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.

Use our Stock Market dataset to access comprehensive financial and corporate data, including company profiles, stock prices, market capitalization, revenue, and key performance metrics. This dataset is tailored for financial analysts, investors, and researchers to analyze market trends and evaluate company performance.

Popular use cases include investment research, competitor benchmarking, and trend forecasting. Leverage this dataset to make informed financial decisions, identify growth opportunities, and gain a deeper understanding of the business landscape. The dataset includes all major data points: company name, company ID, summary, stock ticker, earnings date, closing price, previous close, opening price, and much more.

This dataset integrates multiple financial data sources to enable detailed stock market trend analysis and decision-making.

Key Features:

Daily Stock Trading Metrics – Includes open, high, low, close prices, and trading volume.

Macroeconomic Indicators – Covers GDP growth, inflation rates, and interest rates.

Sentiment-Labeled News – Financial news articles with positive, negative, or neutral sentiment tags.

Multisource Integration – Combines structured and unstructured financial data for deeper insights.

Comprehensive Market Coverage – Designed for stock trend analysis, investment strategies, and risk assessment.

Supports Predictive Modeling – Enables better understanding of market dynamics and investor sentiment.

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.

Reddit: /r/stocks

Analyzing User Engagement to Identify Market Trends

By Reddit [source]

About this dataset

This dataset provides a valuable opportunity for researchers to explore the fascinating world of stock exchange markets through the eyes of those participating in discussions on Reddit. We have compiled posts from the subredditstocks subreddit to provide researchers with an invaluable source of information on how stock market trends may be impacted by user sentiment. With detailed data columns such as post titles, scores, id's, URLs, comments counts and created times for each post we are offering a unique vantage point into understanding how stocks market discussions may inform our better understanding of these dynamics. By delving further into user sentiment and engagement with stock topics, investigators can put together meaningful pieces in assembling full-fledged investments picture that is based off sound evidence gained from real people’s experiences and opinion. Discovering new insights has never been made easier – let’s venture out on this journey together!

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨! ### Research Ideas
• Using the score and comments data, researchers can determine which stocks are being discussed and tracked the most, indicating potential areas of interest in the stock market.
• Analyzing the body text of posts to identify common topics of conversation related to various stocks assists in providing a better understanding of users' feelings towards different stock investments.
• Through analyzing fluctuations in user engagement over time, researchers can observe which stocks have experienced an increase or decrease in user interest and reaction to new developments within different markets

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: stocks.csv | Column name | Description | |:--------------|:--------------------------------------------------------------------| | title | The title of the post. (String) | | score | The score of the post, based on the Reddit voting system. (Integer) | | url | The URL of the post. (String) | | comms_num | The number of comments on the post. (Integer) | | created | The date and time the post was created. (Timestamp) | | body | The body text of the post. (String) | | timestamp | The date and time the post was last updated. (Timestamp) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Reddit.

Hong Kong's main stock market index, the HK50, rose to 26095 points on December 2, 2025, gaining 0.24% from the previous session. Over the past month, the index has declined 0.24%, though it remains 32.15% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Hong Kong. Hong Kong Stock Market Index (HK50) - values, historical data, forecasts and news - updated on December of 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.

Stock Analysis Software Market Outlook

The global stock analysis software market size was valued at approximately USD 1.2 billion in 2023 and is projected to reach around USD 3.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 12.5% during the forecast period. The growth of this market is driven by the increasing adoption of advanced analytics tools by individual investors and financial institutions to make informed investment decisions. The rising demand for automated trading systems and the integration of artificial intelligence (AI) and machine learning (ML) in stock analysis software are significant growth factors contributing to the market expansion.

One of the primary growth factors for the stock analysis software market is the increasing complexity and volume of financial data. With the exponential growth of data from various sources such as social media, news articles, and financial statements, investors and financial analysts require sophisticated tools to process and interpret this information accurately. Stock analysis software equipped with AI and ML algorithms can analyze vast datasets in real-time, providing valuable insights and predictive analytics that enhance investment strategies. Moreover, the growing trend of algorithmic trading, which relies heavily on high-speed data processing and automated decision-making, is further propelling the market growth.

Another crucial growth driver is the rising awareness and adoption of stock analysis software among individual investors. As more individuals seek to actively manage their investment portfolios, there is a growing demand for user-friendly and cost-effective stock analysis tools that offer comprehensive market analysis, technical indicators, and personalized investment recommendations. The proliferation of mobile applications and the increasing accessibility of cloud-based stock analysis solutions have made it easier for retail investors to access advanced analytical tools, thereby contributing to market expansion.

The integration of innovative technologies such as natural language processing (NLP) and sentiment analysis into stock analysis software is also a significant growth factor. These technologies enable the software to interpret and analyze unstructured data from news articles, social media, and other textual sources to gauge market sentiment and predict stock price movements. This capability is particularly valuable in today's fast-paced financial markets, where sentiment and news events can have a substantial impact on stock prices. The continuous advancements in AI and NLP technologies are expected to drive further innovations and improvements in stock analysis software, thereby boosting market growth.

In the evolving landscape of financial technology, Investor Relations Tools have become indispensable for companies seeking to maintain transparent and effective communication with their stakeholders. These tools facilitate seamless interaction between companies and their investors, providing real-time updates, financial reports, and strategic insights. By leveraging these tools, companies can enhance their investor engagement strategies, build trust, and foster long-term relationships with their shareholders. The integration of advanced analytics and AI-driven insights into Investor Relations Tools further empowers companies to tailor their communication strategies, ensuring that they meet the diverse needs of their investor base. As the demand for transparency and accountability in financial markets continues to grow, the adoption of sophisticated Investor Relations Tools is expected to rise, playing a crucial role in the broader ecosystem of stock analysis software.

From a regional perspective, North America is anticipated to hold the largest market share due to the high concentration of financial institutions, brokerage firms, and individual investors in the region. The presence of key market players and the early adoption of advanced technologies also contribute to the dominant position of North America in the global stock analysis software market. Additionally, the Asia Pacific region is expected to witness significant growth during the forecast period, driven by the increasing number of retail investors, rapid economic development, and the growing financial markets in countries such as China and India.

Component Analysis

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.

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.

Graph and download economic data for Index of Common Stock Prices, New York Stock Exchange for United States (M11007USM322NNBR) from Jan 1902 to May 1923 about New York, stock market, indexes, and USA.

Discover the booming stock software market! Our in-depth analysis reveals a $15 billion market in 2025 projected to reach $45 billion by 2033, driven by AI, mobile trading, and algorithmic strategies. Explore market trends, key players (Interactive Data, Ninja Trader, etc.), and regional insights. Invest wisely with our data-driven market overview.

Stock Analysis Software Market size was valued at USD 145.6 Million in 2024 and is projected to reach USD 450.68 Million by 2032, growing at a CAGR of 15.17% during the forecast period 2026-2032.Growing Retail Investor Participation: The Indian stock market has witnessed an unprecedented surge in retail investor participation. With the advent of user-friendly trading platforms, such as Zerodha, Groww, and Upstox, and the reduction of traditional barriers like high fees and the introduction of fractional shares, more individuals are now able to enter the market.Demand for Real-Time Data and Analytics: In today's fast-paced financial world, the need for real-time data and analytics is paramount. Investors, from seasoned professionals to burgeoning retail participants, require up-to-the-minute information on stock prices, breaking news, and crucial technical indicators to capitalize on fleeting opportunities.

The Rolling Stock Market Report is Segmented by Type (Locomotives, Metros and Light Rail Vehicles, Passenger Coaches, and More), Propulsion Type (Diesel, Electric, and More), Application (Passenger Rail and Freight Rail), End-User (National Rail Operators and More), Technology (Conventional and More) and Geography. The Market Forecasts are Provided in Terms of Value (USD) and Volume (Units).

The Dow Jones Industrial Average (DJIA) index dropped around ***** points in the four weeks from February 12 to March 11, 2020, but has since recovered and peaked at ********* points as of November 24, 2024. In February 2020 - just prior to the global coronavirus (COVID-19) pandemic, the DJIA index stood at a little over ****** points. U.S. markets suffer as virus spreads The COVID-19 pandemic triggered a turbulent period for stock markets – the S&P 500 and Nasdaq Composite also recorded dramatic drops. At the start of February, some analysts remained optimistic that the outbreak would ease. However, the increased spread of the virus started to hit investor confidence, prompting a record plunge in the stock markets. The Dow dropped by more than ***** points in the week from February 21 to February 28, which was a fall of **** percent – its worst percentage loss in a week since October 2008. Stock markets offer valuable economic insights The Dow Jones Industrial Average is a stock market index that monitors the share prices of the 30 largest companies in the United States. By studying the performance of the listed companies, analysts can gauge the strength of the domestic economy. If investors are confident in a company’s future, they will buy its stocks. The uncertainty of the coronavirus sparked fears of an economic crisis, and many traders decided that investment during the pandemic was too risky.

The value of the DJIA index amounted to ****** at the end of June 2025, 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.

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.

This stock market dataset is designed for financial analysis and predictive modeling. It includes historical stock prices, technical indicators, macroeconomic factors, and sentiment scores to help in developing and testing machine learning models for stock trend prediction.

Dataset Features: Column Description Stock Random stock ticker (AAPL, GOOG, etc.) Date Random business date Open Open price High High price Low Low price Close Close price Volume Trading volume SMA_10 10-day Simple Moving Average RSI Relative Strength Index (10-90 range) MACD MACD indicator (-5 to 5) Bollinger_Upper Upper Bollinger Band Bollinger_Lower Lower Bollinger Band GDP_Growth Random GDP growth rate (2.5% to 3.5%) Inflation_Rate Inflation rate (1.5% to 3.0%) Interest_Rate Interest rate (0.5% to 5.0%) Sentiment_Score Random sentiment score (-1 to 1) Next_Close Next day's closing price (for regression) Target Binary classification (1: Price Increase, 0: Price Decrease)

Key Features: Stock Prices: Open, High, Low, Close, and Volume data. Technical Indicators: Simple Moving Average (SMA), Relative Strength Index (RSI), MACD, and Bollinger Bands. Macroeconomic Factors: Simulated GDP growth, inflation rate, and interest rates. Sentiment Scores: Randomized sentiment values between -1 and 1 to simulate market sentiment. Target Variables: Next-day close price (for regression) and price movement direction (for classification).

The global stock market demonstrates a robust growth trajectory, poised for significant expansion in the coming decade. Projections indicate the market will surge from approximately $9.55 trillion in 2021 to over $23.85 trillion by 2033, expanding at a compound annual growth rate (CAGR) of 7.926%. This growth is underpinned by strong corporate earnings, technological advancements in trading, and increasing participation from retail investors. While North America currently dominates in terms of market size, the Asia-Pacific region is emerging as the fastest-growing hub, driven by the burgeoning economies of India and China. Factors such as monetary policies, geopolitical stability, and regulatory environments will continue to be pivotal in shaping regional market dynamics and overall global performance.

Key strategic insights from our comprehensive analysis reveal:

The Asia-Pacific region is the primary growth engine for the global stock market, exhibiting the highest CAGR of 9.112%, with nations like India and China leading this rapid expansion.
North America, particularly the United States, will maintain its position as the largest market by value, commanding a significant share of the global total, despite a slightly more moderate growth rate compared to APAC.
There is a consistent and broad-based growth trend across all major global regions, indicating widespread investor confidence and economic recovery, though the pace of expansion varies, highlighting diverse investment opportunities and risks.

Global Market Overview & Dynamics of Stock Market Analysis The global stock market is on a path of sustained and significant growth, driven by a confluence of economic, technological, and social factors. The market is forecast to expand from $9.55 trillion in 2021 to nearly $23.86 trillion by 2033. This expansion reflects growing global wealth, increased corporate profitability, and the continuous innovation in financial technologies that makes investing more accessible. However, this growth is not without its challenges, as markets must navigate through geopolitical tensions, inflationary pressures, and evolving regulatory landscapes that can introduce volatility and uncertainty.

Global Stock Market Drivers

Favorable Economic Conditions: Broad-based global GDP growth, coupled with supportive monetary policies from central banks in major economies, stimulates corporate investment and boosts earnings, attracting investors to equity markets.
Technological Innovation and Accessibility: The proliferation of online trading platforms, robo-advisors, and mobile investing apps has democratized access to stock markets, leading to a surge in retail investor participation.
Corporate Profitability and IPO Activity: Strong and resilient corporate earnings growth, along with a healthy pipeline of Initial Public Offerings (IPOs) from innovative companies, continually injects fresh capital and opportunities into the market.

Global Stock Market Trends

Rise of ESG Investing: There is a rapidly growing trend of investors integrating Environmental, Social, and Governance (ESG) criteria into their investment decisions, pushing companies to adopt more sustainable practices.
Increased Focus on Emerging Markets: Investors are increasingly allocating capital to emerging markets, particularly in the Asia-Pacific and South American regions, in pursuit of higher growth potential compared to more mature markets.
Growth of Passive Investing: The shift towards passive investment strategies, such as index funds and Exchange-Traded Funds (ETFs), continues to gain momentum due to their lower costs and broad market exposure.

Global Stock Market Restraints

Geopolitical Instability and Trade Disputes: International conflicts, trade wars, and political uncertainty can disrupt global supply chains, dampen investor sentiment, and lead to significant market volatility.
Inflation and Interest Rate Hikes: Persistent inflationary pressures force central banks to raise interest rates, which increases borrowing costs for companies and can make less risky assets like bonds more attractive relative to stocks.
Regulatory Scrutiny and Complexity: Stricter regulations on financial markets, data privacy, and corporate governance can increase compliance costs and limit certain market activities, potentially hindering growth.

Strategic Recommendations for Manufacturers

Prioritize market entry and expansion s...

Discover the future of the global stock market. This in-depth analysis reveals key trends, drivers, and restraints impacting growth through 2033, along with regional market share projections and insights into leading companies. Explore the opportunities and challenges in this dynamic trillion-dollar market.