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.

The Nasdaq stock exchange has seen significant fluctuations in its listed companies over recent years. As of December 2024, the exchange boasted a total of ***** listed companies, with ***** domestic and *** international firms. This diverse mix of listings reflects the Nasdaq's global appeal and its role as a major player in the world of stock exchanges.

Graph and download economic data for Number of Listed Companies for United States (DDOM01USA644NWDB) from 1975 to 2019 about companies, stock market, and USA.

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

List of companies in the NASDAQ exchanges.

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

The file used in this repository:

Notes:

...

Based on the total number of companies listed, the Japan Exchange Group was the largest stock exchange operator in the world as of Janaury 2025, with 3,968 companies listed. Of these, only six were foreign companies, with the remaining being domestic. The stock exchange with the highest number of international companies at this time was the U.S. Nasdaq, with 871. However, despite only having the seventh-highest number of companies, the New York Stock Exchange has the highest market capitalization of any stock exchange operator.

Content

Top Companies of NASDAQ 100 in 2022

Here are the top companies on the NASDAQ 100 index in 2022. NASDAQ 100 is one of the most prominent large-cap growth indices in the world.

Many companies listed in the NASDAQ 100 operate in the tech sector. That is why many investors who are focused investing in tech stocks also invest in NASDAQ index to grow their funds

What is NASDAQ 100?

NASDAQ 100 is a stock market index composed of the 100 largest and most actively traded companies in the United States of America in the non- financial sector and are segmented under technology, retail, industrial, biotechnology, health care, telecom, transportation, media and services sectors.

Acknowledgement

Data collected from Yahoo Finance.

The dataset contains a total of 25,161 rows, each row representing the stock market data for a specific company on a given date. The information collected through web scraping from www.nasdaq.com includes the stock prices and trading volumes for the companies listed, such as Apple, Starbucks, Microsoft, Cisco Systems, Qualcomm, Meta, Amazon.com, Tesla, Advanced Micro Devices, and Netflix.

Data Analysis Tasks:

1) Exploratory Data Analysis (EDA): Analyze the distribution of stock prices and volumes for each company over time. Visualize trends, seasonality, and patterns in the stock market data using line charts, bar plots, and heatmaps.

2)Correlation Analysis: Investigate the correlations between the closing prices of different companies to identify potential relationships. Calculate correlation coefficients and visualize correlation matrices.

3)Top Performers Identification: Identify the top-performing companies based on their stock price growth and trading volumes over a specific time period.

4)Market Sentiment Analysis: Perform sentiment analysis using Natural Language Processing (NLP) techniques on news headlines related to each company. Determine whether positive or negative news impacts the stock prices and volumes.

5)Volatility Analysis: Calculate the volatility of each company's stock prices using metrics like Standard Deviation or Bollinger Bands. Analyze how volatile stocks are in comparison to others.

Machine Learning Tasks:

1)Stock Price Prediction: Use time-series forecasting models like ARIMA, SARIMA, or Prophet to predict future stock prices for a particular company. Evaluate the models' performance using metrics like Mean Squared Error (MSE) or Root Mean Squared Error (RMSE).

2)Classification of Stock Movements: Create a binary classification model to predict whether a stock will rise or fall on the next trading day. Utilize features like historical price changes, volumes, and technical indicators for the predictions. Implement classifiers such as Logistic Regression, Random Forest, or Support Vector Machines (SVM).

3)Clustering Analysis: Cluster companies based on their historical stock performance using unsupervised learning algorithms like K-means clustering. Explore if companies with similar stock price patterns belong to specific industry sectors.

4)Anomaly Detection: Detect anomalies in stock prices or trading volumes that deviate significantly from the historical trends. Use techniques like Isolation Forest or One-Class SVM for anomaly detection.

5)Reinforcement Learning for Portfolio Optimization: Formulate the stock market data as a reinforcement learning problem to optimize a portfolio's performance. Apply algorithms like Q-Learning or Deep Q-Networks (DQN) to learn the optimal trading strategy.

The dataset provided on Kaggle, titled "Stock Market Stars: Historical Data of Top 10 Companies," is intended for learning purposes only. The data has been gathered from public sources, specifically from web scraping www.nasdaq.com, and is presented in good faith to facilitate educational and research endeavors related to stock market analysis and data science.

It is essential to acknowledge that while we have taken reasonable measures to ensure the accuracy and reliability of the data, we do not guarantee its completeness or correctness. The information provided in this dataset may contain errors, inaccuracies, or omissions. Users are advised to use this dataset at their own risk and are responsible for verifying the data's integrity for their specific applications.

This dataset is not intended for any commercial or legal use, and any reliance on the data for financial or investment decisions is not recommended. We disclaim any responsibility or liability for any damages, losses, or consequences arising from the use of this dataset.

By accessing and utilizing this dataset on Kaggle, you agree to abide by these terms and conditions and understand that it is solely intended for educational and research purposes.

Please note that the dataset's contents, including the stock market data and company names, are subject to copyright and other proprietary rights of the respective sources. Users are advised to adhere to all applicable laws and regulations related to data usage, intellectual property, and any other relevant legal obligations.

In summary, this dataset is provided "as is" for learning purposes, without any warranties or guarantees, and users should exercise due diligence and judgment when using the data for any purpose.

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

The number of domestic companies listed on the New York Stock Exchange (NYSE) saw some fluctuations between 2018 and 2024. Considering domestic companies only, the NYSE recorded its peak in 2020, with ***** listed companies. Combining both domestic and international companies, as of December 2024, the NYSE had a total of ***** listed companies.

United States US: Number of Listed Domestic Companies: Total data was reported at 4,336.000 Unit in 2017. This records an increase from the previous number of 4,331.000 Unit for 2016. United States US: Number of Listed Domestic Companies: Total data is updated yearly, averaging 5,930.000 Unit from Dec 1980 (Median) to 2017, with 38 observations. The data reached an all-time high of 8,090.000 Unit in 1996 and a record low of 4,102.000 Unit in 2012. United States US: Number of Listed Domestic Companies: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. Listed domestic companies, including foreign companies which are exclusively listed, are those which have shares listed on an exchange at the end of the year. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status, are excluded. A company with several classes of shares is counted once. Only companies admitted to listing on the exchange are included.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Canada: Number of companies listed on the stock exchange: The latest value from 2024 is 4226 companies, a decline from 4312 companies in 2023. In comparison, the world average is 666 companies, based on data from 68 countries. Historically, the average for Canada from 1975 to 2024 is 2499 companies. The minimum value, 1124 companies, was reached in 1980 while the maximum of 4312 companies was recorded in 2023.

Stock Data of Top USA Companies: Apple, Tesla, Amazon

👨‍💻 Author: Azhar Saleem

"https://github.com/azharsaleem18" target="_blank"> https://img.shields.io/badge/GitHub-Profile-blue?style=for-the-badge&logo=github" alt="GitHub Profile"> "https://www.kaggle.com/azharsaleem" target="_blank"> https://img.shields.io/badge/Kaggle-Profile-blue?style=for-the-badge&logo=kaggle" alt="Kaggle Profile"> "https://www.linkedin.com/in/azhar-saleem/" target="_blank"> https://img.shields.io/badge/LinkedIn-Profile-blue?style=for-the-badge&logo=linkedin" alt="LinkedIn Profile">
"https://www.youtube.com/@AzharSaleem19" target="_blank"> https://img.shields.io/badge/YouTube-Profile-red?style=for-the-badge&logo=youtube" alt="YouTube Profile"> "https://www.facebook.com/azhar.saleem1472/" target="_blank"> https://img.shields.io/badge/Facebook-Profile-blue?style=for-the-badge&logo=facebook" alt="Facebook Profile"> "https://www.tiktok.com/@azhar_saleem18" target="_blank"> https://img.shields.io/badge/TikTok-Profile-blue?style=for-the-badge&logo=tiktok" alt="TikTok Profile">
"https://twitter.com/azhar_saleem18" target="_blank"> https://img.shields.io/badge/Twitter-Profile-blue?style=for-the-badge&logo=twitter" alt="Twitter Profile"> "https://www.instagram.com/azhar_saleem18/" target="_blank"> https://img.shields.io/badge/Instagram-Profile-blue?style=for-the-badge&logo=instagram" alt="Instagram Profile"> "mailto:azharsaleem6@gmail.com"> https://img.shields.io/badge/Email-Contact%20Me-red?style=for-the-badge&logo=gmail" alt="Email Contact">

Dataset Description

This dataset provides daily stock data for some of the top companies in the USA stock market, including major players like Apple, Microsoft, Amazon, Tesla, and others. The data is collected from Yahoo Finance, covering each company’s historical data from its starting date until today. This comprehensive dataset enables in-depth analysis of key financial indicators and stock trends for each company, making it valuable for multiple applications.

Column Descriptions

The dataset contains the following columns, consistent across all companies:

• Date: The date of the stock data entry.
• Open: The stock's opening price for the day.
• High: The highest price reached during the trading day.
• Low: The lowest price during the trading day.
• Close: The stock’s closing price for the day.
• Volume: The total number of shares traded on that day.
• Dividends: Any dividends paid out on that day.
• Stock Splits: Records stock split events, if any, on that day.

Potential Use Cases

1. Machine Learning & Deep Learning:

   • Stock Price Prediction: Use historical prices to train models for forecasting future stock prices.
   • Sentiment Analysis and Price Correlation: Combine with external sentiment data to predict price movements based on market sentiment.
   • Anomaly Detection: Detect unusual price patterns or volume spikes using classification algorithms.

2. Data Science:

   • Trend Analysis: Identify long-term trends for each company or compare trends between companies.
   • Volatility Analysis: Calculate volatility to assess risk and return patterns over time.
   • Correlation Analysis: Compare stock performance across companies to study market relationships.

3. Data Analysis:

   • Historical Performance: Review historical data to understand growth trends, market impact of stock splits, and dividends.
   • Seasonal Patterns: Analyze data for seasonal trends or recurring patterns across years.
   • Investment Strategy Backtesting: Test various investment strategies based on historical data to assess potential profitability.

4. Financial Research:

   • Economic Impact Studies: Investigate how major events affected stock prices across top companies.
   • Sector-Specific Analysis: Identify performance differences across sectors, such as tech, healthcare, and retail.

This dataset is a powerful tool for analysts, researchers, and financial enthusiasts, offering versatility across multiple domains from stock analysis to algorithmic trading models.

Stock Market Analysis of Nasdaq 100 Stock from it's Founding / Listing Years which is 2001 to 2022

Data Dictionary

About Nasdaq 100 Stock

The Nasdaq-100 is a stock market index made up of 102 equity securities issued by 101 of the largest non-financial companies listed on the Nasdaq stock exchange. It is a modified capitalization-weighted index. The stocks' weights in the index are based on their market capitalizations, with certain rules capping the influence of the largest components. It is limited to companies from a single exchange, and it does not have any financial companies. The financial companies are in a separate index, the NASDAQ Financial-100.

More - Find More Exciting🙀 Datasets Here - An Upvote👍 A Dayᕙ(`▿´)ᕗ , Keeps Aman Hurray Hurray..... ٩(˘◡˘)۶Hehe

Based in Toronto, the TMX Canada was the largest stock exchange in the Americas as of December 2024 in terms of companies listed, with *****. The B3 - Brasil Bolsa Balcao was the largest in South America, with *** companies. Stock exchange size The number of companies is a straightforward way to measure the size of a stock exchange, but there are others. For example, market capitalization, or market cap, refers to the number of shares available on the exchange multiplied by the price per share. This paints a picture of the financial size of the exchange. Another metric is the measure of capital raised, which gives an idea of the profitability of the exchange for the companies listed. Why measure stock exchanges? A stock exchange is essentially a place where people can buy shares in a company. In principle, one can go online and buy from any of the exchanges in this statistic. However, companies choose where to offer their stock for a variety of reasons. These initial public offerings (IPOs) take place in the countries chosen by the company as the place in which that company can best earn money. This affects the inflow of money into the market, and a vibrant exchange will help established firms as well. On the supply side, an economy can profit from the securities industry as well. For these reasons and others, analysts pay close attention to the size of exchanges.

Graph and download economic data for Number of Listed Companies for France (DDOM01FRA644NWDB) from 1975 to 2018 about companies, France, and stock market.

The Nasdaq 100 Index tracks the largest domestic and international non-financial companies listed on the Nasdaq Stock Exchange. This statistic shows the leading 20 companies on the Nasdaq 100 Index by market capitalization. As of January 2025, the American technology company ***** ranked first, with a market capitalization of over ***** trillion euros. This was followed by ******, with a market capitalization amounting to *** trillion euros.

Content

This dataset provides the latest Nasdaq stock ticker information for all companies listed on Nasdaq in 2025. It includes key financial and industry-specific attributes, making it a valuable resource for investors, analysts, and researchers.

The dataset contains 6,975 unique stock tickers, representing companies across various sectors, market capitalizations, and industries. The data is available in multiple formats to suit different needs, whether for stock screening, financial modeling, or market research.

Columns:

Name – Full name of the company Symbol – Stock ticker symbol Sector – General sector classification Industry – Specific industry category Market Cap – Market capitalization (in USD) Country – Country where the company is headquartered Date – The date the data was last updated

Context

Predicting the stock market is one of the most commonly performed projects when someone is learning about ML and Data Science. After all, who wouldn't want to delegate the task of picking stocks to a model and reap the rewards for themselves? However, one of the most difficult and tedious steps to predict what stocks to invest in is actually gathering the data to use. There are so many options and it is important to get sufficient information for each. But, what if you can skip this step and just download a dataset that has all that information easily available for you? Look no further as this is the answer to this problem.

Content

This dataset contains information of 4447 stocks traded under Nasdaq across various exchanges. There is a file that contains information for all 4447 stocks but also has several null fields, which is why I labeled it as full_financial_stocks_raw.csv --it has minimal modifications to the values inside the rows. The second file, dividend_stocks_only.csv, is still a raw-ish style dataset but it only contains stocks that pay out dividends to its shareholders. Interestingly, it seems dividend-paying stocks have more information about them, which explains why this file has significantly fewer rows with null values.

Update: In the next 24 hours, I will be uploading an optimized, feature-engineered dataset that has fewer columns overall and fewer rows with null values. This dataset is intended to be a fully cleaned option to directly feed into ML/DL models.

Acknowledgements

I would like to thank the sources where I obtained my data, which are the FTP Nasdaq Trader website and the Yahoo Finance API.

Inspiration

Analyzing the stock market is one of the most intriguing endeavors I could think of as the ways it can be influenced are so broad and distinct from one another. A news article can influence how investors view a particular company, social media can directly fluctuate a company's share price, and there are numerous calculations and formulas that can show what stocks are worth investing in.

About this Dataset

The dataset consists of companies listed in the S&P500, stock market index that measures the stock performance of 500 large companies listed on stock exchanges in the United State. The S&P500 or SPX is the most commonly followed equity index.

Category

Markets

Keywords

s&p500,nyse,nasdaq,stock market,equities

Row Count

505

Price

$20.00