The main stock market index of United States, the US500, rose to 6818 points on December 2, 2025, gaining 0.08% from the previous session. Over the past month, the index has declined 0.50%, though it remains 12.70% 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 December of 2025.

Graph and download economic data for Dow Jones Industrial Average (DJIA) from 2015-12-02 to 2025-12-01 about stock market, average, industry, and USA.

Context:

The provided dataset is extracted from yahoo finance using pandas and yahoo finance library in python. This deals with stock market index of the world best economies. The code generated data from Jan 01, 2003 to Jun 30, 2023 that’s more than 20 years. There are 18 CSV files, dataset is generated for 16 different stock market indices comprising of 7 different countries. Below is the list of countries along with number of indices extracted through yahoo finance library, while two CSV files deals with annualized return and compound annual growth rate (CAGR) has been computed from the extracted data.

Number of Countries & Index:

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F90ce8a986761636e3edbb49464b304d8%2FNumber%20of%20Index.JPG?generation=1688490342207096&alt=media" alt="">

Content:

Unit of analysis: Stock Market Index Analysis

This dataset is useful for research purposes, particularly for conducting comparative analyses involving capital market performance and could be used along with other economic indicators.

There are 18 distinct CSV files associated with this dataset. First 16 CSV files deals with number of indices and last two CSV file deals with annualized return of each year and CAGR of each index. If data in any column is blank, it portrays that index was launch in later years, for instance: Bse500 (India), this index launch in 2007, so earlier values are blank, similarly China_Top300 index launch in year 2021 so early fields are blank too.

The extraction process involves applying different criteria, like in 16 CSV files all columns are included, Adj Close is used to calculate annualized return. The algorithm extracts data based on index name (code given by the yahoo finance) according start and end date.

Annualized return and CAGR has been calculated and illustrated in below image along with machine readable file (CSV) attached to that.

To extract the data provided in the attachment, various criteria were applied:

1. Content Filtering: The data was filtered based on several attributes, including the index name, start and end date. This filtering process ensured that only relevant data meeting the specified criteria.

2. Collaborative Filtering: Another filtering technique used was collaborative filtering using yahoo finance, which relies on index similarity. This approach involves finding indices that are similar to other index or extended dataset scope to other countries or economies. By leveraging this method, the algorithm identifies and extracts data based on similarities between indices.

In the last two CSV files, one belongs to annualized return, that was calculated based on the Adj close column and new DataFrame created to store its outcome. Below is the image of annualized returns of all index (if unreadable, machine-readable or CSV format is attached with the dataset).

Annualized Return:

As far as annualised rate of return is concerned, most of the time India stock market indices leading, followed by USA, Canada and Japan stock market indices.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F37645bd90623ea79f3708a958013c098%2FAnnualized%20Return.JPG?generation=1688525901452892&alt=media" alt="">

Compound Annual Growth Rate (CAGR):

The best performing index based on compound growth is Sensex (India) that comprises of top 30 companies is 15.60%, followed by Nifty500 (India) that is 11.34% and Nasdaq (USA) all is 10.60%.

The worst performing index is China top300, however this is launch in 2021 (post pandemic), so would not possible to examine at that stage (due to less data availability). Furthermore, UK and Russia indices are also top 5 in the worst order.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F58ae33f60a8800749f802b46ec1e07e7%2FCAGR.JPG?generation=1688490409606631&alt=media" alt="">

Geography: Stock Market Index of the World Top Economies

Time period: Jan 01, 2003 – June 30, 2023

Variables: Stock Market Index Title, Open, High, Low, Close, Adj Close, Volume, Year, Month, Day, Yearly_Return and CAGR

File Type: CSV file

Inspiration:

• Time series prediction model
• Investment opportunities in world best economies
• Comparative Analysis of past data with other stock market indices or other indices

Disclaimer:

This is not a financial advice; due diligence is required in each investment decision.

Overview This dataset contains combined news headlines and stock market data, specifically the Dow Jones Industrial Average (DJIA). It is designed to facilitate the study of the relationship between news sentiment and stock market movements.

Dataset Description The dataset includes the following features:

Date: The date corresponding to the news headlines and DJIA data. Label: A binary label indicating whether the DJIA increased (1) or decreased (0) on that particular date. Top 1 to Top 25: The top 25 news headlines for each date. These columns contain the news headlines that were published on that date. Usage This dataset can be utilized for various analytical and modeling purposes, including but not limited to:

Sentiment Analysis: Develop models to analyze the sentiment of news headlines and correlate them with stock market movements. Stock Market Prediction: Build predictive models to forecast stock market trends based on news headlines. Text Preprocessing Techniques: Implement and evaluate text preprocessing methods such as tokenization, stemming, and lemmatization. Natural Language Processing: Apply NLP techniques to extract meaningful insights from news headlines. Potential Applications Enhancing trading strategies by incorporating news sentiment analysis. Building robust machine learning pipelines for financial forecasting. Studying the impact of news on stock market volatility. Experimenting with various NLP and machine learning techniques for financial data. File information The dataset is provided in CSV format and contains 1990 records and 27 columns.

The main stock market index of United States, the US500, rose to 6849 points on November 28, 2025, gaining 0.54% from the previous session. Over the past month, the index has declined 0.60%, though it remains 13.54% 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 November of 2025.

Dow Jones - Historical chart and current data through 2025.

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 encapsulates a detailed examination of market dynamics over a five-year period, focusing on the fluctuation of prices and trading volumes across a diversified portfolio. It covers various sectors including energy commodities like natural gas and crude oil, metals such as copper, platinum, silver, and gold, cryptocurrencies including Bitcoin and Ethereum, and key stock indices and companies like the S&P 500, Nasdaq 100, Apple, Tesla, Microsoft, Google, Nvidia, Berkshire Hathaway, Netflix, Amazon, and Meta Platforms. This dataset serves as a valuable resource for analyzing trends and patterns in global markets.

Date: The date of the recorded data, formatted as DD-MM-YYYY. Natural_Gas_Price: Price of natural gas in USD per million British thermal units (MMBtu). Natural_Gas_Vol.: Trading volume of natural gas Crude_oil_Price: Price of crude oil in USD per barrel. Crude_oil_Vol.: Trading volume of crude oil Copper_Price: Price of copper in USD per pound. Copper_Vol.: Trading volume of copper Bitcoin_Price: Price of Bitcoin in USD. Bitcoin_Vol.: Trading volume of Bitcoin Platinum_Price: Price of platinum in USD per troy ounce. Platinum_Vol.: Trading volume of platinum Ethereum_Price: Price of Ethereum in USD. Ethereum_Vol.: Trading volume of Ethereum S&P_500_Price: Price index of the S&P 500. Nasdaq_100_Price: Price index of the Nasdaq 100. Nasdaq_100_Vol.: Trading volume for the Nasdaq 100 index Apple_Price: Stock price of Apple Inc. in USD. Apple_Vol.: Trading volume of Apple Inc. stock Tesla_Price: Stock price of Tesla Inc. in USD. Tesla_Vol.: Trading volume of Tesla Inc. stock Microsoft_Price: Stock price of Microsoft Corporation in USD. Microsoft_Vol.: Trading volume of Microsoft Corporation stock Silver_Price: Price of silver in USD per troy ounce. Silver_Vol.: Trading volume of silver Google_Price: Stock price of Alphabet Inc. (Google) in USD. Google_Vol.: Trading volume of Alphabet Inc. stock Nvidia_Price: Stock price of Nvidia Corporation in USD. Nvidia_Vol.: Trading volume of Nvidia Corporation stock Berkshire_Price: Stock price of Berkshire Hathaway Inc. in USD. Berkshire_Vol.: Trading volume of Berkshire Hathaway Inc. stock Netflix_Price: Stock price of Netflix Inc. in USD. Netflix_Vol.: Trading volume of Netflix Inc. stock Amazon_Price: Stock price of Amazon.com Inc. in USD. Amazon_Vol.: Trading volume of Amazon.com Inc. stock Meta_Price: Stock price of Meta Platforms, Inc. (formerly Facebook) in USD. Meta_Vol.: Trading volume of Meta Platforms, Inc. stock Gold_Price: Price of gold in USD per troy ounce. Gold_Vol.: Trading volume of gold

Image attribute : Image by Freepik

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

👨‍💻 Author: Azhar Saleem

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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.

Japan's main stock market index, the JP225, rose to 49553 points on December 2, 2025, gaining 0.51% from the previous session. Over the past month, the index has declined 3.78%, though it remains 26.25% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Japan. Japan Stock Market Index (JP225) - values, historical data, forecasts and news - updated on December of 2025.

The main stock market index of United States, the US500, rose to 6825 points on December 2, 2025, gaining 0.18% from the previous session. Over the past month, the index has declined 0.39%, though it remains 12.82% 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 December of 2025.

Comprehensive 27+ years of daily stock market data for Indian indices (SENSEX & NIFTY 50) and all their constituent companies. This dataset includes OHLCV data along with pre-calculated technical indicators, making it perfect for time series analysis, algorithmic trading strategies, and machine learning applications.

Total Records: 400,000+
Companies: 80 stocks (30 SENSEX + 50 NIFTY 50)
Features: 21 columns per record

Use Cases:

Machine Learning & Prediction:

• Stock price forecasting using LSTM, GRU, or Transformers
• Next-day close price prediction
• Multi-stock portfolio prediction
• Market regime detection (bull/bear markets)

Technical Analysis:

• Backtest trading strategies (RSI, MACD, Moving Average crossovers)
• Identify support/resistance levels
• Bollinger Band squeeze patterns
• Golden Cross / Death Cross detection

Statistical Analysis:

-Correlation analysis between stocks - Volatility clustering analysis - Market crash impact studies (2008 financial crisis, 2020 COVID) - Sectoral performance comparison

Portfolio Optimization:

• Modern Portfolio Theory implementation
• Risk-return optimization
• Diversification analysis
• Sharpe ratio calculations

Education:

• Financial markets course projects
• Time series analysis tutorials
• Data science portfolio projects
• Algorithmic trading education

Company List:

SENSEX 30 Companies:

Adani Enterprises, Asian Paints, Axis Bank, Bajaj Finance, Bajaj Finserv, Bharti Airtel, HDFC Bank, HCL Technologies, Hindustan Unilever, ICICI Bank, IndusInd Bank, Infosys, ITC, Kotak Mahindra Bank, Larsen & Toubro, Mahindra & Mahindra, Maruti Suzuki, Nestle India, NTPC, ONGC, Power Grid Corporation, Reliance Industries, State Bank of India, Sun Pharmaceutical, Tata Consultancy Services, Tata Motors, Tata Steel, Tech Mahindra, Titan Company, UltraTech Cement, Wipro

NIFTY 50 Companies:

All SENSEX 30 companies plus: Adani Ports, Apollo Hospitals, Bajaj Auto, Bharat Petroleum, Britannia Industries, Cipla, Coal India, Divi's Laboratories, Dr. Reddy's Laboratories, Eicher Motors, Grasim Industries, Hero MotoCorp, Hindalco Industries, Hindustan Zinc, JSW Steel, LTIMindtree, Shriram Finance, Tata Consumer Products, Trent

Ticker Conventions: - .BO suffix = Bombay Stock Exchange (BSE) - .NS suffix = National Stock Exchange (NSE)

Citation Policy:

If you use this dataset in your research, please cite:

Indian Stock Market Historical Data - SENSEX & NIFTY 50 (1997-2024)
Kaggle Dataset, November 2024
URL: https://www.kaggle.com/datasets/rockyt07/stock-market-sensex-nifty-all-time-dataset

This dataset contains several daily features of NASDAQ Composite, Dow Jones Industrial Average, and NYSE Composite from 2010 to 2024. It covers features from various categories of technical indicators, futures contracts, price of commodities, important indices of markets around the world, price of major companies in the U.S. market, and treasury bill rates. Sources and thorough description of features have been mentioned in the paper of "CNNpred: CNN-based stock market prediction using a diverse set of variables" published at Expert Systems with Applications. This dataset has been used in "SAMBA: A Graph-Mamba Approach for Stock Price Prediction" published at ICASSP 2025. Link to Code: https://github.com/Ali-Meh619/SAMBA

United Kingdom's main stock market index, the GB100, fell to 9690 points on December 2, 2025, losing 0.13% from the previous session. Over the past month, the index has declined 0.12%, though it remains 15.91% higher than a year ago, 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 December of 2025.

1) Data Introduction • The Stock Market Dataset contains metadata on stocks and ETFs listed on NASDAQ, including attributes such as ticker symbol, company name, market classification, ETF status, start date, and last trading date.

2) Data Utilization (1) Characteristics of the Stock Market Dataset: • Since the dataset includes only static metadata without price data, it is well-suited for preprocessing and classification tasks such as stock filtering, sector labeling, and distinguishing between ETFs and regular stocks.

(2) Applications of the Stock Market Dataset: • Automated sector classification of stocks: This dataset can be used to automatically tag or analyze stocks by sector using text-based industry keywords.

This comprehensive dataset provides historical stock price data spanning various time periods, offering insights into the fluctuations and trends in the stock market over time. With records covering multiple decades, investors, analysts, and researchers can explore the dynamics of different stocks, industries, and market sectors.

The dataset includes essential information such as opening price, closing price, highest and lowest prices, trading volume, and adjusted closing prices. It encompasses a diverse range of stocks, including those from various exchanges and sectors, allowing for extensive analysis and comparison.

Researchers can utilize this dataset to conduct thorough analyses, develop financial models, backtest trading strategies, and gain a deeper understanding of market behavior. Investors can assess the performance of individual stocks or portfolios over extended periods, aiding in informed decision-making and risk management.

Whether you're a seasoned investor seeking historical insights or an analyst exploring market trends, this dataset serves as a valuable resource for studying the complexities of the stock market across different eras.

China's main stock market index, the SHANGHAI, fell to 3898 points on December 2, 2025, losing 0.42% from the previous session. Over the past month, the index has declined 1.98%, though it remains 15.36% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from China. China Shanghai Composite Stock Market Index - values, historical data, forecasts and news - updated on December of 2025.

The main stock market index of United States, the US500, fell to 6812 points on December 2, 2025, losing 0.01% from the previous session. Over the past month, the index has declined 0.58%, though it remains 12.60% 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 December of 2025.

Sweden's main stock market index, the Stockholm 30, fell to 2782 points on December 2, 2025, losing 0.11% from the previous session. Over the past month, the index has climbed 0.95% and is up 8.08% 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 December of 2025.

Poland's main stock market index, the WIG, fell to 110618 points on December 2, 2025, losing 1.16% from the previous session. Over the past month, the index has declined 1.29%, though it remains 36.78% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Poland. Warsaw Stock Exchange WIG Index - values, historical data, forecasts and news - updated on December of 2025.