The main stock market index of United States, the US500, rose to 6947 points on February 11, 2026, gaining 0.08% from the previous session. Over the past month, the index has declined 0.43%, though it remains 14.79% 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.

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.

Overview

This dataset provides historical daily stock price data for the 20 largest financial companies and major global stock indices. It is designed for financial analysis, market trend exploration, and correlation studies. The dataset includes stock price history for the past 1 year for financial companies and for stock indices.

Contents

The dataset consists of multiple CSV files:
1. Stock data files (stock_JPM.csv, stock_BAC.csv, etc.) – Each file contains daily price data for a specific financial company.
2. indices.csv – A merged dataset containing daily closing prices for major stock indices.

Dataset Structure

1. Stock Data Files (stock_JPM.csv, stock_BAC.csv, etc.)

Each stock file contains the following columns:
- Date – Trading day’s closing date (YYYY-MM-DD format).
- Open – Opening price of the stock.
- High – Highest price during the trading day.
- Low – Lowest price during the trading day.
- Close – Closing price of the stock.
- Volume – Number of shares traded.

Removed Columns:
- Dividends – Removed to focus on price movements.
- Stock Splits – Removed as it does not impact short-term trading analysis.

Each file represents a single company’s daily stock performance over the past 365 days.

2. Stock Indices File (indices.csv)

This file contains historical daily closing prices for major global stock indices over the past six months.

Columns:
- Date – Trading day’s closing date (YYYY-MM-DD format).
- GSPC – S&P 500 Index.
- IXIC – NASDAQ Composite Index.
- DJI – Dow Jones Industrial Average (DJIA).
- RUT – Russell 2000 Index.
- GDAXI – DAX Index (Germany).
- FTSE – FTSE 100 Index (United Kingdom).
- FCHI – CAC 40 Index (France).
- HSI – Hang Seng Index (Hong Kong).
- N225 – Nikkei 225 Index (Japan).
- BSESN – BSE Sensex Index (India).
- BVSP – Bovespa Index (Brazil).

Key Adjustments:
- The ticker for S&P 500 (^GSPC) has been renamed to GSPC to avoid special characters.
- The file does not include separate index files, only the merged dataset.
- Missing values are forward-filled to maintain continuity in time series analysis.

Data Sources & Processing

• Stock and index data were collected and processed using the Yahoo Finance API.
• The dataset was prepared with equity_analysis, a custom module developed for efficient equity data retrieval.
• The data updates cover:
  • Financial companies: Last 365 days of daily price data.
  • Stock indices: Last 180 days of daily closing prices.

Potential Use Cases

This dataset is valuable for:
✅ Stock Market Analysis – Studying price trends, volatility, and historical market behavior.
✅ Financial Modeling – Training machine learning models for market prediction.
✅ Portfolio Optimization – Analyzing the correlation between different financial assets.
✅ Comparing Global Markets – Investigating relationships between US, European, and Asian indices.
✅ Backtesting Trading Strategies – Using historical price data for algorithmic trading strategies.

Technical Details

• File format: CSV (comma-separated values)
• Date format: YYYY-MM-DD
• Data interval: Daily
• Timezone: UTC (without timezone adjustments)
• Size: Varies depending on the number of records

Final Notes

• The dataset is regularly updated with the latest stock and index data.
• It is intended for educational and research purposes only, not for real-time trading decisions.
• Future improvements may include additional financial indicators, sentiment analysis, or alternative data sources.

🚀 Use this dataset to explore market trends, build models, and gain financial insights!

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.

United Kingdom's main stock market index, the GB100, fell to 10354 points on February 10, 2026, losing 0.31% from the previous session. Over the past month, the index has climbed 2.10% and is up 17.96% compared to the same time last year, 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 February of 2026.

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.

France's main stock market index, the FR40, rose to 8339 points on February 9, 2026, gaining 0.78% from the previous session. Over the past month, the index has declined 0.24%, though it remains 4.15% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from France. France Stock Market Index (FR40) - values, historical data, forecasts and news - updated on February of 2026.

Context

Stock market data can be interesting to analyze, strong predictive models can have large financial payoff. The amount of financial data on the web is seemingly endless. A large and well structured dataset on a wide array of companies can be hard to come by. Here I view a dataset with historical stock prices for all companies on the S&P 500 index.

Content

All the files have the following columns:

Date - in format: yy-mm-dd

Open - price of the stock at market open (this is NYSE data so all in USD)

High - highest price reached in the day

Low - lowest price reached in the day

Close - close price

Volume - number of shares traded

Acknowledgements

Thanks to Kaggle, Github, yahoo finance.

Purpose of creating the dataset

This dataset lends itself to a some very interesting visualizations. One can look at simple things like how prices change over time, graph an compare multiple stocks at once, or generate and graph new metrics from the data provided. From these data informative stock stats such as volatility and moving averages can be easily calculated. And people can build quantitative models such as: build portfoio, predict volatility, arbitrage, trading strategies.

Context

This dataset provides comprehensive historical data for the Nifty 50 Index, including daily open, high, low, close prices, and trade volumes. Spanning the period for Year 2024-2025, it captures market trends across India's leading stock index during a time of significant economic shifts, including the global pandemic and post-recovery phases.

The NIFTY 50 is a benchmark Indian stock market index that represents the weighted average of 50 of the largest Indian companies listed on the National Stock Exchange. It is one of the two main stock indices used in India, the other being the BSE SENSEX.

Nifty 50 is owned and managed by NSE Indices (previously known as India Index Services & Products Limited), which is a wholly-owned subsidiary of the NSE Strategic Investment Corporation Limited. NSE Indices had a marketing and licensing agreement with Standard & Poor's for co-branding equity indices until 2013. The Nifty 50 index was launched on 22 April 1996 and is one of the many stock indices of Nifty.

Data can be useful for trend analysis, volatility studies, and investment strategy development for both long-term and short-term market assessments.

The NIFTY 50 index is a free-float market capitalization weighted index. The index was initially calculated on a full market capitalization methodology. On 26 June 2009, the computation was changed to a free-float methodology. The base period for the NIFTY 50 index is 3 November 1995, which marked the completion of one year of operations of the National Stock Exchange Equity Market Segment. The base value of the index has been set at 1000 and a base capital of ₹ 2.06 trillion.

The dataset shows average of Share Price Indices and Market Capitalisation

Note: 1. Market capitalisation data are as at end-December up to 1987-88 and at end-March from 1988-89 onwards. 2. Compilation of RBI index was discontinued by the Reserve Bank of India since 1999-2000. Similarly, the compilation of data on the All-India market capitalisation was discontinued by Bombay Stock Exchange Limited (BSE), since 1999-2000. 3. BSE 100 Index introduced from October 14, 1996 was previously known as BSE National Index. BSE National Index (Base: 1983-84 = 100) comprised 100 stocks listed at five major stock exchanges in India - Mumbai, Calcutta, Delhi, Ahmedabad and Madras, while BSE 100 index into account only the prices of stocks listed at BSE. 4. BSE 100 index has been re-based as 1983-84=58 with effect from June 04, 2012. Since 2009-10, data is based on re-based index value of 58.

Sweden's main stock market index, the Stockholm 30, fell to 3137 points on February 10, 2026, losing 0.00% from the previous session. Over the past month, the index has climbed 5.10% and is up 17.61% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Sweden. Sweden Stock Market Index - values, historical data, forecasts and news - updated on February of 2026.

Graph and download economic data for Index of All Common Stock Prices for United States (M1125BUSM347NNBR) from Jan 1945 to Dec 1968 about stock market, indexes, and USA.

The dataset contains stock market indices and stock prices of companies.

Syria SY: Index: Share Price data was reported at 89.356 2010=100 in Jun 2011. This records a decrease from the previous number of 116.806 2010=100 for Mar 2011. Syria SY: Index: Share Price data is updated quarterly, averaging 100.654 2010=100 from Mar 2010 (Median) to Jun 2011, with 6 observations. The data reached an all-time high of 120.890 2010=100 in Dec 2010 and a record low of 77.802 2010=100 in Mar 2010. Syria SY: Index: Share Price data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Syrian Arab Republic – Table SY.IMF.IFS: Share Price Index: Quarterly.

About:

This dataset encompasses the historical data of major stock indices from around the world, sourced directly from Yahoo Finance. With data reaching back to the early 1920s (where available), it serves as an invaluable repository for academic researchers, financial analysts, and market enthusiasts. Users can delve into trends across decades, evaluate historical market behaviors, or even design and validate predictive financial models.

Photo by Tötös Ádám on Unsplash

Info on CSVs:

1. all_indices_data.csv:

   • Description: A consolidated dataset merging all the stock indices from Yahoo Finance.
   • Columns:
     • date: The date of the data point (formatted as YYYY-MM-DD).
     • open: The opening value of the index on that date.
     • high: The highest value of the index during the trading session.
     • low: The lowest value of the index during the trading session.
     • close: The closing value of the index.
     • volume: The trading volume of the index on that date.
     • ticker: The ticker symbol of the stock index.

2. individual_indices_data/[SYMBOL]_data.csv:

   • Description: Individual datasets for each stock index, where [SYMBOL] denotes the ticker symbol of the respective stock index. Each dataset is curated from Yahoo Finance's historical data archives.
   • Columns:
     • date: The date of the data point (formatted as YYYY-MM-DD).
     • open: The opening value of the index on that date.
     • high: The highest value of the index during the trading session.
     • low: The lowest value of the index during the trading session.
     • close: The closing value of the index.
     • volume: The trading volume of the index on that date.

End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.

This Stock Market Dataset is designed for predictive analysis and machine learning applications in financial markets. It includes 13647 records of simulated stock trading data with features commonly used in stock price forecasting.

🔹 Key Features Date – Trading day timestamps (business days only) Open, High, Low, Close – Simulated stock prices Volume – Trading volume per day RSI (Relative Strength Index) – Measures market momentum MACD (Moving Average Convergence Divergence) – Trend-following momentum indicator Sentiment Score – Simulated market sentiment from financial news & social media Target – Binary label (1: Price goes up, 0: Price goes down) for next-day prediction This dataset is useful for training hybrid deep learning models such as LSTM, CNN, and Attention-based networks for stock market forecasting. It enables financial analysts, traders, and AI researchers to experiment with market trends, technical analysis, and sentiment-based predictions.

Graph and download economic data for Index of Stock Prices (General) for Germany (M1123BDEM334NNBR) from Jan 1924 to Dec 1935 about stock market, Germany, and indexes.

End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.

Stock market index in the USA, September, 2025 The most recent value is 199.97 points as of September 2025, an increase compared to the previous value of 194.61 points. Historically, the average for the USA from January 1960 to September 2025 is 46.08 points. The minimum of 2.98 points was recorded in June 1962, while the maximum of 199.97 points was reached in September 2025. | TheGlobalEconomy.com