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.

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.

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.

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.

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.

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.

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.

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.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

The Dow Jones U.S. Completion Total Stock Market Index

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

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.

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.

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.

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.

The S&P 500 index dropped significantly between January 3 and September 9, 2022. As of January 3, the index stood at ******** points, and it dropped approximately 15 percent by September 2022. In August 2025, the daily value of the S&P 500 increased over 6**** points and reached ********as of August 19 of the same year.

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.

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.

Throughout the 1920s, prices on the U.S. stock exchange rose exponentially, however, by the end of the decade, uncontrolled growth and a stock market propped up by speculation and borrowed money proved unsustainable, resulting in the Wall Street Crash of October 1929. This set a chain of events in motion that led to economic collapse - banks demanded repayment of debts, the property market crashed, and people stopped spending as unemployment rose. Within a year the country was in the midst of an economic depression, and the economy continued on a downward trend until late-1932.

It was during this time where Franklin D. Roosevelt (FDR) was elected president, and he assumed office in March 1933 - through a series of economic reforms and New Deal policies, the economy began to recover. Stock prices fluctuated at more sustainable levels over the next decades, and developments were in line with overall economic development, rather than the uncontrolled growth seen in the 1920s. Overall, it took over 25 years for the Dow Jones value to reach its pre-Crash peak.

All data acquired on December 11th 2023

1) Ticker: Stock symbol identifying the company.

2) Company: Name of the company.

3) Sector: Industry category to which the company belongs.

4) Industry: Specific sector or business category of the company.

5) Country: Country where the company is based.

6) Market Cap: Total market value of a company's outstanding shares.

7) Price: Current stock price.

8) Change (%): Percentage change in stock price.

9) Volume: Number of shares traded.

10) Price to Earnings Ratio: Ratio of stock price to earnings per share.

11) Price to Earnings: Price-to-earnings ratio based on past earnings.

12) Forward Price to Earnings: Expected price-to-earnings ratio.

13) Price/Earnings to Growth: Ratio of P/E to earnings growth.

14) Price to Sales: Ratio of stock price to annual sales.

15) Price to Book: Ratio of stock price to book value.

16) Price to Cash: Ratio of stock price to cash per share.

17) Price to Free Cash Flow: Ratio of stock price to free cash flow.

18) Earnings Per Share This Year (%): Percentage change in earnings per share for the current year.

19) Earnings Per Share Next Year (%): Percentage change in earnings per share for the next year.

20) Earnings Per Share Past 5 Years (%): Percentage change in earnings per share over the past 5 years.

21) Earnings Per Share Next 5 Years (%): Estimated percentage change in earnings per share over the next 5 years.

22) Sales Past 5 Years (%): Percentage change in sales over the past 5 years.

23) Dividend (%): Dividend yield as a percentage of the stock price.

24) Return on Assets (%): Percentage return on total assets.

25) Return on Equity (%): Percentage return on shareholder equity.

26) Return on Investment (%): Percentage return on total investment.

27) Current Ratio: Ratio of current assets to current liabilities.

28) Quick Ratio: Ratio of liquid assets to current liabilities.

29) Long-Term Debt to Equity: Ratio of long-term debt to shareholder equity.

30) Debt to Equity: Ratio of total debt to shareholder equity.

31) Gross Margin (%): Percentage difference between revenue and cost of goods sold.

32) Operating Margin (%): Percentage of operating income to revenue.

33) Profit Margin: Percentage of net income to revenue.

34) Earnings: Net income of the company.

35) Outstanding Shares: Total number of shares issued by the company.

36) Float: Tradable shares available to the public.

37) Insider Ownership (%): Percentage of company owned by insiders.

38) Insider Transactions: Recent insider buying or selling activity.

39) Institutional Ownership (%): Percentage of company owned by institutional investors.

40) Float Short (%): Percentage of tradable shares sold short by investors.

41) Short Ratio: Number of days it would take to cover short positions.

42) Average Volume: Average number of shares traded daily.

43) Performance (Week) (%): Weekly stock performance percentage.

44) Performance (Month) (%): Monthly stock performance percentage.

45) Performance (Quarter) (%): Quarterly stock performance percentage.

46) Performance (Half Year) (%): Semi-annual stock performance percentage.

47) Performance (Year) (%): Annual stock performance percentage.

48) Performance (Year to Date) (%): Year-to-date stock performance percentage.

49) Volatility (Week) (%): Weekly stock price volatility percentage.

50) Volatility (Month) (%): Monthly stock price volatility percentage.

51) Analyst Recommendation: Analyst consensus recommendation on the stock.

52) Relative Volume: Volume compared to the average volume.

53) Beta: Measure of stock price volatility relative to the market.

54) Average True Range: Average price range of a stock.

55) Simple Moving Average (20) (%): Percentage difference from the 20-day simple moving average.

56) Simple Moving Average (50) (%): Percentage difference from the 50-day simple moving average.

57) Simple Moving Average (200) (%): Percentage difference from the 200-day simple moving average.

58) Yearly High (%): Percentage difference from the yearly high stock price.

59) Yearly Low (%): Percentage difference from the yearly low stock price.

60) Relative Strength Index: Momentum indicator measuring the speed and change of price movements.

61) Change from Open (%): Percentage change from the opening stock price.

62) Gap (%): Percentage difference between the previous close and the current open price.

63) Volume: Total number of shares traded.

The Dow Jones Industrial Average (DJIA) is a stock market index used to analyze trends in the stock market. While many economists prefer to use other, market-weighted indices (the DJIA is price-weighted) as they are perceived to be more representative of the overall market, the Dow Jones remains one of the most commonly-used indices today, and its longevity allows for historical events and long-term trends to be analyzed over extended periods of time. Average changes in yearly closing prices, for example, shows how markets developed year on year. Figures were more sporadic in early years, but the impact of major events can be observed throughout. For example, the occasions where a decrease of more than 25 percent was observed each coincided with a major recession; these include the Post-WWI Recession in 1920, the Great Depression in 1929, the Recession of 1937-38, the 1973-75 Recession, and the Great Recession in 2008.

The stock market today saw mixed results with major U.S. stock indexes closing higher, while crude oil prices experienced a decline. Factors including a tech sell-off, economic recovery concerns, stimulus package delays, demand outlook, OPEC+ production increase, and U.S. inventory buildup influenced the market and oil prices.