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). NYSE and Nasdaq monthly market cap of listed companies comparison 2018-2025 [Dataset]. https://www.statista.com/statistics/1277195/nyse-nasdaq-comparison-market-capitalization-listed-companies/
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    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2018 - Jan 2025
    Area covered
    United States
    Description

    As of Janaury 2025, the New York Stock Exchange (NYSE) and the Nasdaq - the two largest stock exchange operators in the United States - held a combined market capitalization for domestic listed companies of over ** trillion U.S. dollars. Both markets were almost evenly sized at this point in time - at approximately ** and ** trillion U.S. dollars, respectively. However, the Nasdaq has grown much quicker than the NYSE since January 2018, when their respective domestic market caps were ** and ** trillion U.S. dollars. Much of this can be attributed to the success of information technology stocks during the global coronavirus (COVID-19) pandemic, as the Nasdaq is the traditional venue for companies operating in the tech sector.

  4. d

    Nasdaq Listings

    • datahub.io
    Updated Sep 2, 2017
    + more versions
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    (2017). Nasdaq Listings [Dataset]. https://datahub.io/core/nasdaq-listings
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    Dataset updated
    Sep 2, 2017
    Description

    List of companies in the NASDAQ exchanges.

    Data and documentation are available on NASDAQ's official webpage. Data is updated regularly on the FTP site.

    The file used in this repository:

    Notes:

    ...

  5. o

    Nasdaq Stocks Dataset

    • explore.openaire.eu
    • zenodo.org
    Updated Mar 17, 2022
    + more versions
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    Javier Advani (2022). Nasdaq Stocks Dataset [Dataset]. http://doi.org/10.5281/zenodo.6368831
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    Dataset updated
    Mar 17, 2022
    Authors
    Javier Advani
    Description

    NASDAQ (National Association of Securities Dealers Automated Quotation) is the world's second largest automated and electronic stock exchange and securities market in the United States, the first being the New York Stock Exchange, with more than 8,000 companies and corporations. It has more trading volume per hour than any other stock exchange in the world. More than 7,000 small and mid-cap stocks are traded on the NASDAQ. It is characterized by comprising high-tech companies in electronics, computers, telecommunications, biotechnology, and many others. This dataset was created as a result of an automatic extraction of open & public data available in nasdaq.com, using web scraping techniques. The only purpose of creating it was for academic reasons https://github.com/jadvani/NasdaqScraper

  6. List of Companies in NASDAQ Exchanges

    • johnsnowlabs.com
    csv
    Updated Jan 20, 2021
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    John Snow Labs (2021). List of Companies in NASDAQ Exchanges [Dataset]. https://www.johnsnowlabs.com/marketplace/list-of-companies-in-nasdaq-exchanges/
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    csvAvailable download formats
    Dataset updated
    Jan 20, 2021
    Dataset authored and provided by
    John Snow Labs
    Area covered
    N/A
    Description

    This dataset contains a detailed information on companies listed in the NASDAQ exchanges. The dataset also includes the market category as well as the financial status of the listed companies.

  7. F

    NASDAQ Composite Index

    • fred.stlouisfed.org
    json
    Updated Jul 30, 2025
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    (2025). NASDAQ Composite Index [Dataset]. https://fred.stlouisfed.org/series/NASDAQCOM
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 30, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Description

    Graph and download economic data for NASDAQ Composite Index (NASDAQCOM) from 1971-02-05 to 2025-07-30 about NASDAQ, composite, stock market, indexes, and USA.

  8. Google Trends History for 4000+ Stocks

    • kaggle.com
    Updated May 26, 2020
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    Miguel Aenlle (2020). Google Trends History for 4000+ Stocks [Dataset]. https://www.kaggle.com/miguelaenlle/google-trends-history-for-4000-stocks/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 26, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Miguel Aenlle
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    Getting Google Trends data for a large number of stocks can be tedious, so I've compiled Google Trends history for 4000+ stocks since 2004 in a quick, easy-to-use format for anyone who needs it.

    Content

    Every column other than "date" represents a ticker and its search volume from a range from 0-100, 0 being the least volume it has ever gotten and 100 being the most volume it has gotten for stock search history.

    Acknowledgements

    Pytrends was used for getting the trends data and yfinance was used for getting stock prices.

    Inspiration

    Can a stock's Google search volume be used to profitably make investment decisions?

  9. Iron Ore Nasdaq

    • indexbox.io
    doc, docx, pdf, xls +1
    Updated Jul 1, 2025
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    IndexBox Inc. (2025). Iron Ore Nasdaq [Dataset]. https://www.indexbox.io/search/iron-ore-nasdaq/
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    pdf, docx, doc, xls, xlsxAvailable download formats
    Dataset updated
    Jul 1, 2025
    Dataset provided by
    IndexBox
    Authors
    IndexBox Inc.
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2012 - Jul 29, 2025
    Area covered
    World
    Variables measured
    Price CIF, Price FOB, Export Value, Import Price, Import Value, Export Prices, Export Volume, Import Volume
    Description

    Explore investment opportunities in the iron ore industry via NASDAQ-listed companies involved in mining, distribution, and technological advancements, as well as ETFs tracking the global mining sector.

  10. f

    Web Search Queries Can Predict Stock Market Volumes

    • figshare.com
    pdf
    Updated Jun 1, 2023
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    Ilaria Bordino; Stefano Battiston; Guido Caldarelli; Matthieu Cristelli; Antti Ukkonen; Ingmar Weber (2023). Web Search Queries Can Predict Stock Market Volumes [Dataset]. http://doi.org/10.1371/journal.pone.0040014
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Ilaria Bordino; Stefano Battiston; Guido Caldarelli; Matthieu Cristelli; Antti Ukkonen; Ingmar Weber
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    We live in a computerized and networked society where many of our actions leave a digital trace and affect other people’s actions. This has lead to the emergence of a new data-driven research field: mathematical methods of computer science, statistical physics and sociometry provide insights on a wide range of disciplines ranging from social science to human mobility. A recent important discovery is that search engine traffic (i.e., the number of requests submitted by users to search engines on the www) can be used to track and, in some cases, to anticipate the dynamics of social phenomena. Successful examples include unemployment levels, car and home sales, and epidemics spreading. Few recent works applied this approach to stock prices and market sentiment. However, it remains unclear if trends in financial markets can be anticipated by the collective wisdom of on-line users on the web. Here we show that daily trading volumes of stocks traded in NASDAQ-100 are correlated with daily volumes of queries related to the same stocks. In particular, query volumes anticipate in many cases peaks of trading by one day or more. Our analysis is carried out on a unique dataset of queries, submitted to an important web search engine, which enable us to investigate also the user behavior. We show that the query volume dynamics emerges from the collective but seemingly uncoordinated activity of many users. These findings contribute to the debate on the identification of early warnings of financial systemic risk, based on the activity of users of the www.

  11. Stock Market Dataset

    • kaggle.com
    zip
    Updated Apr 2, 2020
    + more versions
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    Oleh Onyshchak (2020). Stock Market Dataset [Dataset]. http://doi.org/10.34740/kaggle/dsv/1054465
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    zip(547714524 bytes)Available download formats
    Dataset updated
    Apr 2, 2020
    Authors
    Oleh Onyshchak
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    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.

  12. Average cross-correlation time series for NASDAQ-100 stocks (query: Company...

    • plos.figshare.com
    xls
    Updated Jun 3, 2023
    + more versions
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    Ilaria Bordino; Stefano Battiston; Guido Caldarelli; Matthieu Cristelli; Antti Ukkonen; Ingmar Weber (2023). Average cross-correlation time series for NASDAQ-100 stocks (query: Company name, volumes: searches). [Dataset]. http://doi.org/10.1371/journal.pone.0040014.t005
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ilaria Bordino; Stefano Battiston; Guido Caldarelli; Matthieu Cristelli; Antti Ukkonen; Ingmar Weber
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Correlations are lower than the case in which we consider the queries deriving from the tickers (Table 4).

  13. F

    NASDAQ 100 Index

    • fred.stlouisfed.org
    json
    Updated Jul 30, 2025
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    (2025). NASDAQ 100 Index [Dataset]. https://fred.stlouisfed.org/series/NASDAQ100
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 30, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Description

    Graph and download economic data for NASDAQ 100 Index (NASDAQ100) from 1986-01-02 to 2025-07-30 about NASDAQ, stock market, indexes, and USA.

  14. Top Tech Companies Stock Price

    • kaggle.com
    Updated Nov 24, 2020
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    Tomas Mantero (2020). Top Tech Companies Stock Price [Dataset]. https://www.kaggle.com/datasets/tomasmantero/top-tech-companies-stock-price
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 24, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Tomas Mantero
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    In this dataset you can find the Top 100 companies in the technology sector. You can also find 5 of the most important and used indices in the financial market as well as a list of all the companies in the S&P 500 index and in the technology sector.

    The Global Industry Classification Standard also known as GICS is the primary financial industry standard for defining sector classifications. The Global Industry Classification Standard was developed by index providers MSCI and Standard and Poor’s. Its hierarchy begins with 11 sectors which can be further delineated to 24 industry groups, 69 industries, and 158 sub-industries.

    You can read the definition of each sector here.

    The 11 broad GICS sectors commonly used for sector breakdown reporting include the following: Energy, Materials, Industrials, Consumer Discretionary, Consumer Staples, Health Care, Financials, Information Technology, Telecommunication Services, Utilities and Real Estate.

    In this case we will focuse in the Technology Sector. You can see all the sectors and industry groups here.

    To determine which companies, correspond to the technology sector, we use Yahoo Finance, where we rank the companies according to their “Market Cap”. After having the list of the Top 100 best valued companies in the sector, we proceeded to download the historical data of each of the companies using the NASDAQ website.

    Regarding to the indices, we searched various sources to find out which were the most used and determined that the 5 most frequently used indices are: Dow Jones Industrial Average (DJI), S&P 500 (SPX), NASDAQ Composite (IXIC), Wilshire 5000 Total Market Inde (W5000) and to specifically view the technology sector SPDR Select Sector Fund - Technology (XLK). Historical data for these indices was also obtained from the NASDQ website.

    Content

    In total there are 107 files in csv format. They are composed as follows:

    • 100 files contain the historical data of tech companies.
    • 5 files contain the historical data of the most used indices.
    • 1 file contain the list of all the companies in the S&P 500 index.
    • 1 file contain the list of all the companies in the technology sector.

    Column Description

    Every company and index file has the same structure with the same columns:

    Date: It is the date on which the prices were recorded. High: Is the highest price at which a stock traded during the course of the trading day. Low: Is the lowest price at which a stock traded during the course of the trading day. Open: Is the price at which a stock started trading when the opening bell rang. Close: Is the last price at which a stock trades during a regular trading session. Volume: Is the number of shares that changed hands during a given day. Adj Close: The adjusted closing price factors in corporate actions, such as stock splits, dividends, and rights offerings.

    The two other files have different columns names:

    List of S&P 500 companies

    Symbol: Ticker symbol of the company. Name: Name of the company. Sector: The sector to which the company belongs.

    Technology Sector Companies List

    Symbol: Ticker symbol of the company. Name: Name of the company. Price: Current price at which a stock can be purchased or sold. (11/24/20) Change: Net change is the difference between closing prices from one day to the next. % Change: Is the difference between closing prices from one day to the next in percentage. Volume: Is the number of shares that changed hands during a given day. Avg Vol: Is the daily average of the cumulative trading volume during the last three months. Market Cap (Billions): Is the total value of a company’s shares outstanding at a given moment in time. It is calculated by multiplying the number of shares outstanding by the price of a single share. PE Ratio: Is the ratio of a company's share (stock) price to the company's earnings per share. The ratio is used for valuing companies and to find out whether they are overvalued or undervalued.

    Acknowledgements

    SEC EDGAR | Company Filings NASDAQ | Historical Quotes Yahoo Finance | Technology Sector Wikipedia | List of S&P 500 companies S&P Dow Jones Indices | S&P 500 [S&P Dow Jones Indices | DJI](https://www.spglobal.com/spdji/en/i...

  15. Largest stock exchange operators worldwide 2025, by market capitalization

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Largest stock exchange operators worldwide 2025, by market capitalization [Dataset]. https://www.statista.com/statistics/270126/largest-stock-exchange-operators-by-market-capitalization-of-listed-companies/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jun 2025
    Area covered
    Worldwide
    Description

    The New York Stock Exchange (NYSE) is the largest stock exchange in the world, with an equity market capitalization of almost ** trillion U.S. dollars as of June 2025. The following three exchanges were the NASDAQ, PINK Exchange, and the Frankfurt Exchange. What is a stock exchange? A stock exchange is a marketplace where stockbrokers, traders, buyers, and sellers can trade in equities products. The largest exchanges have thousands of listed companies. These companies sell shares of their business, giving the general public the opportunity to invest in them. The oldest stock exchange worldwide is the Frankfurt Stock Exchange, founded in the late sixteenth century. Other functions of a stock exchange Since these are publicly traded companies, every firm listed on a stock exchange has had an initial public offering (IPO). The largest IPOs can raise billions of dollars in equity for the firm involved. Related to stock exchanges are derivatives exchanges, where stock options, futures contracts, and other derivatives can be traded.

  16. nasdaqadmin@nasdaq.com - Reverse Whois Lookup

    • whoisdatacenter.com
    csv
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    AllHeart Web Inc, nasdaqadmin@nasdaq.com - Reverse Whois Lookup [Dataset]. https://whoisdatacenter.com/email/nasdaqadmin@nasdaq.com/
    Explore at:
    csvAvailable download formats
    Dataset provided by
    AllHeart Web
    Authors
    AllHeart Web Inc
    License

    https://whoisdatacenter.com/terms-of-use/https://whoisdatacenter.com/terms-of-use/

    Time period covered
    Mar 15, 1985 - Jul 17, 2025
    Description

    Explore historical ownership and registration records by performing a reverse Whois lookup for the email address nasdaqadmin@nasdaq.com..

  17. f

    Average cross-correlation functions for the clean NASDAQ-100 stocks (query:...

    • figshare.com
    xls
    Updated Jun 1, 2023
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    Ilaria Bordino; Stefano Battiston; Guido Caldarelli; Matthieu Cristelli; Antti Ukkonen; Ingmar Weber (2023). Average cross-correlation functions for the clean NASDAQ-100 stocks (query: Ticker, volumes: searches). [Dataset]. http://doi.org/10.1371/journal.pone.0040014.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Ilaria Bordino; Stefano Battiston; Guido Caldarelli; Matthieu Cristelli; Antti Ukkonen; Ingmar Weber
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    By clean stocks we mean that we remove those stocks which give rise to spurious queries such as the one containing a common words like LIFE or for instance the stock EBAY. In Supporting Information S1 we report the cross correlation functions of the 87 stocks on which the average is performed.

  18. Denmark Number of Listed Company: OMX Copenhagen Stock Exchange

    • ceicdata.com
    Updated Feb 3, 2018
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    CEICdata.com (2018). Denmark Number of Listed Company: OMX Copenhagen Stock Exchange [Dataset]. https://www.ceicdata.com/en/denmark/nasdaq-copenhagen-number-of-listed-companies
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    Dataset updated
    Feb 3, 2018
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2024 - Dec 1, 2024
    Area covered
    Denmark
    Variables measured
    Number of Listed Companies
    Description

    Number of Listed Company: OMX Copenhagen Stock Exchange data was reported at 119.000 Unit in Mar 2025. This records a decrease from the previous number of 120.000 Unit for Feb 2025. Number of Listed Company: OMX Copenhagen Stock Exchange data is updated monthly, averaging 174.000 Unit from Feb 2000 (Median) to Mar 2025, with 302 observations. The data reached an all-time high of 261.000 Unit in Jun 2000 and a record low of 119.000 Unit in Mar 2025. Number of Listed Company: OMX Copenhagen Stock Exchange data remains active status in CEIC and is reported by Nasdaq Copenhagen. The data is categorized under Global Database’s Denmark – Table DK.Z002: Nasdaq Copenhagen: Number of Listed Companies.

  19. Nasdaq Inc. SWOT and Financial Analysis

    • quaintel.com
    Updated Aug 10, 2023
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    Quaintel Research Solutions (2023). Nasdaq Inc. SWOT and Financial Analysis [Dataset]. https://quaintel.com/store/report/nasdaq-inc-company-profile-swot-pestle-value-chain-analysis
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    Dataset updated
    Aug 10, 2023
    Dataset provided by
    Authors
    Quaintel Research Solutions
    License

    https://quaintel.com/privacy-policyhttps://quaintel.com/privacy-policy

    Area covered
    Global
    Description

    Nasdaq Inc. Company Profile, Opportunities, Challenges and Risk (SWOT, PESTLE and Value Chain); Corporate and ESG Strategies; Competitive Intelligence; Financial KPI’s; Operational KPI’s; Recent Trends: “ Read More

  20. F

    S&P 500

    • fred.stlouisfed.org
    json
    Updated Jul 30, 2025
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    (2025). S&P 500 [Dataset]. https://fred.stlouisfed.org/series/SP500
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 30, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-pre-approvalhttps://fred.stlouisfed.org/legal/#copyright-pre-approval

    Description

    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.

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LSEG (2024). US NASDAQ [Dataset]. https://www.lseg.com/en/data-analytics/financial-data/pricing-and-market-data/equities-market-data/us-nasdaq
Organization logo

US NASDAQ

Explore at:
csv,delimited,gzip,html,json,pcap,pdf,parquet,python,sql,string format,text,user interface,xml,zip archiveAvailable download formats
Dataset updated
Nov 25, 2024
Dataset provided by
London Stock Exchange Grouphttp://www.londonstockexchangegroup.com/
Authors
LSEG
License

https://www.lseg.com/en/policies/website-disclaimerhttps://www.lseg.com/en/policies/website-disclaimer

Description

Browse LSEG's US NASDAQ market data and find real-time trade and quote information in NASDAQ listed instruments from all regulated US exchanges and venues.

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