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.

This dataset contains the monthly historical data of the S&P 500 index from January 1901 to May 2025, collected from Investing.com. The S&P 500 is a stock market index that tracks the performance of 500 large companies listed on stock exchanges in the United States.

It is widely used as a benchmark for the U.S. equity market, representing over 80% of the total market capitalization. This dataset is suitable for:

• Time-series forecasting
• Economic event impact analysis (e.g., wars, recessions, pandemics)
• Financial visualizations in Tableau or Power BI
• Quantitative finance and portfolio management research

Column Descriptions

Potential Use Cases:

• Visualizing market impact of wars, financial crises, and pandemics
• Analyzing long-term trends in the U.S. equity market
• Forecasting future index levels using machine learning
• Annotating economic history alongside market movements

Citation:

Data source: Investing.com

S&P 500 index data including level, dividend, earnings and P/E ratio on a monthly basis since 1870. The S&P 500 (Standard and Poor's 500) is a free-float, capitalization-weighted index of the top ...

The main stock market index of United States, the US500, fell to 6226 points on July 14, 2025, losing 0.54% from the previous session. Over the past month, the index has climbed 3.20% and is up 10.56% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

Full historical data for the S&P 500 (ticker ^GSPC), sourced from Yahoo Finance (https://finance.yahoo.com/).

Including Open, High, Low and Close prices in USD + daily volumes.

Info about S&P 500: https://en.wikipedia.org/wiki/S%26P_500

The main stock market index of United States, the US500, fell to 6260 points on July 11, 2025, losing 0.33% from the previous session. Over the past month, the index has climbed 3.55% and is up 11.48% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

Browse S&P 500 Index (SPX) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Consolidated last sale, exchange BBO and national BBO across all US equity options exchanges. Includes single name stock options (e.g. TSLA), options on ETFs (e.g. SPY, QQQ), index options (e.g. VIX), and some indices (e.g. SPIKE and VSPKE). This dataset is based on the newer, binary OPRA feed after the migration to SIAC's OPRA Pillar SIP in 2021. OPRA is notable for the size of its data and we recommend users to anticipate several TBs of data per day for the full dataset in its highest granularity (MBP-1).

Origin: Options Price Reporting Authority

Supported data encodings: DBN, JSON, CSV Learn more

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

Resolution: Immediate publication, nanosecond-resolution timestamps

The main stock market index of United States, the US500, fell to 6238 points on July 4, 2025, losing 0.65% from the previous session. Over the past month, the index has climbed 5.04% and is up 12.06% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

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.

Browse S&P 500 MINI SPX OPTIONS INDEX (XSP) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Consolidated last sale, exchange BBO and national BBO across all US equity options exchanges. Includes single name stock options (e.g. TSLA), options on ETFs (e.g. SPY, QQQ), index options (e.g. VIX), and some indices (e.g. SPIKE and VSPKE). This dataset is based on the newer, binary OPRA feed after the migration to SIAC's OPRA Pillar SIP in 2021. OPRA is notable for the size of its data and we recommend users to anticipate several TBs of data per day for the full dataset in its highest granularity (MBP-1).

Origin: Options Price Reporting Authority

Supported data encodings: DBN, JSON, CSV Learn more

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

Resolution: Immediate publication, nanosecond-resolution timestamps

Dataset Card for S&P 500 Dataset

This Dataset was created by combining the daily close prices for each stock in the current (as of 10/29/2022) S&P 500 index dating back to January 1, 1970. This data came from the Kaggle dataset (https://www.kaggle.com/datasets/paultimothymooney/stock-market-data) and was aggregated using PANDAS before being converted to a HuggingFace Dataset.

  Dataset Summary

This dataset has 407 columns specifying dates and associated close prices of… See the full description on the dataset page: https://huggingface.co/datasets/nick-carroll1/sp500.

About this dataset

India's National Stock Exchange (NSE) has a total market capitalization of more than US$3.4 trillion, making it the world's 10th-largest stock exchange as of August 2021, with a trading volume of ₹8,998,811 crore (US$1.2 trillion) and more 2000 total listings.

NSE's flagship index, the NIFTY 50, is a 50 stock index is used extensively by investors in India and around the world as a barometer of the Indian capital market.

This dataset contains data of all company stocks listed in the NSE, allowing anyone to analyze and make educated choices about their investments, while also contributing to their countries economy.

How to use this dataset

• Create a time series regression model to predict NIFTY-50 value and/or stock prices.
• Explore the most the returns, components and volatility of the stocks.
• Identify high and low performance stocks among the list.

Highlighted Notebooks

• Your kernel can be featured here!
• Related Dataset: S&P 500 Stocks - daily updated
• More datasets

Acknowledgements

License

CC0: Public Domain

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Stonks by unknown memer.

Russia's main stock market index, the MOEX, fell to 2642 points on July 11, 2025, losing 3.31% from the previous session. Over the past month, the index has declined 3.94% and is down 11.21% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Russia. Russia Stock Market Index MOEX CFD - values, historical data, forecasts and news - updated on July of 2025.

Browse Weekly - S&P 500 Index (SPXW) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Consolidated last sale, exchange BBO and national BBO across all US equity options exchanges. Includes single name stock options (e.g. TSLA), options on ETFs (e.g. SPY, QQQ), index options (e.g. VIX), and some indices (e.g. SPIKE and VSPKE). This dataset is based on the newer, binary OPRA feed after the migration to SIAC's OPRA Pillar SIP in 2021. OPRA is notable for the size of its data and we recommend users to anticipate several TBs of data per day for the full dataset in its highest granularity (MBP-1).

Origin: Options Price Reporting Authority

Supported data encodings: DBN, JSON, CSV Learn more

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

Resolution: Immediate publication, nanosecond-resolution timestamps

There are a total of 5 datasets.sp500_datasp500_newFeatures_datasp500_lagged_datanasdaq_lagged_datahsi_lagged_dataThe first dataset contains 34 years worth of data from 1990 to 2023 for the stock index S&P500. This dataset has been preprocessed and is used for training and testing. The second dataset transforms the initial dataset with the addition of new features derived from the first dataset. The third dataset is a different transformation of the first dataset where the features are mostly contained of lagged features. The fourth dataset contains 10 years of data for the NASDAQ index from 2014-2023 following the same format of lagged features like the third dataset. The fifth dataset has 10 years of data from 2014-2023 for the HSI stock index. This dataset also follows the same format of features as the third datasetAll five of these datasets were used as implementations for a research to predict tomorrow's closing price based on today's financial features

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...

Graph and download economic data for CBOE Volatility Index: VIX (VIXCLS) from 1990-01-02 to 2025-07-10 about VIX, volatility, stock market, and USA.

Graph and download economic data for Dow Jones Industrial Average (DJIA) from 2015-07-13 to 2025-07-11 about stock market, average, industry, and USA.

Nifty 50 The NIFTY 50 is a diversified 50 stock index accounting for 13 sectors of the economy. It is used for a variety of purposes such as benchmarking fund portfolios, index based derivatives and index funds.

NIFTY 50 is owned and managed by NSE Indices Limited (formerly known as India Index Services & Products Limited) (NSE Indices). NSE Indices is India's specialised company focused upon the index as a core product.

The NIFTY 50 Index represents about 66.8% of the free float market capitalization of the stocks listed on NSE as on March 29, 2019. The total traded value of NIFTY 50 index constituents for the last six months ending March 2019 is approximately 53.4% of the traded value of all stocks on the NSE. Impact cost of the NIFTY 50 for a portfolio size of Rs.50 lakhs is 0.02% for the month March 2019.. NIFTY 50 is ideal for derivatives trading. From June 26, 2009, NIFTY 50 is computed based on free float methodology.

Nifty 100 NIFTY 100 is a diversified 100 stock index representing major sectors of the economy. NIFTY 100 represents top 100 companies based on full market capitalisation from NIFTY 500. This index intends to measure the performance of large market capitalisation companies. The NIFTY 100 tracks the behavior of combined portfolio of two indices viz. NIFTY 50 and NIFTY Next 50

NIFTY 100 is owned and managed by NSE Indices Limited (formerly known as India Index Services & Products Limited) (NSE Indices). NSE Indices is India’s specialized company focused upon the index as a core products.

• The NIFTY 100 Index represents about 76.8% of the free float market capitalization of the stocks listed on NSE as on March 29, 2019. • The total traded value for the last six months ending March 2019 of all index constituents is approximately 66.2% of the traded value of all stocks on the NSE. From June 26, 2009, NIFTY 100 is computed based on free float methodology.

Nifty Microcap 250

The Nifty Microcap 250 index aims to track the performance of microcap stocks listed or permitted to trade on NSE. The index includes the top 250 companies beyond the Nifty 500 index constituents, selected based on their average full market capitalization. A stocks weight is based on its free-float market capitalization.

Highlights:

The index has a base date of April 01, 2005, with a base value of 1000. The index includes the top 250 companies beyond the Nifty 500 index constituents, selected based on their average full market capitalization.

The weight of each stock in the index is based on its free float market capitalization.

A buffer based on full market capitalization is used to reduce portfolio churn.

The index is reviewed semi-annually.

Nifty500 It represents the top 500 companies based on full market capitalisation from the eligible universe. The NIFTY 500 Index represents about 96.1% of the free float market capitalization of the stocks listed on NSE as on March 29, 2019. The total traded value for the last six months ending March 2019, of all Index constituents is approximately 96.5% of the traded value of all stocks on NSE. The NIFTY 500 companies are disaggregated into industry indices viz. NIFTY Industry Indices.

** FMCG** MCGs (Fast Moving Consumer Goods) are those goods and products, which are non-durable, mass consumption products and available off the shelf. The Nifty FMCG Index comprises of maximum of 15 companies who manufacture such products which are listed on the National Stock Exchange (NSE).

Healthcare The Nifty Healthcare Index is designed to reflect the behaviour and performance of the Healthcare companies. The Nifty Healthcare Index comprises of maximum of 20 stocks that are listed on the National Stock Exchange.

Information Technology (IT) Information Technology (IT) industry has played a major role in the Indian economy. In order to have a good benchmark of the Indian IT sector, NSE Indices has developed the Nifty IT sector index. Nifty IT provides investors and market intermediaries with an appropriate benchmark that captures the performance of the IT segment of the market.

Companies in this index are those that have more than 50% of their turnover from IT related activities like IT Infrastructure , IT Education and Software Training , Telecommunication Services and Networking Infrastructure, Software Development, Hardware Manufacturer’s, Vending, Support and Maintenance.

REAL ESTATE Real estate sector in India is witnessing significant growth. Recent dynamics of the market reflected the opportunity of creating wealth across real estate companies, as proven by recent listings of real estate companies resulting into prominent growth in public funds and private equity.

The main growth thrust is coming due to favorable demographics, increasing purchasing power, existence of customer friendly banks & housing finance companies, professional...

Browse SPDR S&P 500 ETF Trust (SPY) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Consolidated last sale, exchange BBO and national BBO across all US equity options exchanges. Includes single name stock options (e.g. TSLA), options on ETFs (e.g. SPY, QQQ), index options (e.g. VIX), and some indices (e.g. SPIKE and VSPKE). This dataset is based on the newer, binary OPRA feed after the migration to SIAC's OPRA Pillar SIP in 2021. OPRA is notable for the size of its data and we recommend users to anticipate several TBs of data per day for the full dataset in its highest granularity (MBP-1).

Origin: Options Price Reporting Authority

Supported data encodings: DBN, JSON, CSV Learn more

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

Resolution: Immediate publication, nanosecond-resolution timestamps