100+ datasets found
  1. T

    United States Stock Market Index Data

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +10more
    csv, excel, json, xml
    Updated Sep 22, 2025
    + more versions
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    TRADING ECONOMICS (2025). United States Stock Market Index Data [Dataset]. https://tradingeconomics.com/united-states/stock-market
    Explore at:
    excel, xml, json, csvAvailable download formats
    Dataset updated
    Sep 22, 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, 1928 - Sep 22, 2025
    Area covered
    United States
    Description

    The main stock market index of United States, the US500, rose to 6698 points on September 22, 2025, gaining 0.51% from the previous session. Over the past month, the index has climbed 4.02% and is up 17.13% 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 September of 2025.

  2. Weekly development Dow Jones Industrial Average Index 2020-2025

    • statista.com
    Updated Jun 26, 2025
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    Statista (2025). Weekly development Dow Jones Industrial Average Index 2020-2025 [Dataset]. https://www.statista.com/statistics/1104278/weekly-performance-of-djia-index/
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    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 1, 2020 - Mar 2, 2025
    Area covered
    United States
    Description

    The Dow Jones Industrial Average (DJIA) index dropped around ***** points in the four weeks from February 12 to March 11, 2020, but has since recovered and peaked at ********* points as of November 24, 2024. In February 2020 - just prior to the global coronavirus (COVID-19) pandemic, the DJIA index stood at a little over ****** points. U.S. markets suffer as virus spreads The COVID-19 pandemic triggered a turbulent period for stock markets – the S&P 500 and Nasdaq Composite also recorded dramatic drops. At the start of February, some analysts remained optimistic that the outbreak would ease. However, the increased spread of the virus started to hit investor confidence, prompting a record plunge in the stock markets. The Dow dropped by more than ***** points in the week from February 21 to February 28, which was a fall of **** percent – its worst percentage loss in a week since October 2008. Stock markets offer valuable economic insights The Dow Jones Industrial Average is a stock market index that monitors the share prices of the 30 largest companies in the United States. By studying the performance of the listed companies, analysts can gauge the strength of the domestic economy. If investors are confident in a company’s future, they will buy its stocks. The uncertainty of the coronavirus sparked fears of an economic crisis, and many traders decided that investment during the pandemic was too risky.

  3. Monthly development Dow Jones Industrial Average Index 2018-2025

    • statista.com
    Updated Jul 22, 2025
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    Statista (2025). Monthly development Dow Jones Industrial Average Index 2018-2025 [Dataset]. https://www.statista.com/statistics/261690/monthly-performance-of-djia-index/
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    Dataset updated
    Jul 22, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2018 - Jun 2025
    Area covered
    United States
    Description

    The value of the DJIA index amounted to ****** at the end of June 2025, up from ********* at the end of March 2020. Global panic about the coronavirus epidemic caused the drop in March 2020, which was the worst drop since the collapse of Lehman Brothers in 2008. Dow Jones Industrial Average index – additional information The Dow Jones Industrial Average index is a price-weighted average of 30 of the largest American publicly traded companies on New York Stock Exchange and NASDAQ, and includes companies like Goldman Sachs, IBM and Walt Disney. This index is considered to be a barometer of the state of the American economy. DJIA index was created in 1986 by Charles Dow. Along with the NASDAQ 100 and S&P 500 indices, it is amongst the most well-known and used stock indexes in the world. The year that the 2018 financial crisis unfolded was one of the worst years of the Dow. It was also in 2008 that some of the largest ever recorded losses of the Dow Jones Index based on single-day points were registered. On September 29, 2008, for instance, the Dow had a loss of ****** points, one of the largest single-day losses of all times. The best years in the history of the index still are 1915, when the index value increased by ***** percent in one year, and 1933, year when the index registered a growth of ***** percent.

  4. F

    S&P 500

    • fred.stlouisfed.org
    json
    Updated Sep 19, 2025
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    (2025). S&P 500 [Dataset]. https://fred.stlouisfed.org/series/SP500
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 19, 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.

  5. F

    Dow Jones Industrial Average

    • fred.stlouisfed.org
    json
    Updated Sep 19, 2025
    + more versions
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    (2025). Dow Jones Industrial Average [Dataset]. https://fred.stlouisfed.org/series/DJIA
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 19, 2025
    License

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

    Description

    Graph and download economic data for Dow Jones Industrial Average (DJIA) from 2015-09-21 to 2025-09-19 about stock market, average, industry, and USA.

  6. Dow Jones: average and yearly closing prices 1915-2021

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). Dow Jones: average and yearly closing prices 1915-2021 [Dataset]. https://www.statista.com/statistics/1316908/dow-jones-average-and-yearly-closing-prices-historical/
    Explore at:
    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The Dow Jones Industrial Average is (DJIA) is possibly the most well-known and commonly used stock index in the United States. It is a price-weighted index that assesses the stock prices of 30 prominent companies, whose combined prices are then divided by a regularly-updated divisor (0.15199 in February 2021), which gives the index value. The companies included are rotated in and out on a regular basis; as of mid-2022, the longest mainstay on the list is Procter & Gamble, which was added in 1932; whereas Amgen, Salesforce, and Honeywell were all added in 2020. As one of the oldest indices for stock market analysis, the impact of major events, recessions, and economic shocks or booms can be tracked and contextualized over longer periods of time.

    Due to inflation, unadjusted figures appear to be more sporadic in recent years, however the greatest fluctuations came in the earliest years of the index. In the given period, the greatest decline came in the wake of the Wall Street Crash in 1929; by 1932 average values had fallen to just one fifth of their 1929 average, from roughly 314 to 65.

  7. Stock Market Dataset for August 2025

    • kaggle.com
    Updated Aug 7, 2025
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    Kshitij Saini (2025). Stock Market Dataset for August 2025 [Dataset]. https://www.kaggle.com/datasets/kshitijsaini121/stock-market-prediction-for-july-2025-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 7, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Kshitij Saini
    License

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

    Description

    Dataset Overview

    This dataset contains comprehensive stock market data for June 2025, capturing daily trading information across multiple companies and sectors. The dataset represents a substantial collection of market data with detailed financial metrics and trading statistics.

    Basic Dataset Information

    • Time Period: June 1-21, 2025 (21 trading days)
    • Total Records: Approximately 11,600+ entries
    • Companies Covered: 500+ unique stocks
    • Data Type: Daily stock market trading data with fundamental metrics

    Markdown Table Format

    Column NameData TypeDescriptionExample Values
    DateDateTrading date in DD-MM-YYYY format01-06-2025, 02-06-2025
    TickerStringStock ticker symbol (3-4 characters)AAPL, GOOGL, TSLA
    Open PriceFloatOpening price of the stock34.92, 206.5, 125.1

    Dataset Information Table

    Dataset Overview

    AttributeDetails
    Dataset NameStock Market Data - June 2025
    File FormatCSV
    File Size~2.5 MB
    Number of Records11,600+
    Number of Features13
    Time PeriodJune 1-21, 2025

    Data Schema

    Column NameData TypeDescriptionExample Values
    DateDateTrading date in DD-MM-YYYY format01-06-2025, 02-06-2025
    TickerStringStock ticker symbol (3-4 characters)AAPL, GOOGL, TSLA, SLH
    Open PriceFloatOpening price of the stock34.92, 206.5, 125.1
    Close PriceFloatClosing price of the stock34.53, 208.45, 124.03
    High PriceFloatHighest price during the trading day35.22, 210.51, 127.4
    Low PriceFloatLowest price during the trading day34.38, 205.12, 121.77
    Volume TradedIntegerNumber of shares traded2,966,611, 1,658,738
    Market CapFloatMarket capitalization in dollars57,381,363,838.88
    PE RatioFloatPrice-to-Earnings ratio29.63, 13.03, 29.19
    Dividend YieldFloatDividend yield percentage2.85, 2.73, 2.64
    EPSFloatEarnings per Share1.17, 16.0, 4.25
    52 Week HighFloatHighest price in the last 52 weeks39.39, 227.38, 138.35
    52 Week LowFloatLowest price in the last 52 weeks28.44, 136.79, 100.69
    SectorStringIndustry sector classificationIndustrials, Energy, Healthcare

    Market Capitalization Tiers

    • Mega Cap (>$1T): 6 companies (AAPL, MSFT, NVDA, AMZN, GOOGL, META)
    • Large Cap ($200B-$1T): 28 companies
    • Mid Cap ($50B-$200B): 47 companies

    Key Market Characteristics

    Price Volatility by Sector

    • Technology: Higher volatility (±3.5% daily range)
    • Energy: High volatility (±4.0% daily range)
    • Utilities: Lower volatility (±1.5% daily range)
    • Healthcare/Financials: Moderate volatility (±2.5% daily range)

    Trading Volume Patterns

    • Mega Cap: 25M - 90M shares daily
    • Large Cap: 8M - 35M shares daily
    • Mid Cap: 2M - 15M shares daily
    • Small Cap: 500K - 5M shares daily

    Financial Metrics Distribution

    • Average P/E Ratio: 25.9 (market-wide)
    • Average Dividend Yield: 1.25%
    • Price Range: $19 (T) to $3,850 (BKNG)
    • EPS Range: $1.50 to $70.00

    Notable Market Features

    High-Value Stocks

    • BKNG (Booking Holdings): $3,650-$3,850 range
    • AVGO (Broadcom): $1,650-$1,750 range
    • REGN (Regeneron): $1,050-$1,150 range
    • LLY (Eli Lilly): $920-$980 range

    High-Dividend Yielders

    • T (AT&T): 7.1% dividend yield
    • VZ (Verizon): 6.2% dividend yield
    • PFE (Pfizer): 5.8% dividend yield

    Growth & Technology Leaders

    • NOW (ServiceNow): P/E ratio of 85
    • NVDA (NVIDIA): P/E ratio of 45
    • TSLA (Tesla): P/E ratio of 55

    Data Quality & Realism Features

    ✅ Authentic Price Ranges: Based on realistic 2025 market projections ✅ Sector-Appropriate Volatility: Different volatility patterns by industry ✅ Correlated Metrics: P/E ratios, dividend yields, and EPS align with market caps ✅ Realistic Trading Volumes: Volume scaled appropriately to market cap ✅ Temporal Consistency: Logical price progression over 53-day period ✅ Market Cap Accuracy: Daily fluctuations reflect actual price movements

    Intended Use Cases

    • Financial Analysis & Modeling: Portfolio optimization, risk assessment
    • Machine Learning Applications: Predictive modeling, algorithmic trading
    • Educational Purposes: Finance courses, data science training
    • Algorithm Development: Backtesting trading strategies
    • Market Research: Sector analysis, correlation studies
    • Visualization Projects: Interactive dashboards, market trend analysis

    This dataset provides a comprehensive foundation for quantitative finance research, offering both breadth across market sectors and depth in daily trading dynamics while maintaining statistical realism throughout the observation period...

  8. T

    United Kingdom Stock Market Index (GB100) Data

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 23, 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
    Sep 23, 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 - Sep 22, 2025
    Area covered
    United Kingdom
    Description

    United Kingdom's main stock market index, the GB100, rose to 9227 points on September 22, 2025, gaining 0.11% from the previous session. Over the past month, the index has declined 0.42%, though it remains 11.71% 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 September of 2025.

  9. Dow Jones: annual change in closing prices 1915-2021

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). Dow Jones: annual change in closing prices 1915-2021 [Dataset]. https://www.statista.com/statistics/1317023/dow-jones-annual-change-historical/
    Explore at:
    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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.

  10. T

    China Shanghai Composite Stock Market Index Data

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 22, 2025
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    TRADING ECONOMICS (2025). China Shanghai Composite Stock Market Index Data [Dataset]. https://tradingeconomics.com/china/stock-market
    Explore at:
    xml, csv, excel, jsonAvailable download formats
    Dataset updated
    Sep 22, 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
    Dec 19, 1990 - Sep 22, 2025
    Area covered
    China
    Description

    China's main stock market index, the SHANGHAI, rose to 3829 points on September 22, 2025, gaining 0.22% from the previous session. Over the past month, the index has declined 1.42%, though it remains 39.28% higher than a year ago, 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 September of 2025.

  11. T

    Japan Stock Market Index (JP225) Data

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 22, 2025
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    TRADING ECONOMICS (2025). Japan Stock Market Index (JP225) Data [Dataset]. https://tradingeconomics.com/japan/stock-market
    Explore at:
    excel, csv, xml, jsonAvailable download formats
    Dataset updated
    Sep 22, 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 5, 1965 - Sep 22, 2025
    Area covered
    Japan
    Description

    Japan's main stock market index, the JP225, rose to 45481 points on September 22, 2025, gaining 0.97% from the previous session. Over the past month, the index has climbed 6.24% and is up 19.87% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Japan. Japan Stock Market Index (JP225) - values, historical data, forecasts and news - updated on September of 2025.

  12. Weekly development S&P 500 Index 2024

    • statista.com
    Updated Jun 26, 2025
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    Statista (2025). Weekly development S&P 500 Index 2024 [Dataset]. https://www.statista.com/statistics/1104270/weekly-sandp-500-index-performance/
    Explore at:
    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 1, 2020 - Dec 29, 2024
    Area covered
    United States
    Description

    Between March 4 and March 11, 2020, the S&P 500 index declined by ** percent, descending into a bear market. On March 12, 2020, the S&P 500 plunged *** percent, its steepest one-day fall since 1987. The index began to recover at the start of April and reached a peak in December 2021. As of December 29, 2024, the value of the S&P 500 stood at ******** points. Coronavirus sparks stock market chaos Stock markets plunged in the wake of the COVID-19 pandemic, with investors fearing its spread would destroy economic growth. Buoyed by figures that suggested cases were leveling off in China, investors were initially optimistic about the virus being contained. However, confidence in the market started to subside as the number of cases increased worldwide. Investors were deterred from buying stocks, and this was reflected in the markets – the values of the Dow Jones Industrial Average and the Nasdaq Composite also dived during the height of the crisis. What is a bear market? A bear market occurs when the value of a stock market suffers a prolonged decline of more than 20 percent over a period of at least 2 months. The COVID-19 pandemic caused severe concern and sent stock markets on a steep downward spiral. The S&P 500 achieved a record closing high of ***** on February 19, 2020. However, just over 3 weeks later, the market closed on *****, which represented a decline of around ** percent in only 16 sessions.

  13. Largest point gains of the Dow Jones Average 2025

    • statista.com
    Updated Nov 8, 2014
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    Statista (2014). Largest point gains of the Dow Jones Average 2025 [Dataset]. https://www.statista.com/statistics/274196/largest-single-day-gains-of-the-dow-jones-index/
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    Dataset updated
    Nov 8, 2014
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    April 9, 2025, saw the largest one-day gain in the history of the Dow Jones Industrial Average (DJIA), follwing Trump's announcement of 90-day delay in the introduction of tariffs imposed on imports from all countries. The second-largest one-day gain occurred on March 24, 2020, with the index increasing ******** points. This occurred approximately two weeks after the largest one-day point loss occurred on March 9, 2020, which was triggered by the growing panic about the coronavirus outbreak worldwide. Index fluctuations The DJIA is an index of ** large companies traded on the New York Stock Exchange. It is one of the numbers that financial analysts watch closely, using it as a bellwether for the United States economy. Seeing when these large gains occur, as well as the largest one-day point losses, gives insight to why these fluctuations may occur. The gains in 2009 are likely adjustments after major losses during the Financial Crisis, but those in 2018 are probably signs of high market volatility. Other leading financial indicators While the DJIA is closely watched, it only gives insight on the performance of thirty leading U.S. companies. An index like the S&P 500, tracking *** companies, can give a more comprehensive overview of the United States economy. Even so, this only reflects investment. Other parts of the economy, such as consumer spending or unemployment rate are not well reflected in stock market indices.

  14. F

    Index of Common Stock Prices, New York Stock Exchange for United States

    • fred.stlouisfed.org
    json
    Updated Aug 15, 2012
    + more versions
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    (2012). Index of Common Stock Prices, New York Stock Exchange for United States [Dataset]. https://fred.stlouisfed.org/series/M11007USM322NNBR
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Aug 15, 2012
    License

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

    Area covered
    United States
    Description

    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.

  15. Summary statistics of limit hits in the whole period (Panel A), in the...

    • plos.figshare.com
    xls
    Updated Jun 4, 2023
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    Yu-Lei Wan; Wen-Jie Xie; Gao-Feng Gu; Zhi-Qiang Jiang; Wei Chen; Xiong Xiong; Wei Zhang; Wei-Xing Zhou (2023). Summary statistics of limit hits in the whole period (Panel A), in the bullish periods (Panel B), and in the bearish periods (Panel C). [Dataset]. http://doi.org/10.1371/journal.pone.0120312.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Yu-Lei Wan; Wen-Jie Xie; Gao-Feng Gu; Zhi-Qiang Jiang; Wei Chen; Xiong Xiong; Wei Zhang; Wei-Xing Zhou
    License

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

    Description

    N is the total number of trading days with limit hits. ⟨N⟩ is the average number of limit-hitting days for individual stocks. Ncon is the number of limit-hitting days with continued next-day opening prices (up-limit days with the next-day opening prices higher than the closing prices and down-limit days with the next-day opening price lower than the closing prices). Nrev is the number of limit-hitting days with price reversal on the next day. Nopen, Nam, Npm and Nclose are respectively the numbers of days with limit hits occurred in the opening call auction, in the continuous double auction in the morning, in the continuous double auction in the afternoon and at the closure of the trading days. Nclose,con and Nclose,rev are the numbers of trading days that closed at limit prices and the price continued rising or falling on the successive trading days.

  16. AXISBANK

    • kaggle.com
    Updated Jul 4, 2025
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    Pratyush Kumar (2025). AXISBANK [Dataset]. https://www.kaggle.com/datasets/prat2004/axisbank/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 4, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Pratyush Kumar
    License

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

    Description

    AXISBANK OHLCV Data: Multi-Interval Historical Stock Prices (NSE)

    Overview

    This dataset provides comprehensive historical Open, High, Low, Close, and Volume (OHLCV) data for Axis Bank (AXISBANK), a prominent Indian stock listed on the National Stock Exchange (NSE). The data has been consolidated from various time intervals (1-minute, 5-minute, 15-minute, and 1-day), offering a granular yet unified view for diverse analytical needs, from high-frequency trading simulations to long-term trend analysis.

    Data Source

    The raw data was collected programmatically using the Groww API. The specific API endpoint used for fetching charting data is: https://groww.in/v1/api/charting_service/v4/chart/exchange/NSE/segment/CASH. While efforts have been made during data fetching and consolidation to ensure accuracy, please be aware that financial data can sometimes be subject to minor corrections or revisions by data providers.

    Dataset Contents

    This dataset is provided as a single, unified CSV file (e.g., unified_axisbank_ohlcv_data.csv), which has been consolidated from multiple JSON files representing different time intervals (1m, 5m, 15m, 1d).

    The unified CSV file contains the following columns:

    • Symbol: The stock ticker symbol (AXISBANK).
    • Interval: The original time interval of the candle (1m, 5m, 15m, 1d).
    • DateTime: The human-readable timestamp of the candle (derived from Unix Timestamp, e.g., YYYY-MM-DD HH:MM:SS).
    • Open: The opening price of the stock during that interval.
    • High: The highest price reached during that interval.
    • Low: The lowest price reached during that interval.
    • Close: The closing price of the stock during that interval.
    • Volume: The trading volume (number of shares traded) during that interval.
    • Timestamp: The raw Unix timestamp.

    Overall Date Range and Record Count: The exact historical date range and total number of records for the complete dataset depend on the full content and consolidation process of the original JSON files. Your conversion script will provide the precise earliest and latest dates, as well as the total number of records in this unified CSV file. Based on the original file snippets, the data appears to span from at least mid-2022 into mid-2025.

    Potential Use Cases

    This dataset can be highly valuable for various applications in quantitative finance and data science, including: * Algorithmic Trading Strategy Development: Backtesting and optimizing trading strategies across different timeframes for AXISBANK. * Technical Analysis: Generating charts, calculating technical indicators (e.g., Moving Averages, RSI, MACD, Bollinger Bands) specific to AXISBANK. * Machine Learning for Price Prediction: Training models to forecast future stock prices, trends, or volatility for AXISBANK. * Market Trend Analysis: Studying short-term and long-term market behavior, liquidity, and price action of Axis Bank. * Educational Purposes: A clean, multi-interval dataset ideal for learning and practicing data analysis with financial time series.

    Disclaimer

    This dataset is provided for informational and educational purposes only. It should not be considered financial advice, investment recommendations, or a solicitation to buy or sell any securities. Trading and investing in financial markets involve significant risk, and past performance is not indicative of future results. Always conduct your own thorough research and consult with a qualified financial advisor before making any investment decisions. The creators of this dataset are not liable for any losses incurred from its use.

  17. 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/tomasmantero/top-tech-companies-stock-price/metadata
    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...

  18. NYSE and Nasdaq monthly number of listed companies comparison 2018-2024, by...

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). NYSE and Nasdaq monthly number of listed companies comparison 2018-2024, by domicile [Dataset]. https://www.statista.com/statistics/1277216/nyse-nasdaq-comparison-number-listed-companies/
    Explore at:
    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The number of domestic companies listed on the Nasdaq and on the New York Stock Exchange (NYSE) has seen some fluctuations since 2018. As of the end of 2023, the NYSE had a total of ***** listed domestic and international companies, while the figure for the Nasdaq was much higher, standing at *****. Despite this, the NYSE has a higher market capitalization than the Nasdaq. What are the top listed companies? The NYSE has been a home for stable and long-lasting firms, also known as “blue-chip” companies. For example, Berkshire Hathaway, established in 1839, is the largest company traded on the NYSE. On the other hand, the Nasdaq has been known for listing major tech companies. For instance, Apple is the largest company listed on the Nasdaq. As of 2024, both companies were among the biggest companies in the world in terms of market capitalization. Which stock exchange has the most companies worldwide? Although the NYSE and the Nasdaq are the world’s largest two stock market operators by market capitalization, the Japan Exchange Group (JPX) is the biggest stock exchange in the world based on the number of companies. The JPX was created in 2013 through the merger of the Tokyo Stock Exchange and the Osaka Securities Exchange and is also one of the largest stock exchanges in the world based on total market capitalization.

  19. d

    Data from: Value Line Investment Survey

    • search.dataone.org
    • dataone.org
    Updated Sep 25, 2024
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    Value Line Publishing (2024). Value Line Investment Survey [Dataset]. http://doi.org/10.7910/DVN/P0RROU
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    Dataset updated
    Sep 25, 2024
    Dataset provided by
    Harvard Dataverse
    Authors
    Value Line Publishing
    Time period covered
    Jan 4, 1980 - Dec 31, 1989
    Description

    The Value Line Investment Survey is one of the oldest, continuously running investment advisory publications. Since 1955, the Survey has been published in multiple formats including print, loose-leaf, microfilm and microfiche. Data from 1997 to present is now available online. The Survey tracks 1700 stocks across 92 industry groups. It provides reported and projected measures of firm performance, proprietary rankings and analysis for each stock on a quarterly basis. This dataset, a subset of the Survey covering the years 1980-1989 has been digitized from the microfiche collection available at the Dewey Library (FICHE HG 4501.V26). It is only available to MIT students and faculty for academic research. Published weekly, each edition of the Survey has the following three parts: Summary & Index: includes an alphabetical listing of all industries with their relative ranking and the page number for detailed industry analysis. It also includes an alphabetical listing of all stocks in the publication with references to their location in Part 3, Ratings & Reports. Selection & Opinion: contains the latest economic and stock market commentary and advice along with one or more pages of research on interesting stocks or industries, and a variety of pertinent economic and stock market statistics. It also includes three model stock portfolios. Ratings & Reports: This is the core of the Value Line Investment Survey. Preceded by an industry report, each one-page stock report within that industry includes Timeliness, Safety and Technical rankings, 3-to 5-year analyst forecasts for stock prices, income and balance sheet items, up to 17 years of historical data, and Value Line analysts’ commentaries. The report also contains stock price charts, quarterly sales, earnings, and dividend information. Publication Schedule: Each edition of the Survey covers around 130 stocks in seven to eight industries on a preset sequential schedule so that all 1700 stocks are analyzed once every 13 weeks or each quarter. All editions are numbered 1-13 within each quarter. For example, in 1980, reports for Chrysler appear in edition 1 of each quarter on the following dates: January 4, 1980 – page 132 April 4, 1980 – page 133 July 4, 1980 – page 133 October 1, 1980 – page 133 Reports for Coca-Cola were published in edition 10 of each quarter on: March 7, 1980 – page 1514 June 6, 1980 – page 1518 Sept. 5, 1980 – page 1517 Dec. 5, 1980 – page 1548 Any significant news affecting a stock between quarters is covered in the supplementary reports that appear at the end of part 3, Ratings & Reports. File format: Digitized files within this dataset are in PDF format and are arranged by publication date within each compressed annual folder. How to Consult the Value Line Investment Survey: To find reports on a particular stock, consult the alphabetical listing of stocks in the Summary & Index part of the relevant weekly edition. Look for the page number just to the left of the company name and then use the table below to identify the edition where that page number appears. All editions within a given quarter are numbered 1-13 and follow equally sized page ranges for stock reports. The table provides page ranges for stock reports within editions 1-13 of 1980 Q1. It can be used to identify edition and page numbers for any quarter within a given year. Ratings & Reports Edition Pub. Date Pages 1 04-Jan-80 100-242 2 11-Jan-80 250-392 3 18-Jan-80 400-542 4 25-Jan-80 550-692 5 01-Feb-80 700-842 6 08-Feb-80 850-992 7 15-Feb-80 1000-1142 8 22-Feb-80 1150-1292 9 29-Feb-80 1300-1442 10 07-Mar-80 1450-1592 11 14-Mar-80 1600-1742 12 21-Mar-80 1750-1908 13 28-Mar-80 2000-2142 Another way to navigate to the Ratings & Reports part of an edition would be to look around page 50 within the PDF document. Note that the page numbers of the PDF will not match those within the publication.

  20. Microsoft Stocks 1 Year Historical Data

    • kaggle.com
    Updated Aug 4, 2025
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    Imaad Mahmood (2025). Microsoft Stocks 1 Year Historical Data [Dataset]. https://www.kaggle.com/datasets/imaadmahmood/microsoft-stocks-1-year-historical-data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 4, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Imaad Mahmood
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Dataset Description: Microsoft Stock Prices (One Year)

    -This dataset contains daily trading information for Microsoft Corporation (MSFT) stock over a one-year period. Each entry represents a single trading day and includes essential stock market data.

    Columns and Descriptions:

    -**Date:** The trading day in YYYY-MM-DD format.

    -**Open:** Stock price at market open.

    -**High:** Highest stock price during the day.

    -**Low:** Lowest stock price during the day.

    -**Close:** Stock price at market close.

    -**Volume:** Number of shares traded on that day.

    -This dataset is suitable for time series analysis, stock price forecasting, and machine learning projects focused on financial data.

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TRADING ECONOMICS (2025). 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 (1928-01-03/2025-09-22)

Explore at:
19 scholarly articles cite this dataset (View in Google Scholar)
excel, xml, json, csvAvailable download formats
Dataset updated
Sep 22, 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, 1928 - Sep 22, 2025
Area covered
United States
Description

The main stock market index of United States, the US500, rose to 6698 points on September 22, 2025, gaining 0.51% from the previous session. Over the past month, the index has climbed 4.02% and is up 17.13% 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 September of 2025.

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