As of April 10, 2025, tech giants Apple, Microsoft, Nvidia, Alphabet (Google), and Amazon dominated the S&P 500 index and were among only eight companies with a market capitalization exceeding *** ******** U.S. dollars in the U.S.

View monthly updates and historical trends for S&P 500 Market Cap. from United States. Source: Standard and Poor's. Track economic data with YCharts analy…

List of companies in the S&P 500 (Standard and Poor’s 500).

The S&P 500 is a free-float, capitalization-weighted index of the top 500 publicly listed stocks in the US (top 500 by market cap). The dataset includes a list of all the stocks contained therein and associated key financials such as price, market capitalization, earnings, price/earnings ratio, price to book etc.

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 provides a fascinating look into the ever-changing landscape of the S&P 500 by tracking the top 30 companies by market capitalization from 2010 to 2024. Explore which giants consistently held their ground, which rising stars broke into the ranks, and which former leaders faded from the top.

With columns for 'Year', 'Ticker', 'Weight', '1Y_P' (1-year historical return), '1Y_F' (1-year forward return), 'Industry', and 'Sector', this dataset is a goldmine for analyzing:

Market Concentration: How has the weight of the top companies changed over time? Sector Shifts: Which sectors have dominated the top ranks, and how has this evolved? Performance of Leaders: How did the top companies perform in the year they were included and the year after? Turnover Analysis: Identify which companies were added and removed from the top 30 each year and investigate potential reasons. Whether you're a seasoned quantitative analyst, a student of market trends, or simply curious about the companies shaping the US economy, this dataset offers a unique perspective on market dynamics and the forces driving the S&P 500.

Potential Use Cases:

Time Series Analysis of Market Cap Concentration. Studying sector rotation and dominance. Backtesting strategies based on top-performing companies. Analyzing the characteristics of companies entering or leaving the top 30. Educational purposes for understanding market structure. Dive in and uncover the stories behind the numbers in the S&P 500's top tier!

With a market capitalization of 3.12 trillion U.S. dollars as of May 2024, Microsoft was the world’s largest company that year. Rounding out the top five were some of the world’s most recognizable brands: Apple, NVIDIA, Google’s parent company Alphabet, and Amazon. Saudi Aramco led the ranking of the world's most profitable companies in 2023, with a pre-tax income of nearly 250 billion U.S. dollars. How are market value and market capitalization determined? Market value and market capitalization are two terms frequently used – and confused - when discussing the profitability and viability of companies. Strictly speaking, market capitalization (or market cap) is the worth of a company based on the total value of all their shares; an important metric when determining the comparative value of companies for trading opportunities. Accordingly, many stock exchanges such as the New York or London Stock Exchange release market capitalization data on their listed companies. On the other hand, market value technically refers to what a company is worth in a much broader context. It is determined by multiple factors, including profitability, corporate debt, and the market environment as a whole. In this sense it aims to estimate the overall value of a company, with share price only being one element. Market value is therefore useful for determining whether a company’s shares are over- or undervalued, and in arriving at a price if the company is to be sold. Such valuations are generally made on a case-by-case basis though, and not regularly reported. For this reason, market capitalization is often reported as market value. What are the top companies in the world? The answer to this question depends on the metric used. Although the largest company by market capitalization, Microsoft's global revenue did not manage to crack the top 20 companies. Rather, American multinational retailer Walmart was ranked as the largest company in the world by revenue. Walmart also had the highest number of employees in the world.

The Standard and Poors (S&P) 500 stock market index, maintained by S&P Dow Jones Indices, comprises 505 common stocks issued by 500 large-cap companies and traded on American stock exchanges, and covers about 80 percent of the American equity market by capitalization. The index is weighted by free-float market capitalization, so more valuable companies account for relatively more of the index.

The Standard & Poor’s (S&P) 500 Index is an index of 500 leading publicly traded companies in the United States. In 2021, the index value closed at ******** points, which was the second highest value on record despite the economic effects of the global coronavirus (COVID-19) pandemic. In 2023, the index values closed at ********, the highest value ever recorded. What is the S&P 500? The S&P 500 was established in 1860 and expanded to its present form of 500 stocks in 1957. It tracks the price of stocks on the major stock exchanges in the United States, distilling their performance down to a single number that investors can use as a snapshot of the economy’s performance at a given moment. This snapshot can be explored further. For example, the index can be examined by industry sector, which gives a more detailed illustration of the economy. Other measures Being a stock market index, the S&P 500 only measures equities performance. In addition to other stock market indices, analysts will look to other indicators such as GDP growth, unemployment rates, and projected inflation. Similarly, since these indicators say something about the economic future, stock market investors will use these indicators to speculate on the stocks in the S&P 500.

Context

The S&P 500,[2] or simply the S&P,[4] is a stock market index that measures the stock performance of 500 large companies listed on stock exchanges in the United States. It is one of the most commonly followed equity indices.[5] The average annual total return and compound annual growth rate of the index, including dividends, since inception in 1926 has been approximately 9.8%, or 6% after inflation; however, there were several years where the index declined over 30%.[6][7] The index has posted annual increases 70% of the time.[5] However, the index has only made new highs on 5% of trading days, meaning that on 95% of trading days, the index has closed below its all-time high.[8]

For a list of the components of the index, see List of S&P 500 companies. The components that have increased their dividends in 25 consecutive years are known as the S&P 500 Dividend Aristocrats.[9]:25

The S&P 500 index is a capitalization-weighted index and the 10 largest companies in the index account for 26% of the market capitalization of the index. The 10 largest companies in the index, in order of weighting, are Apple Inc., Microsoft, Amazon.com, Alphabet Inc., Facebook, Johnson & Johnson, Berkshire Hathaway, Visa Inc., Procter & Gamble and JPMorgan Chase, respectively.[2]

Funds that track the index have been recommended as investments by Warren Buffett, Burton Malkiel, and John C. Bogle for investors with long time horizons.[10]

Although the index includes only companies listed in the United States, companies in the index derive on average only 71% of their revenue in the United States.[11]

The index is one of the factors in computation of the Conference Board Leading Economic Index, used to forecast the direction of the economy.[12]

The index is associated with many ticker symbols, including: ^GSPC,[13] INX,[14] and $SPX, depending on market or website.[15] The index value is updated every 15 seconds, or 1,559 times per trading day, with price updates disseminated by Reuters.[16]

The S&P 500 is maintained by S&P Dow Jones Indices, a joint venture majority-owned by S&P Global and its components are selected by a committee.[17][18]

Content

What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too.

Acknowledgements

We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

View monthly updates and historical trends for S&P 500 Monthly Return. from United States. Source: Standard and Poor's. Track economic data with YCharts a…

📊 About Dataset This dataset provides a comprehensive historical record of the S&P 500's constituent companies and their respective weights, spanning from September 30, 2000, to 2024.

The data is sourced from the annual reports of the SPDR S&P 500 ETF (SPY), the largest and oldest exchange-traded fund that tracks the S&P 500. Because the SPY ETF's investment strategy is to hold all 500 stocks in the index in direct proportion to their index weighting, its holdings report is a precise, real-world snapshot of the S&P 500's composition at that time.

This dataset offers a clean, point-in-time view of the market's structure, allowing for analysis that avoids "survivorship bias" (i.e., analyzing only the companies that are currently in the index). It is a valuable resource for quantitative analysts, financial researchers, and data scientists looking to study the evolution of the U.S. large-cap market.

Each file represents an annual snapshot, typically from the end of the fiscal year (September 30th), and contains a list of all companies held by the ETF and their percentage weight in the portfolio.

💡 Potential Use Cases This historical data is ideal for a wide range of financial analysis, quantitative modeling, and academic research.

Market & Sector Trend Analysis:

Visualize the evolution of the U.S. economy by tracking the rise and fall of sector weights over time. For example, you can map the decline of Industrials and Energy and the dramatic rise of the Information Technology sector since 2000.

Analyze the changing landscape of top-tier companies, observing how giants from 2000 (like GE, Exxon, and Cisco) were replaced by today's tech leaders (like Apple, Microsoft, and Nvidia).

Quantitative Strategy Backtesting:

Build and test investment strategies against a historically accurate benchmark. For example, you could test a "sector rotation" strategy based on economic indicators and see how it would have performed.

Simulate portfolio performance without survivorship bias, leading to more realistic and robust backtest results.

Market Concentration Analysis:

Track the concentration of the index in its top 10 holdings.

Analyze how today's market concentration compares to historical periods like the 2000 dot-com bubble, which can be an indicator of market risk.

Academic & Economic Research:

Study the relationship between sector performance and the business cycle. For instance, do certain sectors (like Consumer Staples) consistently outperform during recessions?

Analyze factor investing (e.g., Value, Growth, Momentum) by applying factor definitions to the index constituents at each point in time.

Portfolio Management & Benchmarking:

Use the historical data as a benchmark to evaluate the performance of an active investment portfolio.

Analyze a portfolio's "active share" and "tracking error" against the S&P 500's actual composition from any given year.

View monthly updates and historical trends for S&P 500. from United States. Source: Standard and Poor's. Track economic data with YCharts analytics.

Graph and download economic data for Stock Market Capitalization to GDP for United States (DDDM01USA156NWDB) from 1975 to 2020 about market cap, stock market, capital, GDP, and USA.

In 2018, the intangible value of all companies on the S&P 500 Index was ***** trillion U.S. dollars. During the same year, the value of tangible assets of the same companies was only **** trillion U.S. dollars.

Prices for United States Stock Market Index (US500) including live quotes, historical charts and news. United States Stock Market Index (US500) was last updated by Trading Economics this December 1 of 2025.

Enterprise value to earnings before interest, taxes, depreciation and amortization (EV/EBITDA) is a key measurement ratio used as a metric of valuing whether a company is under or overvalued as compared to a historical industry average. The S&P 500 (Standard & Poor’s) is an index of the 500 largest U.S. publicly traded companies by market capitalization. In 2023, the consumer staples sector displayed the highest EV/EBITDA multiple with *****.

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...

Context

If you are satisfied in data and code, please upvote :)👍 The investing is necessary for everyone's future. I think that just knowing the meaning of the variables without interpreting this dataset is enough to study. This data is an S&p500 index, taken from yahoo finance. Contains multiple financial statements and represents prices over a period of about 10 years(2010-01-01 - 2022-04-18(version 12)) we can analyze price of stocks by time series with comparing financial statements that it is expected to be good measurement of correlation! Have you fun!🎉

The data format is received as json and can be used as a data frame. The script used can be checked at Github repository and if you want longer time scale data or up-to-date data, please run the script from the link. And also, if you want another list of stock, you should check the link which can analysis like Dow (tickers are 30), nasdaq (ticker are about 3000).

If you interest this data and code, Pleases see notebooks of strategy :)

I'm still learning Python, so if you find messy code execution or have a better way of doing it, let me know!! and Please contact me :) I think it will be a good study.

Content

• In FS_sp500_Value.json It is presented by price like 'Open', 'Close' and so on.

• In FS_sp500_RecentValue.json It is presented by Current price.

• In FS_sp500_stats.json. It is summary statement for each ticker.

• In FS_sp500_addstats.json It is fundamental statement not to be presented in stats.

• In FS_sp500_balsheets.json It is presented in balance sheets.

• In FS_sp500_income.json It is presented in income statements.

• In FS_sp500_flow.json It is presented by cash flow.

All data is presented recently. If you want the statements before, Pleases check and fix below code.

Acknowledgements

I'm studying physics and writing code of python and c++. However I'm not used to it yet and also English :(. Let you know if it is not correctly for code and English :🙏

Inspiration

In interpreting the stock market, there are traditionally low PER and PBR strategies. Prior to this, an ML model using various statements and a price estimation model using time series data have been proposed recently, but we know that they are of little use. This data is highly likely to be used for various analyzes, and it is considered to be basic data for understanding the stock's market. Let's study together and find the best model!

If you are satisfied in data and code, please upvote :)👍

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.

This dataset consists of five CSV files that provide detailed data on a stock portfolio and related market performance over the last 5 years. It includes portfolio positions, stock prices, and major U.S. market indices (NASDAQ, S&P 500, and Dow Jones). The data is essential for conducting portfolio analysis, financial modeling, and performance tracking.

1. Portfolio

This file contains the portfolio composition with details about individual stock positions, including the quantity of shares, sector, and their respective weights in the portfolio. The data also includes the stock's closing price.

• Columns:
  • Ticker: The stock symbol (e.g., AAPL, TSLA)
  • Quantity: The number of shares in the portfolio
  • Sector: The sector the stock belongs to (e.g., Technology, Healthcare)
  • Close: The closing price of the stock
  • Weight: The weight of the stock in the portfolio (as a percentage of total portfolio)

2. Portfolio Prices

This file contains historical pricing data for the stocks in the portfolio. It includes daily open, high, low, close prices, adjusted close prices, returns, and volume of traded stocks.

• Columns:
  • Date: The date of the data point
  • Ticker: The stock symbol
  • Open: The opening price of the stock on that day
  • High: The highest price reached on that day
  • Low: The lowest price reached on that day
  • Close: The closing price of the stock
  • Adjusted: The adjusted closing price after stock splits and dividends
  • Returns: Daily percentage return based on close prices
  • Volume: The volume of shares traded that day

3. NASDAQ

This file contains historical pricing data for the NASDAQ Composite index, providing similar data as in the Portfolio Prices file, but for the NASDAQ market index.

• Columns:
  • Date: The date of the data point
  • Ticker: The stock symbol (for NASDAQ index, this will be "IXIC")
  • Open: The opening price of the index
  • High: The highest value reached on that day
  • Low: The lowest value reached on that day
  • Close: The closing value of the index
  • Adjusted: The adjusted closing value after any corporate actions
  • Returns: Daily percentage return based on close values
  • Volume: The volume of shares traded

4. S&P 500

This file contains similar historical pricing data, but for the S&P 500 index, providing insights into the performance of the top 500 U.S. companies.

• Columns:
  • Date: The date of the data point
  • Ticker: The stock symbol (for S&P 500 index, this will be "SPX")
  • Open: The opening price of the index
  • High: The highest value reached on that day
  • Low: The lowest value reached on that day
  • Close: The closing value of the index
  • Adjusted: The adjusted closing value after any corporate actions
  • Returns: Daily percentage return based on close values
  • Volume: The volume of shares traded

5. Dow Jones

This file contains similar historical pricing data for the Dow Jones Industrial Average, providing insights into one of the most widely followed stock market indices in the world.

• Columns:
  • Date: The date of the data point
  • Ticker: The stock symbol (for Dow Jones index, this will be "DJI")
  • Open: The opening price of the index
  • High: The highest value reached on that day
  • Low: The lowest value reached on that day
  • Close: The closing value of the index
  • Adjusted: The adjusted closing value after any corporate actions
  • Returns: Daily percentage return based on close values
  • Volume: The volume of shares traded

Personal Portfolio Data

This data is received using a custom framework that fetches real-time and historical stock data from Yahoo Finance. It provides the portfolio’s data based on user-specific stock holdings and performance, allowing for personalized analysis. The personal framework ensures the portfolio data is automatically retrieved and updated with the latest stock prices, returns, and performance metrics.

This part of the dataset would typically involve data specific to a particular user’s stock positions, weights, and performance, which can be integrated with the other files for portfolio performance analysis.