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 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.

This dataset contains 2000 daily stock market records including price movements, trading volume, market trends, indices, economic scores, and market sentiment information. It covers multiple sectors with a general category column and includes a target column for the next-day closing price. Additional text columns capture market sentiment and news tags for each record. The dataset is designed to provide comprehensive insights into stock market behavior and trends.

Number of Records: 2000

Number of Columns: 18

Column Descriptions:

Category – General text representing the sector or type of stock (e.g., Tech, Finance, Health).

Date – The calendar date of the stock record.

Open – The opening price of the stock on that day.

High – The highest price of the stock during the day.

Low – The lowest price of the stock during the day.

Close – The closing price of the stock on that day.

Volume – The total number of shares traded during the day.

SMA_10 – The 10-day simple moving average of the closing price, showing short-term trend.

EMA_10 – The 10-day exponential moving average of the closing price, giving more weight to recent prices.

Volatility – The standard deviation of the closing price over a 10-day window, representing price fluctuation.

Wavelet_Trend – Trend component of the closing price over a 10-day period.

Wavelet_Noise – Difference between the actual closing price and the trend component, capturing minor fluctuations.

Wavelet_HighFreq – Daily price changes in closing price, showing high-frequency movement.

General_Index – A numeric indicator representing general market performance.

Economic_Score – A numeric score representing overall economic factors impacting the stock.

Market_Sentiment – Text describing the sentiment of the market for that day (Positive, Neutral, Negative).

News_Tag – Text describing the main type of news impacting the stock on that day (e.g., Earnings, Merger).

Close_Next – The closing price of the stock for the next day, serving as the target variable.

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.

Stock Market Data: 9,000+ Tickers (1962 - Present)

Dataset Overview

This dataset offers comprehensive historical stock market data covering over 9,000 tickers from 1962 to the present day. It includes essential daily trading information, making it suitable for various financial analyses, trend studies, and algorithmic trading model development.

Columns

• Date: The date of the recorded trading data.
• Ticker: The stock symbol of the company.
• Open: Opening price of the stock on the trading day.
• High: Highest price reached during the trading day.
• Low: Lowest price reached during the trading day.
• Close: Closing price of the stock on the trading day.
• Volume: The total number of shares traded during the day.
• Dividends: Cash dividends issued on the date, if applicable.
• Stock Splits: Stock split factor for the date, if any split occurred.

Usage

This dataset is ideal for: - Time-Series Analysis: Track stock price trends over time, examining daily, monthly, and yearly patterns across sectors. - Algorithmic Trading: Develop and backtest trading strategies using historical price movements and volume data. - Machine Learning Applications: Train models for stock price prediction, volatility forecasting, or portfolio optimization. - Quantitative Research: Perform event studies, analyze the impact of dividends and stock splits, and assess long-term investment strategies. - Comparative Analysis: Evaluate performance across industries or against broader market trends by analyzing multiple tickers in one dataset.

This dataset serves as a robust resource for academic research, quantitative finance studies, and financial technology development.

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.

Greece's main stock market index, the Athens General, rose to 2108 points on December 2, 2025, gaining 0.41% from the previous session. Over the past month, the index has climbed 4.15% and is up 47.48% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Greece. Greece Stock Market (ASE) - 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.

Spain's main stock market index, the ES35, rose to 16493 points on December 2, 2025, gaining 0.63% from the previous session. Over the past month, the index has climbed 2.84% and is up 38.90% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Spain. Spain Stock Market Index (ES35) - values, historical data, forecasts and news - updated on December of 2025.

Overview

This dataset contains historical daily prices for all tickers currently trading on NASDAQ. The up to date list is available from nasdaqtrader.com. The historic data is retrieved from Yahoo finance via yfinance python package.

It contains prices for up to 01 of April 2020. If you need more up to date data, just fork and re-run data collection script also available from Kaggle.

Data Structure

The date for every symbol is saved in CSV format with common fields:

• Date - specifies trading date
• Open - opening price
• High - maximum price during the day
• Low - minimum price during the day
• Close - close price adjusted for splits
• Adj Close - adjusted close price adjusted for both dividends and splits.
• Volume - the number of shares that changed hands during a given day

All that ticker data is then stored in either ETFs or stocks folder, depending on a type. Moreover, each filename is the corresponding ticker symbol. At last, symbols_valid_meta.csv contains some additional metadata for each ticker such as full name.

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.

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.

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 value of global domestic equity market increased from ***** trillion U.S. dollars in 2013 to ****** trillion U.S. dollars in 2024. The United States was by far the leading country with the largest share of total world stocks as of 2024. Global market capitalization in different regions The market capitalization of domestic companies listed varied across different regions of the world. As of Decmber 2024, the Americas region had the largest domestic equity market, totaling ** trillion U.S. dollars. This region is home to the NYSE and Nasdaq, which are the two largest stock exchange operators in the world. The market capitalization of these two exchanges alone exceeded ** billion U.S. dollars as of January 2025, larger than the total market capitalization in the Asia-Pacific, and in the EMEA regions in the same period. Largest Stock Exchanges in Latin America As of December 2024, the B3 (Brasil Bolsa Balcao) was the biggest stock exchange in Latin America in terms of market capitalization and the second-largest in terms of number of listed companies. Following the B3 were the Mexican Stock Exchange and the Santiago Stock Exchange in Chile. The most valuable company in Latin America is listed on the Mexican Stock Exchange: Fomento Económico Mexicano, a multinational beverage and retail company headquartered in Monterrey, had a market cap of *** billion U.S. dollars as of March 2025.

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

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.

Historical dataset of the United States Stock Market Index (S&P 500), covering values from 1928-01-01 to 2025-11-28, with the latest releases and long-term trends. Available for free download in CSV format.

Graph and download economic data for Financial Market: Share Prices for United Kingdom (SPASTT01GBM661N) from Dec 1957 to Oct 2025 about stock market and United Kingdom.

On January 29, 2024 the AEX index closed at ****** points - significantly higher than the 2020 low of ***** points recorded on March 18, 2020. The AEX Index, the index of the ** biggest stocks on the Amsterdam Stock Exchange, saw heavy losses early March 2020 due to economic uncertainties following the coronavirus pandemic. On top, there was an unexpected decrease in oil prices, as announced by Saudi Arabia over a dispute with Russia. This caused stocks like Royal Dutch Shell, the Netherlands' biggest listed company, to go down significantly.

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.