79 datasets found
  1. T

    United States Stock Market Index Data

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +12more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States Stock Market Index Data [Dataset]. https://tradingeconomics.com/united-states/stock-market
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 3, 1928 - Jun 27, 2025
    Area covered
    United States
    Description

    The main stock market index of United States, the US500, rose to 6159 points on June 27, 2025, gaining 0.30% from the previous session. Over the past month, the index has climbed 4.60% and is up 12.80% 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 June of 2025.

  2. b

    Stock Market Dataset

    • brightdata.com
    .json, .csv, .xlsx
    Updated Feb 5, 2023
    + more versions
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    Bright Data (2023). Stock Market Dataset [Dataset]. https://brightdata.com/products/datasets/financial/stock-market
    Explore at:
    .json, .csv, .xlsxAvailable download formats
    Dataset updated
    Feb 5, 2023
    Dataset authored and provided by
    Bright Data
    License

    https://brightdata.com/licensehttps://brightdata.com/license

    Area covered
    Worldwide
    Description

    Use our Stock Market dataset to access comprehensive financial and corporate data, including company profiles, stock prices, market capitalization, revenue, and key performance metrics. This dataset is tailored for financial analysts, investors, and researchers to analyze market trends and evaluate company performance.

    Popular use cases include investment research, competitor benchmarking, and trend forecasting. Leverage this dataset to make informed financial decisions, identify growth opportunities, and gain a deeper understanding of the business landscape. The dataset includes all major data points: company name, company ID, summary, stock ticker, earnings date, closing price, previous close, opening price, and much more.

  3. i

    Dataset for Stock Market Prediction

    • ieee-dataport.org
    Updated Jul 8, 2024
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    Umara Umar (2024). Dataset for Stock Market Prediction [Dataset]. https://ieee-dataport.org/documents/dataset-stock-market-prediction
    Explore at:
    Dataset updated
    Jul 8, 2024
    Authors
    Umara Umar
    License

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

    Description

    Hascol

  4. Stock Market Dataset

    • kaggle.com
    zip
    Updated Apr 2, 2020
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    Oleh Onyshchak (2020). Stock Market Dataset [Dataset]. http://doi.org/10.34740/kaggle/dsv/1054465
    Explore at:
    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.

  5. i

    datasets of stock market indices.

    • ieee-dataport.org
    Updated Apr 7, 2024
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    Enrique Gonzalez Nunez (2024). datasets of stock market indices. [Dataset]. https://ieee-dataport.org/documents/datasets-stock-market-indices
    Explore at:
    Dataset updated
    Apr 7, 2024
    Authors
    Enrique Gonzalez Nunez
    License

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

    Description

    DAX

  6. d

    Stock Market Data North America ( End of Day Pricing dataset )

    • datarade.ai
    Updated Aug 24, 2023
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    Techsalerator (2023). Stock Market Data North America ( End of Day Pricing dataset ) [Dataset]. https://datarade.ai/data-products/stock-market-data-north-america-end-of-day-pricing-dataset-techsalerator
    Explore at:
    .json, .csv, .xls, .txtAvailable download formats
    Dataset updated
    Aug 24, 2023
    Dataset authored and provided by
    Techsalerator
    Area covered
    Bermuda, Greenland, Guatemala, United States of America, Honduras, Belize, Panama, El Salvador, Mexico, Saint Pierre and Miquelon, North America
    Description

    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.

  7. h

    stock-market-tweets-data

    • huggingface.co
    Updated Dec 16, 2023
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    Stephan Akkerman (2023). stock-market-tweets-data [Dataset]. https://huggingface.co/datasets/StephanAkkerman/stock-market-tweets-data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 16, 2023
    Authors
    Stephan Akkerman
    License

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

    Description

    Stock Market Tweets Data

      Overview
    

    This dataset is the same as the Stock Market Tweets Data on IEEE by Bruno Taborda.

      Data Description
    

    This dataset contains 943,672 tweets collected between April 9 and July 16, 2020, using the S&P 500 tag (#SPX500), the references to the top 25 companies in the S&P 500 index, and the Bloomberg tag (#stocks).

      Dataset Structure
    

    created_at: The exact time this tweet was posted. text: The text of the tweet, providing… See the full description on the dataset page: https://huggingface.co/datasets/StephanAkkerman/stock-market-tweets-data.

  8. Stock Market Data Europe ( End of Day Pricing dataset )

    • datarade.ai
    Updated Aug 24, 2023
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    Techsalerator (2023). Stock Market Data Europe ( End of Day Pricing dataset ) [Dataset]. https://datarade.ai/data-products/stock-market-data-europe-end-of-day-pricing-dataset-techsalerator
    Explore at:
    .json, .csv, .xls, .txtAvailable download formats
    Dataset updated
    Aug 24, 2023
    Dataset provided by
    Techsalerator LLC
    Authors
    Techsalerator
    Area covered
    Slovenia, Finland, Lithuania, Denmark, Italy, Andorra, Latvia, Croatia, Switzerland, Belgium, Europe
    Description

    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.

  9. T

    China Shanghai Composite Stock Market Index Data

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, China Shanghai Composite Stock Market Index Data [Dataset]. https://tradingeconomics.com/china/stock-market
    Explore at:
    xml, csv, excel, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Dec 19, 1990 - Jun 27, 2025
    Area covered
    China
    Description

    China's main stock market index, the SHANGHAI, fell to 3424 points on June 27, 2025, losing 0.70% from the previous session. Over the past month, the index has climbed 2.52% and is up 15.39% 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 June of 2025.

  10. Stock Market Dataset (NIFTY-500)

    • kaggle.com
    Updated Jun 10, 2023
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    Sourav Banerjee (2023). Stock Market Dataset (NIFTY-500) [Dataset]. https://www.kaggle.com/datasets/iamsouravbanerjee/nifty500-stocks-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    Kaggle
    Authors
    Sourav Banerjee
    Description

    Context

    NIFTY 500 is India’s first broad-based stock market index of the Indian stock market. It contains the top 500 listed companies on the NSE. The NIFTY 500 index represents about 96.1% of free-float market capitalization and 96.5% of the total turnover on the National Stock Exchange (NSE).

    NIFTY 500 companies are disaggregated into 72 industry indices. Industry weights in the index reflect industry weights in the market. For example, if the banking sector has a 5% weight in the universe of stocks traded on the NSE, banking stocks in the index would also have an approximate representation of 5% in the index. NIFTY 500 can be used for a variety of purposes such as benchmarking fund portfolios, launching index funds, ETFs, and other structured products.

    • Other Notable Indices -
      • NIFTY 50: Top 50 listed companies on the NSE. A diversified 50-stock index accounting for 13 sectors of the Indian economy.
      • NIFTY Next 50: Also called NIFTY Juniors. Represents 50 companies from NIFTY 100 after excluding the NIFTY 50 companies.
      • NIFTY 100: Diversified 100 stock index representing major sectors of the economy. NIFTY 100 represents the top 100 companies based on full market capitalization from NIFTY 500.
      • NIFTY 200: Designed to reflect the behavior and performance of large and mid-market capitalization companies.

    Content

    The dataset comprises various parameters and features for each of the NIFTY 500 Stocks, including Company Name, Symbol, Industry, Series, Open, High, Low, Previous Close, Last Traded Price, Change, Percentage Change, Share Volume, Value in Indian Rupee, 52 Week High, 52 Week Low, 365 Day Percentage Change, and 30 Day Percentage Change.

    Dataset Glossary (Column-Wise)

    Company Name: Name of the Company.

    Symbol: A stock symbol is a unique series of letters assigned to a security for trading purposes.

    Industry: Name of the industry to which the stock belongs.

    Series: EQ stands for Equity. In this series intraday trading is possible in addition to delivery and BE stands for Book Entry. Shares falling in the Trade-to-Trade or T-segment are traded in this series and no intraday is allowed. This means trades can only be settled by accepting or giving the delivery of shares.

    Open: It is the price at which the financial security opens in the market when trading begins. It may or may not be different from the previous day's closing price. The security may open at a higher price than the closing price due to excess demand for the security.

    High: It is the highest price at which a stock is traded during the course of the trading day and is typically higher than the closing or equal to the opening price.

    Low: Today's low is a security's intraday low trading price. Today's low is the lowest price at which a stock trades over the course of a trading day.

    Previous Close: The previous close almost always refers to the prior day's final price of a security when the market officially closes for the day. It can apply to a stock, bond, commodity, futures or option co-contract, market index, or any other security.

    Last Traded Price: The last traded price (LTP) usually differs from the closing price of the day. This is because the closing price of the day on NSE is the weighted average price of the last 30 mins of trading. The last traded price of the day is the actual last traded price.

    Change: For a stock or bond quote, change is the difference between the current price and the last trade of the previous day. For interest rates, change is benchmarked against a major market rate (e.g., LIBOR) and may only be updated as infrequently as once a quarter.

    Percentage Change: Take the selling price and subtract the initial purchase price. The result is the gain or loss. Take the gain or loss from the investment and divide it by the original amount or purchase price of the investment. Finally, multiply the result by 100 to arrive at the percentage change in the investment.

    Share Volume: Volume is an indicator that means the total number of shares that have been bought or sold in a specific period of time or during the trading day. It will also involve the buying and selling of every share during a specific time period.

    Value (Indian Rupee): Market value—also known as market cap—is calculated by multiplying a company's outstanding shares by its current market price.

    52-Week High: A 52-week high is the highest share price that a stock has traded at during a passing year. Many market aficionados view the 52-week high as an important factor in determining a stock's current value and predicting future price movement. 52-week High prices are adjusted for Bonus, Split & Rights Corporate actions.

    52-Week Low: A 52-week low is the lowest ...

  11. Nasdaq Stocks Dataset

    • zenodo.org
    • explore.openaire.eu
    csv
    Updated Mar 20, 2022
    + more versions
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    Javier Advani; Javier Advani (2022). Nasdaq Stocks Dataset [Dataset]. http://doi.org/10.5281/zenodo.6368832
    Explore at:
    csvAvailable download formats
    Dataset updated
    Mar 20, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Javier Advani; Javier Advani
    License

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

    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

  12. T

    Sweden Stock Market Index Data

    • tradingeconomics.com
    • ru.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Apr 25, 2024
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    TRADING ECONOMICS (2024). Sweden Stock Market Index Data [Dataset]. https://tradingeconomics.com/sweden/stock-market
    Explore at:
    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    Apr 25, 2024
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Sep 30, 1986 - Jun 27, 2025
    Area covered
    Sweden
    Description

    Sweden's main stock market index, the Stockholm, rose to 2506 points on June 27, 2025, gaining 2.26% from the previous session. Over the past month, the index has declined 0.16% and is down 2.46% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Sweden. Sweden Stock Market Index - values, historical data, forecasts and news - updated on June of 2025.

  13. F

    S&P 500

    • fred.stlouisfed.org
    json
    Updated Jun 26, 2025
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    (2025). S&P 500 [Dataset]. https://fred.stlouisfed.org/series/SP500
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 26, 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.

  14. J

    Information flows and stock market volatility (replication data)

    • journaldata.zbw.eu
    • jda-test.zbw.eu
    txt
    Updated Dec 7, 2022
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    Chew Lian Chua; Sarantis Tsiaplias; Chew Lian Chua; Sarantis Tsiaplias (2022). Information flows and stock market volatility (replication data) [Dataset]. http://doi.org/10.15456/jae.2022327.0707822777
    Explore at:
    txt(1013)Available download formats
    Dataset updated
    Dec 7, 2022
    Dataset provided by
    ZBW - Leibniz Informationszentrum Wirtschaft
    Authors
    Chew Lian Chua; Sarantis Tsiaplias; Chew Lian Chua; Sarantis Tsiaplias
    License

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

    Description

    This study examines how news is distributed across stocks. A model is developed that categorizes a stock's latent news into normal and nonnormal news, and allows both types of news to be filtered through to other stocks. This is achieved by formulating a model that jointly incorporates a multivariate lognormal-Poisson jump process (for nonnormal news) and a multivariate GARCH process (for normal news), in addition to a news (or shock) transmission mechanism that allows the shocks from both processes to impact intertemporally on all stocks in the system. The relationship between news and the expected volatility surface is explored and a unique news impact surface is derived that depends on time, news magnitude, and news type. We find that the effect of nonnormal news on volatility expectations typically builds up before dissipating, with the news transmission mechanism effectively crowding-out normal news and crowding-in nonnormal news. Moreover, in contrast to the standard approach for measuring leverage effects using asymmetric generalized autoregressive conditional heteroskedasticity models, we find that leverage effects stem predominantly from nonnormal news. Finally, we find that the capacity to identify positively or negatively correlated stock returns is ambiguous in the short term, and depends heavily on the behavior of the nonnormal news component.

  15. Stock Market Performance and Corporate Board

    • kaggle.com
    Updated Jan 12, 2023
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    The Devastator (2023). Stock Market Performance and Corporate Board [Dataset]. https://www.kaggle.com/datasets/thedevastator/stock-market-performance-and-corporate-board-mem/suggestions
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 12, 2023
    Dataset provided by
    Kaggle
    Authors
    The Devastator
    Description

    Stock Market Performance and Corporate Board Member Profiles

    Analyzing the Influences of Leadership on Stock Market Performance

    By Jon Loyens [source]

    About this dataset

    This powerful dataset brings together publically-available information from leading stock markets with extensive details about corporate board members. For each company, discover not only their board composition and background, but also current market dynamics, trends and rule changes affecting them. Whether you're a teacher looking to add more detail to a class presentation or an investor seeking a competitive edge in the market - this dataset provides comprehensive insights into the world of stocks and those that play an influential role on its direction. Unprecedented access awaits as you explore hypothetical investments and strategies or actual risks associated with established entities today

    More Datasets

    For more datasets, click here.

    Featured Notebooks

    • 🚨 Your notebook can be here! 🚨!

    How to use the dataset

    Using this dataset, you can gain a better understanding of the relationship between corporate board members and stock market performance. You can analyze the data to determine the average performance of board members at different companies and compare it to the overall performance of other stocks. In addition, you can look into correlations between individual stocks, various industries, and different groups of companies with similar board membership profiles. This dataset provides an overview of all major stocks across multiple industries with detailed insights on each stock's current and past market performance as well as corporate boards

    Research Ideas

    • Analyzing the performance of individual board members in relation to their company’s stock market performance.
    • Determining if certain board members are better at making decisions that benefit the company’s stock market position across all companies they have a stake in.
    • Identifying correlations between trends in different companies' stocks and external factors such as the influence of particular board members or other events associated with that company's sectors or markets

    Acknowledgements

    If you use this dataset in your research, please credit the original authors. Data Source

    License

    See the dataset description for more information.

    Columns

    File: boardmembers.csv | Column name | Description | |:--------------------|:-----------------------------------| | BoardMemberName | Name of the board member. (String) | | CompanyName | Name of the company. (String) | | Source | Source of the data. (String) |

    Acknowledgements

    If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Jon Loyens.

  16. End-of-Day Pricing Market Data Syria Techsalerator

    • kaggle.com
    Updated Aug 24, 2023
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    Techsalerator (2023). End-of-Day Pricing Market Data Syria Techsalerator [Dataset]. https://www.kaggle.com/datasets/techsalerator/end-of-day-pricing-market-data-syria-techsalerator
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 24, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Techsalerator
    Area covered
    Syria
    Description

    Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 30 companies listed on the Damascus Securities Exchange (XDSE) in Syria. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

    Top 5 used data fields in the End-of-Day Pricing Dataset for Syria:

    1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

    2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

    3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

    4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

    5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

    Top 5 financial instruments with End-of-Day Pricing Data in Syria:

    Damascus Securities Exchange (DSE): The primary stock exchange in Syria, tracking the performance of domestic companies listed on the exchange. It provides insights into the Syrian equity market.

    Syrian Pound (SYP): The official currency of Syria, used for transactions and trade within the country. The Syrian Pound has faced significant challenges due to the ongoing conflict and economic instability in the country.

    Central Bank of Syria (CBS): The central bank responsible for monetary policy, currency issuance, and regulation of the financial sector in Syria. It plays a crucial role in managing the country's economic challenges.

    Syrian Petroleum Company (SPC): A state-owned company responsible for the exploration, production, and export of oil and natural gas. Energy resources are important for Syria's economy, and SPC is a key player in the sector.

    Commercial Bank of Syria: One of the major state-owned banks in Syria, providing various financial services to individuals and businesses. Despite challenges, the banking sector remains a vital part of the Syrian economy.

    If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Syria, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

    Data fields included:

    Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

    Q&A:

    1. How much does the End-of-Day Pricing Data cost in Syria ?

    The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

    1. How complete is the End-of-Day Pricing Data coverage in Syria?

    Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Syria exchanges.

    1. How does Techsalerator collect this data?

    Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

    1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

    Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

    1. How do I pay for this dataset?

    Techsalerator accepts various payment methods, including credit cards, direct transfers, ACH, and wi...

  17. M

    S&P 500 - 100 Year Historical Chart

    • macrotrends.net
    csv
    Updated Jun 30, 2025
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    MACROTRENDS (2025). S&P 500 - 100 Year Historical Chart [Dataset]. https://www.macrotrends.net/2324/sp-500-historical-chart-data
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

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

    Time period covered
    1915 - 2025
    Area covered
    United States
    Description

    Interactive chart of the S&P 500 stock market index since 1927. 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.

  18. T

    United Kingdom Stock Market Index (GB100) Data

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 27, 2025
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    TRADING ECONOMICS (2025). United Kingdom Stock Market Index (GB100) Data [Dataset]. https://tradingeconomics.com/united-kingdom/stock-market
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 3, 1984 - Jun 26, 2025
    Area covered
    United Kingdom
    Description

    United Kingdom's main stock market index, the GB100, rose to 8736 points on June 26, 2025, gaining 0.19% from the previous session. Over the past month, the index has declined 0.48%, though it remains 6.80% higher than a year ago, 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 June of 2025.

  19. M

    Dow Jones - 10 Year Daily Chart

    • macrotrends.net
    csv
    Updated Jun 30, 2025
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    MACROTRENDS (2025). Dow Jones - 10 Year Daily Chart [Dataset]. https://www.macrotrends.net/1358/dow-jones-industrial-average-last-10-years
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

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

    Time period covered
    1915 - 2025
    Area covered
    United States
    Description

    Interactive chart illustrating the performance of the Dow Jones Industrial Average (DJIA) market index over the last ten years. Each point of the stock market graph is represented by the daily closing price for the DJIA. Historical data can be downloaded via the red button on the upper left corner of the chart.

  20. Stock market statistics, Canada and United States, Bank of Canada

    • open.canada.ca
    • www150.statcan.gc.ca
    • +3more
    csv, html, xml
    Updated Jan 17, 2023
    + more versions
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    Statistics Canada (2023). Stock market statistics, Canada and United States, Bank of Canada [Dataset]. https://open.canada.ca/data/en/dataset/e037b4dd-4c13-4cc2-b8c4-0262083dbbd0
    Explore at:
    csv, xml, htmlAvailable download formats
    Dataset updated
    Jan 17, 2023
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Area covered
    Canada, United States
    Description

    This table contains 14 series, with data starting from 1953 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Stock market statistics (14 items: Toronto Stock Exchange; value of shares traded; United States common stocks; Dow-Jones industrials; high; United States common stocks; Dow-Jones industrials; low; Toronto Stock Exchange; volume of shares traded ...).

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TRADING ECONOMICS, United States Stock Market Index Data [Dataset]. https://tradingeconomics.com/united-states/stock-market

United States Stock Market Index Data

United States Stock Market Index - Historical Dataset (1928-01-03/2025-06-27)

Explore at:
22 scholarly articles cite this dataset (View in Google Scholar)
excel, xml, json, csvAvailable download formats
Dataset authored and provided by
TRADING ECONOMICS
License

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

Time period covered
Jan 3, 1928 - Jun 27, 2025
Area covered
United States
Description

The main stock market index of United States, the US500, rose to 6159 points on June 27, 2025, gaining 0.30% from the previous session. Over the past month, the index has climbed 4.60% and is up 12.80% 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 June of 2025.

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