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.

India's main stock market index, the SENSEX, fell to 85138 points on December 2, 2025, losing 0.59% from the previous session. Over the past month, the index has climbed 1.38% and is up 5.31% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from India. BSE SENSEX Stock Market Index - values, historical data, forecasts and news - updated on December of 2025.

View monthly updates and historical trends for S&P 500 Monthly Return. from United States. Source: Standard and Poor's. Track economic data with YCharts a…

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 monthly updates and historical trends for S&P 500 12 Month Total Return. from United States. Source: Standard and Poor's. Track economic data with YC…

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.

By the end of January 2025, the leading stock index in Israel (TA-125) reached just over 2500 points. During the observed period, the American stock index S&P 500 reached about 6040 points. Since the beginning of the Israel-Hamas war in October 2023 until January 2025, the Israeli index has grown by nearly ** percent. In comparison, the S&P 500 index grew by ** percent over the same period.

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 Preferred Stock Prices, New York Stock Exchange for United States (M11008USM322NNBR) from Jan 1902 to May 1923 about New York, stock market, indexes, and USA.

The S&P BSE Sensex index, one of India's two main stock indices, lost almost *********** of its value between the end of February and the end of March 2020, owing to the economic impact of the global coronavirus (COVID-19) pandemic. It has since recovered, surpassing its pre-corona level in *************.The S&P BSE Sensex index includes 30 companies listed on the Bombay Stock Exchange which are representative of various industrial sectors of the Indian economy. It is considered one of the main Indicators of the Indian stock market, along with the CNX Nifty Index (which includes shares from India's other main stock exchange, the National Stock Exchange).

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.

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.

Key information about India Sensitive 30 (Sensex)

• India Sensitive 30 (Sensex) closed at 85,706.7 points in Nov 2025, compared with 83,938.7 points at the previous month end
• India Equity Market Index: Month End: BSE: Sensitive 30 (Sensex) data is updated monthly, available from Apr 1979 to Nov 2025, with an average number of 2,987.7 points
• The data reached an all-time high of 85,706.7 points in Nov 2025 and a record low of 115.6 points in Nov 1979

• In the latest reports, SENSEX recorded a daily P/E ratio of 23.2 in Dec 2025

View monthly updates and historical trends for S&P 500. from United States. Source: Standard and Poor's. Track economic data with YCharts analytics.

Context

NIFTY 500 is India’s first broad-based stock market index of the Indian stock market. It contains the top 500 listed companies on the NSE. The NIFTY 500 index represents about 96.1% of free-float market capitalization and 96.5% of the total turnover on the National Stock Exchange (NSE).

NIFTY 500 companies are disaggregated into 72 industry indices. Industry weights in the index reflect industry weights in the market. For example, if the banking sector has a 5% weight in the universe of stocks traded on the NSE, banking stocks in the index would also have an approximate representation of 5% in the index. NIFTY 500 can be used for a variety of purposes such as benchmarking fund portfolios, launching index funds, ETFs, and other structured products.

• Other Notable Indices -
  • NIFTY 50: Top 50 listed companies on the NSE. A diversified 50-stock index accounting for 13 sectors of the Indian economy.
  • NIFTY Next 50: Also called NIFTY Juniors. Represents 50 companies from NIFTY 100 after excluding the NIFTY 50 companies.
  • NIFTY 100: Diversified 100 stock index representing major sectors of the economy. NIFTY 100 represents the top 100 companies based on full market capitalization from NIFTY 500.
  • NIFTY 200: Designed to reflect the behavior and performance of large and mid-market capitalization companies.

Content

The dataset comprises various parameters and features for each of the NIFTY 500 Stocks, including Company Name, Symbol, Industry, Series, Open, High, Low, Previous Close, Last Traded Price, Change, Percentage Change, Share Volume, Value in Indian Rupee, 52 Week High, 52 Week Low, 365 Day Percentage Change, and 30 Day Percentage Change.

Dataset Glossary (Column-Wise)

Company Name: Name of the Company.

Symbol: A stock symbol is a unique series of letters assigned to a security for trading purposes.

Industry: Name of the industry to which the stock belongs.

Series: EQ stands for Equity. In this series intraday trading is possible in addition to delivery and BE stands for Book Entry. Shares falling in the Trade-to-Trade or T-segment are traded in this series and no intraday is allowed. This means trades can only be settled by accepting or giving the delivery of shares.

Open: It is the price at which the financial security opens in the market when trading begins. It may or may not be different from the previous day's closing price. The security may open at a higher price than the closing price due to excess demand for the security.

High: It is the highest price at which a stock is traded during the course of the trading day and is typically higher than the closing or equal to the opening price.

Low: Today's low is a security's intraday low trading price. Today's low is the lowest price at which a stock trades over the course of a trading day.

Previous Close: The previous close almost always refers to the prior day's final price of a security when the market officially closes for the day. It can apply to a stock, bond, commodity, futures or option co-contract, market index, or any other security.

Last Traded Price: The last traded price (LTP) usually differs from the closing price of the day. This is because the closing price of the day on NSE is the weighted average price of the last 30 mins of trading. The last traded price of the day is the actual last traded price.

Change: For a stock or bond quote, change is the difference between the current price and the last trade of the previous day. For interest rates, change is benchmarked against a major market rate (e.g., LIBOR) and may only be updated as infrequently as once a quarter.

Percentage Change: Take the selling price and subtract the initial purchase price. The result is the gain or loss. Take the gain or loss from the investment and divide it by the original amount or purchase price of the investment. Finally, multiply the result by 100 to arrive at the percentage change in the investment.

Share Volume: Volume is an indicator that means the total number of shares that have been bought or sold in a specific period of time or during the trading day. It will also involve the buying and selling of every share during a specific time period.

Value (Indian Rupee): Market value—also known as market cap—is calculated by multiplying a company's outstanding shares by its current market price.

52-Week High: A 52-week high is the highest share price that a stock has traded at during a passing year. Many market aficionados view the 52-week high as an important factor in determining a stock's current value and predicting future price movement. 52-week High prices are adjusted for Bonus, Split & Rights Corporate actions.

52-Week Low: A 52-week low is the lowest ...

1. Overview

This dataset provides monthly stock price data for the MAG7 over the past 20 years (2004–2024). The data includes key financial metrics such as opening price, closing price, highest and lowest prices, trading volume, and percentage change. The dataset is valuable for financial analysis, stock trend forecasting, and portfolio optimization.

2. What is MAG7 ?

MAG7 refers to the seven largest and most influential technology companies in the U.S. stock market : - Microsoft (MSFT) - Apple (AAPL) - Google (Alphabet, GOOGL) - Amazon (AMZN) - Nvidia (NVDA) - Meta (META) - Tesla (TSLA)

These companies are known for their market dominance, technological innovation, and significant impact on global stock indices such as the S&P 500 and Nasdaq-100.

3. Dataset Details

The dataset consists of historical monthly stock prices of MAG7, retrieved from Investing.com. It provides an overview of how these stocks have performed over two decades, reflecting market trends, economic cycles, and technological shifts.

4. Columns Descriptions

• Date The recorded month and year (DD-MM-YYYY)
• Price The closing price of the stock at the end of the month
• Open The price at which the stock opened at the beginning of the month
• High The highest stock price recorded in the month
• Low The lowest stock price recorded in the month
• Vol. The total trading volume for the month
• Change % The percentage change in stock price compared to the previous month # 5. Data Source & Format The dataset was obtained from Investing.com and downloaded in CSV format. The data has been processed to ensure consistency and accuracy, with date formats standardized for time-series analysis. # 6. Potential Use Cases This dataset can be used for :
• 📈 Stock price trend analysis over 20 years
• 📊 Building financial models for long-term investing
• 🔎 Machine learning applications in stock market prediction
• 📉 Evaluating market volatility and economic impact on MAG7 stocks

7. Limitations & Considerations

• ⚠️ The dataset is limited to monthly data, meaning short-term price fluctuations are not captured.
• ⚠️ Trading volume (Vol.) may vary in availability due to differences in reporting.
• ⚠️ External factors such as stock splits, dividends, and market crashes are not explicitly noted but may impact historical trends.

Global Stock Market Financial Dataset (from TradingView)

This collection provides a comprehensive snapshot of over 11,800 publicly traded companies worldwide. It combines multiple financial statements and performance indicators extracted from TradingView to support data analysis, stock screening, and financial modeling.

Files Overview

1.tradingview_all_stocks.csv Contains general stock information and market statistics.

Columns: ticker, name, close, change, change_abs, volume, market_cap_basic, price_earnings_ttm, sector, industry Size: 11,806 rows × 10 columns Description: Lists all active stocks with latest prices, PE ratios, and sector/industry classifications.

2.tradingview_performance.csv Tracks short- and long-term stock performance.

Columns (sample): ticker, name, close, Perf.W, Perf.1M, Perf.3M, Perf.6M, Perf.YTD, Perf.1Y, Perf.5Y, etc. Size: 11,814 rows × 17 columns Description: Shows relative percentage performance across multiple timeframes.

3.balance_sheet.csv Summarizes financial position and liquidity metrics.

Columns: total_assets_fq, cash_n_short_term_invest_fq, total_liabilities_fq, total_debt_fq, net_debt_fq, total_equity_fq, current_ratio_fq Size: 11,821 rows × 12 columns Description: Includes key balance sheet values, enabling leverage and liquidity analysis.

4.cashflow.csv Focuses on company cash generation and sustainability.

Columns: free_cash_flow_ttm Size: 11,821 rows × 4 columns Description: Provides trailing twelve-month free cash flow figures for profitability evaluation.

5.dividends.csv Details dividend-related statistics.

Columns: dividends_yield, dividend_payout_ratio_ttm Size: 11,823 rows × 5 columns Description: Useful for income-focused investors; includes dividend yields and payout ratios.

6.income_statement.csv Presents company earnings metrics.

Columns: total_revenue_ttm, gross_profit_ttm, net_income_ttm, ebitda_ttm Size: 11,821 rows × 7 columns Description: Captures profitability over the last 12 months for revenue and margin analysis.

7.profitability.csv Shows margin-based performance indicators.

Columns: gross_margin_ttm, operating_margin_ttm, net_margin_ttm, ebitda_margin_ttm Size: 11,823 rows × 7 columns Description: Enables efficiency and operational performance comparisons across companies.

Use Cases 1. Stock market and financial analysis 2. Portfolio optimization and factor modeling 3. Machine learning for price prediction 4. Company benchmarking and screening 5. Academic or educational use in finance courses

Data Source & Notes 1. All data was aggregated from TradingView using public financial data endpoints. 2. Missing values may occur for companies that do not report certain metrics. 3. All monetary figures are based on the latest available TTM (Trailing Twelve Months) or FQ (Fiscal Quarter) data at the time of extraction.

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 Financial Market: Share Prices for Poland (SPASTT01PLM661N) from May 1991 to Sep 2025 about Poland and stock market.

France's main stock market index, the FR40, rose to 8121 points on December 2, 2025, gaining 0.29% from the previous session. Over the past month, the index has climbed 0.13% and is up 11.93% compared to the same time last year, 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 December of 2025.