The main stock market index of United States, the US500, rose to 6375 points on March 30, 2026, gaining 0.09% from the previous session. Over the past month, the index has declined 7.37%, though it remains 13.59% higher than a year ago, 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 March of 2026.

This dataset contains 184,138 daily stock market records for 120 leading US publicly traded companies, spanning 9 major economic sectors. Each record represents one trading day per company and includes essential OHLCV (Open, High, Low, Close, Adjusted Close, Volume) features used extensively in financial analysis, time-series forecasting, quantitative trading, and AI/ML research.

The dataset is clean, complete, and free of missing values, making it ideal for both educational and production-level projects.

🔍 Use cases include:

• 📊 Exploratory Data Analysis (EDA)
• 📈 Time Series Forecasting (ARIMA, LSTM, Prophet)
• 🤖 Machine Learning & Deep Learning models
• 💹 Portfolio analysis & sector comparison
• 🧠 AI-driven financial research and feature engineering

This dataset is especially valuable for multi-stock modeling, sector-wise trend analysis, and cross-company comparisons.

🧩 Column Descriptions (One Line Each)

• Date – Trading date of the stock record.
• Ticker – Stock market ticker symbol (e.g., AAPL, MSFT, TSLA).
• Company_Name – Full registered name of the company.
• Sector – Economic sector the company belongs to (9 total).
• Industry – Specific industry classification of the company.
• Open – Stock price at market opening.
• High – Highest stock price during the trading day.
• Low – Lowest stock price during the trading day.
• Close – Stock price at market close.
• Adj_Close – Closing price adjusted for splits and dividends.
• Volume – Total number of shares traded during the day.

📊 Dataset Summary

• Rows: 184,138
• Columns: 11
• Companies: 120
• Sectors: 9
• Missing Values: None
• Memory Size: ~15.5 MB

Graph and download economic data for Stock Market Total Value Traded to GDP for United States (DDDM02USA156NWDB) from 1975 to 2019 about market cap, stock market, trade, GDP, and USA.

The main stock market index of United States, the US500, rose to 6899 points on February 25, 2026, gaining 0.13% from the previous session. Over the past month, the index has declined 0.73%, though it remains 15.84% higher than a year ago, 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 February of 2026.

The US Stock Market Historical Dataset contains past trading data of major companies listed on prominent American stock exchanges such as the New York Stock Exchange (NYSE) and NASDAQ. This dataset typically includes daily records of stock prices such as Open, High, Low, Close (OHLC) values, trading Volume, and sometimes Adjusted Close prices.

It provides long-term historical data that helps analysts study market trends, price movements, volatility, and investment performance over time. The dataset may cover large-cap companies, including firms listed in the S&P 500, as well as technology-focused stocks from the NASDAQ Composite.

This dataset is widely used for:

• 📈 Financial analysis and forecasting
• 🤖 Machine learning model training
• 📊 Time series analysis
• 💼 Investment strategy development
• 📉 Risk management and portfolio optimization

Researchers, students, and financial professionals use this dataset to understand historical market behavior, compare company performance, and predict future trends based on past patterns. It is a valuable resource for anyone working in finance, data science, or economic research.

The main stock market index of United States, the US500, fell to 6369 points on March 27, 2026, losing 1.67% from the previous session. Over the past month, the index has declined 7.45%, though it remains 14.12% higher than a year ago, 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 March of 2026.

United States US: Stocks Traded: Total Value data was reported at 39,785.881 USD bn in 2017. This records a decrease from the previous number of 42,071.330 USD bn for 2016. United States US: Stocks Traded: Total Value data is updated yearly, averaging 17,934.293 USD bn from Dec 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 47,245.496 USD bn in 2008 and a record low of 1,108.421 USD bn in 1984. United States US: Stocks Traded: Total Value 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. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; 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.

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.

4974 Stock Symbols End of day data. Includes close open high low volume and date. Data was collected from Google finance public data. +—————+——————+ | Table | Size in MB | +—————+——————+ | surf_eod | 1109.00 | +—————+——————+ 1 row in set (0.00 sec) mysql> SELECT COUNT(DISTINCT( ticker )) FROM surf_eod; +—————————————-+ | COUNT(DISTINCT( ticker )) | +—————————————-+ | 4974 | +—————————————-+ 1 row in set (6.31 sec) mysql> describe surf_eod; +————+——————-+—&mdash

In 2025, ** percent of adults in the United States invested in the stock market. This figure has remained steady over the last few years and is still below the levels before the Great Recession, when it peaked in 2007 at ** percent. What is the stock market? The stock market can be defined as a group of stock exchanges where investors can buy shares in a publicly traded company. In more recent years, it is estimated an increasing number of Americans are using neobrokers, making stock trading more accessible to investors. Other investments A significant number of people think stocks and bonds are the safest investments, while others point to real estate, gold, bonds, or a savings account. Since witnessing the significant one-day losses in the stock market during the financial crisis, many investors were turning towards these alternatives in hopes for more stability, particularly for investments with longer maturities. This could explain the decrease in this statistic since 2007. Nevertheless, some speculators enjoy chasing the short-run fluctuations, and others see value in choosing particular stocks.

Graph and download economic data for Index of Preferred Stock Prices, New York Stock Exchange for United States (M11008USM322NNBR) from Jan 1902 to May 1923 about stock market, New York, indexes, and USA.

📌 About This Dataset

This dataset contains daily historical stock market data for three major US companies:

• 🍎 Apple (AAPL) • 🪟 Microsoft (MSFT) • 🚗 Tesla (TSLA)

It includes essential trading features such as:

✔ Open ✔ High ✔ Low ✔ Close ✔ Adjusted Close ✔ Volume

The data is structured in a multi-ticker format, making it perfect for: • 📊 Financial analysis • 🤖 Machine learning • 🔮 Price prediction • 📈 Portfolio research • 🧠 Time series forecasting

🧪 Data Description Column Group Description Price Adjusted Close & Close prices Open Opening price of the stock High Highest price of the day Low Lowest price of the day Volume Total number of shares traded Ticker Stock symbol (AAPL, MSFT, TSLA) Date Trading date (YYYY-MM-DD)

Each company has its own values under the same feature category for easy comparison.

stock-market finance time-series tesla apple microsoft machine-learning deep-learning lstm forecasting trading investment kaggle-dataset ai python

Dataset

This dataset was created by Joseph Armstrong

Released under Database: Open Database, Contents: © Original Authors

Contents

📊 Overview

Welcome to the Fortune 90+ US Stock Market Dataset - a comprehensive collection of historical market data covering over 90 major American corporations. This dataset is designed for data scientists, financial analysts, machine learning enthusiasts, and anyone interested in understanding stock market dynamics and building predictive models.

Whether you're exploring market trends, developing trading algorithms, or conducting financial research, this dataset provides the foundation you need to unlock valuable insights from the US stock market.

🎯 What's Inside?

This dataset contains rich historical trading data for 90+ publicly traded US companies spanning multiple sectors and industries. The data includes:

Stock Price Information: Open, High, Low, Close prices for comprehensive price action analysis Trading Volume Data: Daily trading volumes to understand market liquidity and investor interest Market Capitalization: Company valuation metrics over time Temporal Coverage: Multi-year historical data enabling long-term trend analysis Diverse Sectors: Companies from Technology, Finance, Healthcare, Energy, Consumer Goods, and more

Each ticker symbol represents a major American corporation, providing a well-rounded view of the US equity market landscape.

💡 Use Cases & Applications

This dataset is perfect for:

📈 Financial Analysis & Research

• Analyze historical price movements and market trends
• Study sector-specific performance and correlations
• Investigate market volatility and risk metrics
• Conduct fundamental and technical analysis

🤖 Machine Learning & Predictive Modeling

• Build stock price prediction models using various algorithms
• Develop time series forecasting systems (LSTM, ARIMA, Prophet)
• Create classification models for trend direction prediction
• Train ensemble models (Random Forest, XGBoost, Gradient Boosting)

📊 Data Visualization & Insights

• Create interactive dashboards and visual analytics
• Generate candlestick charts and technical indicators
• Visualize market correlations and sector performance
• Build portfolio performance tracking tools

💼 Educational Projects

• Learn data analysis with real-world financial data
• Practice data preprocessing and feature engineering
• Understand stock market mechanics and trading patterns
• Develop algorithmic trading strategies

🔍 Comparative Analysis

• Compare performance across different sectors
• Identify market leaders and underperformers
• Analyze inter-company relationships and dependencies
• Study market reactions to economic events

🛠️ Technical Details

• Format: CSV (Comma-Separated Values)
• Structure: Clean, ready-to-use tabular data
• Quality: Pre-processed and validated for accuracy
• Accessibility: Easy to load with Python (pandas), R, or any data analysis tool

Typical Data Schema:

• Date/Timestamp
• Open Price
• High Price
• Low Price
• Close Price
• Stock Splits Price
• Trading Volume Additional market metrics (if applicable)

🚀 Getting Started

Quick Start with Python:

`import pandas as pd

Load the dataset

df = pd.read_csv('fortune_90_stock_data.csv')

Basic exploration

print(df.head()) print(df.info()) print(df.describe())`

Suggested Libraries:

• Data Analysis: pandas, numpy
• Visualization: matplotlib, seaborn, plotly
• Machine Learning: scikit-learn, TensorFlow, PyTorch
• Financial Analysis: TA-Lib, yfinance, pandas-ta

📚 Who Should Use This Dataset?

✅ Data Scientists looking for real-world financial data for ML projects ✅ Financial Analysts conducting market research and investment analysis ✅ Students & Researchers learning about stock markets and quantitative finance ✅ Developers building fintech applications and trading platforms ✅ Traders exploring algorithmic trading strategies ✅ Portfolio Managers analyzing diversification and risk management

🎓 Learning Opportunities

This dataset enables you to:

• Master time series analysis techniques
• Understand market behavior and economic cycles
• Apply statistical methods to financial data
• Build and evaluate predictive models
• Develop data-driven investment strategies
• Create professional-grade financial visualizations

🌟 Why This Dataset Stands Out

✨ Comprehensive Coverage: 90+ major US corporations across diverse sectors ✨ High Quality: Clean, validated, and ready for immediate analysis ✨ Versatile: Suitable for beginners and advanced practitioners alike ✨ Real-World Data: Actual market data reflecting true market dynamics ✨ Multi-Purpose: Supports academic research, ML projects, and professional analysis

🔑 Keywords for Discovery

Primary Keywords:

stock market data, US stocks, historical stock prices, stock market dataset, NYSE data, NASDAQ data, equity market data, trading data, financial data, stock price pre...

The value of the DJIA index amounted to ********* at the end of February 2026, 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.

Graph and download economic data for Dow Jones Industrial Average (DJIA) from 2016-03-28 to 2026-03-27 about stock market, average, industry, and USA.

As of July 21, 2025, the ****************************** held the largest share of any stock exchange operator of the U.S. equity market, accounting for around ** percent of all equities traded in the country. Following was the ******, then the *************************************, with there then being a large gap back to any other stock market operator. However, the largest portion of equity trading took place through off-exchange transactions.

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

The main stock market index of United States, the US500, rose to 6420 points on March 30, 2026, gaining 0.81% from the previous session. Over the past month, the index has declined 6.70%, though it remains 14.41% higher than a year ago, 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 March of 2026.

As of January 2026, the combined average monthly turnover of the three main U.S. equities market operators - the New York Stock Exchange (NYSE), the Nasdaq, and Chicago Board Options Exchange (CBOE) Global Markets - amounted to around **** trillion U.S. dollars. However, the largest share of total equity trades in the United States was held by off-exchange transactions.