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.

Israel's main stock market index, the TA-125, rose to 3538 points on December 2, 2025, gaining 1.75% from the previous session. Over the past month, the index has climbed 4.40% and is up 50.06% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Israel. Israel Stock Market (TA-125) - values, historical data, forecasts and news - updated on December of 2025.

The US_Stock_Data.csv dataset offers a comprehensive view of the US stock market and related financial instruments, spanning from January 2, 2020, to February 2, 2024. This dataset includes 39 columns, covering a broad spectrum of financial data points such as prices and volumes of major stocks, indices, commodities, and cryptocurrencies. The data is presented in a structured CSV file format, making it easily accessible and usable for various financial analyses, market research, and predictive modeling. This dataset is ideal for anyone looking to gain insights into the trends and movements within the US financial markets during this period, including the impact of major global events.

Key Features and Data Structure

The dataset captures daily financial data across multiple assets, providing a well-rounded perspective of market dynamics. Key features include:

• Commodities: Prices and trading volumes for natural gas, crude oil, copper, platinum, silver, and gold.
• Cryptocurrencies: Prices and volumes for Bitcoin and Ethereum, including detailed 5-minute interval data for Bitcoin.
• Stock Market Indices: Data for major indices such as the S&P 500 and Nasdaq 100.
• Individual Stocks: Prices and volumes for major companies including Apple, Tesla, Microsoft, Google, Nvidia, Berkshire Hathaway, Netflix, Amazon, and Meta.

The dataset’s structure is designed for straightforward integration into various analytical tools and platforms. Each column is dedicated to a specific asset's daily price or volume, enabling users to perform a wide range of analyses, from simple trend observations to complex predictive models. The inclusion of intraday data for Bitcoin provides a detailed view of market movements.

Applications and Usability

This dataset is highly versatile and can be utilized for various financial research purposes:

• Market Analysis: Track the performance of key assets, compare volatility, and study correlations between different financial instruments.
• Risk Assessment: Analyze the impact of commodity price movements on related stock prices and evaluate market risks.
• Educational Use: Serve as a resource for teaching market trends, asset correlation, and the effects of global events on financial markets.

The dataset’s daily updates ensure that users have access to the most current data, which is crucial for real-time analysis and decision-making. Whether for academic research, market analysis, or financial modeling, the US_Stock_Data.csv dataset provides a valuable foundation for exploring the complexities of financial markets over the specified period.

Acknowledgements:

This dataset would not be possible without the contributions of Dhaval Patel, who initially curated the US stock market data spanning from 2020 to 2024. Full credit goes to Dhaval Patel for creating and maintaining the dataset. You can find the original dataset here: US Stock Market 2020 to 2024.

Graph and download economic data for Stocks, Number of Shares Sold on the New York Stock Exchange for United States (M11002USM444NNBR) from Jan 1875 to Aug 1966 about stock market and USA.

Photo by Maxim Hopman on Unsplash.

Introduction

According to Economatica, a company specializing in the Latin American stock market, the Brazilian stock exchange market, governed by Brasil, Bolsa, Balcão (B3), exchanged BRL ~25.9 billion per day in the first half of 2020, during the coronavirus epidemic. Furthermore, it is estimated that in this same period there was an 18% growth in the number of Brazilian investors, totaling ~2.6 million active investors. Therefore, the financial market moves a large amount of values and, consequently, produces a vast amount of information and data daily; These data represent the movements of shares, their respective prices, dollar exchange values, and so on. This dataset contains daily stock values and information about their companies.

Inspiration

• Data Analysis - Spark
• Price Prediction - Regression task
• Best Group of Stocks - Association Rules task

This dataset provides an environment (Data Warehouse-like) for analysis and visualization of financial business for users of decision support systems. Specifically, the data allow compare different assets (i.e. stocks) listed on B3, according to the sectors of the economy in which these assets operate. For example, with this Data Warehouse, the user will be able to answer questions similar to this one: What are the most profitable sectors for investment in a given period of time? In this way, the user can identify which are the sectors that are standing out, as well as which are the most profitable companies in the sector.

Dataset

https://i.imgur.com/28Mf0sN.png" alt="Data Warehouse">

This dataset is split into five files: - dimCoin.csv - Dimension table with information about the coins. - dimCompany.csv - Dimension table with information about the companies. - dimTime.csv - Dimension table with information about the datetime. - factCoins.csv - Fact table with coin value over time. - factStocks.csv - Fact table with stock prices over time.

Source

The data were available by B3. You can access in https://www.b3.com.br/en_us/market-data-and-indices/ .I just structure and model the data as Data Warehouse tables. You can access my code in https://github.com/leomaurodesenv/b3-stock-indexes

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.

While the global coronavirus (COVID-19) pandemic caused all major stock market indices to fall sharply in March 2020, both the extent of the decline at this time, and the shape of the subsequent recovery, have varied greatly. For example, on March 15, 2020, major European markets and traditional stocks in the United States had shed around ** percent of their value compared to January *, 2020. However, Asian markets and the NASDAQ Composite Index only shed around ** to ** percent of their value. A similar story can be seen with the post-coronavirus recovery. As of November 14, 2021 the NASDAQ composite index value was around ** percent higher than in January 2020, while most other markets were only between ** and ** percent higher. Why did the NASDAQ recover the quickest? Based in New York City, the NASDAQ is famously considered a proxy for the technology industry as many of the world’s largest technology industries choose to list there. And it just so happens that technology was the sector to perform the best during the coronavirus pandemic. Accordingly, many of the largest companies who benefitted the most from the pandemic such as Amazon, PayPal and Netflix, are listed on the NADSAQ, helping it to recover the fastest of the major stock exchanges worldwide. Which markets suffered the most? The energy sector was the worst hit by the global COVID-19 pandemic. In particular, oil companies share prices suffered large declines over 2020 as demand for oil plummeted while workers found themselves no longer needing to commute, and the tourism industry ground to a halt. In addition, overall share prices in two major stock exchanges – the London Stock Exchange (as represented by the FTSE 100 index) and Hong Kong (as represented by the Hang Seng index) – have notably recovered slower than other major exchanges. However, in both these, the underlying issue behind the slower recovery likely has more to do with political events unrelated to the coronavirus than it does with the pandemic – namely Brexit and general political unrest, respectively.

1) Data Introduction • The Twitter Stock Prices Dataset contains stock price data for Twitter from November 2013 to October 2022. This dataset is a time series dataset that provides daily stock trading information. • The key attributes include the stock's opening price (Open), highest price (High), lowest price (Low), closing price (Close), adjusted closing price (Adj Close), and volume (Volume).

2) Data Utilization (1) Characteristics of the Twitter Stock Prices Data • This dataset is a time series, offering daily stock price fluctuations and allows tracking of price changes over time. • It includes 7 main attributes related to stock trading, allowing for analysis of price movements (open, high, low, close) and volume, to better understand Twitter’s stock price dynamics. • This data helps analyze market trends, price volatility patterns, and price fluctuation analysis, providing insights into the dynamics of the stock market.

(2) Applications of the Twitter Stock Prices Data • Predictive Modeling: This dataset can be used to develop stock price prediction models, including predicting price increases/decreases or forecasting future stock prices using machine learning models. • Business Insights: Investment experts can use this dataset to evaluate Twitter’s stock performance, and it provides useful information for optimizing investment strategies in response to market changes. This dataset can be used for trend forecasting and investor analysis. • Trend Analysis: By analyzing stock upward/downward trends, this dataset can help evaluate the company's market performance and develop trend-based investment strategies.

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.

Content

Top Companies of NASDAQ 100 in 2022

Here are the top companies on the NASDAQ 100 index in 2022. NASDAQ 100 is one of the most prominent large-cap growth indices in the world.

Many companies listed in the NASDAQ 100 operate in the tech sector. That is why many investors who are focused investing in tech stocks also invest in NASDAQ index to grow their funds

What is NASDAQ 100?

NASDAQ 100 is a stock market index composed of the 100 largest and most actively traded companies in the United States of America in the non- financial sector and are segmented under technology, retail, industrial, biotechnology, health care, telecom, transportation, media and services sectors.

Acknowledgement

Data collected from Yahoo Finance.

Vietnam VN: Stocks Traded: Turnover Ratio of Domestic Shares data was reported at 32.962 % in 2017. This records a decrease from the previous number of 39.143 % for 2016. Vietnam VN: Stocks Traded: Turnover Ratio of Domestic Shares data is updated yearly, averaging 39.143 % from Dec 2008 (Median) to 2017, with 9 observations. The data reached an all-time high of 85.465 % in 2009 and a record low of 25.985 % in 2013. Vietnam VN: Stocks Traded: Turnover Ratio of Domestic Shares data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Vietnam – Table VN.World Bank.WDI: Financial Sector. Turnover ratio is the value of domestic shares traded divided by their market capitalization. The value is annualized by multiplying the monthly average by 12.; ; World Federation of Exchanges database.; Weighted average; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Alibaba Group (BABA) Stock Price Data (2014–2025)

Dataset Overview

This dataset contains historical stock price data for Alibaba Group Holding Limited (NYSE: BABA) from September 19, 2014, to March 1, 2025. It provides crucial stock market indicators such as opening price, closing price, highest and lowest prices, adjusted closing price, and trading volume.

Columns Description

date: Date of the stock market record (2014-09-19).

open: Opening price of the stock on that day.

high: Highest price reached during the trading session.

low: Lowest price recorded during the trading session.

close: Closing price of the stock at the end of the trading day.

adj_close: Adjusted closing price accounting for corporate actions like splits or dividends.

volume: Number of shares traded on that day.

Dataset Details

-Total Rows: 2,627 (trading days)

-Total Columns: 7

-Data Range: September 19, 2014 – March 1, 2025

Potential Use Cases

-Stock price trend analysis

-Time series forecasting

-Volatility analysis

-Developing trading strategies using machine learning models

-Technical analysis with indicators

Source The data is sourced from stock market records of the New York Stock Exchange (NYSE) and is intended for research, financial analysis, and educational purposes.

Contect info:

You can contect me for more data sets

-E_mail

-Linkdin

-Kaggle

-X

-Github

In 2024, the average price-to-book (P/B) ratio of stocks on the Prime Market of the Tokyo Stock Exchange (TSE) in Japan was ***. The average P/B ratio of stocks on the Standard Market was ***.

This statistic presents the outlook that registered investment advisors (RIAs) have for the stock market in the first half of 2020. At the time of the survey, **% of RIAs thought the stock market would increase in value overall.

This statistic shows Euronext Lisbon's ** strongest market capitalization for companies incorporated in Portugal. As of the end of June 2025, the highest market capitalization recorded was for EDP, which reached **** billion euros. Jerónimo Martins, SGPS came second with approximately **** billion euros, followed by Galp Energia, with a market capitalization of **** billion euros.

Actual value and historical data chart for United States Stocks Traded Total Value Us Dollar

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.

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.

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 93 companies listed on the Bucharest Stock Exchange* (XBSE) in Romania. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

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Top 5 used data fields in the End-of-Day Pricing Dataset for Romania:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

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Top 5 financial instruments with End-of-Day Pricing Data in Romania:

Bucharest Stock Exchange Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Bucharest Stock Exchange. This index provides an overview of the overall market performance in Romania.

Bucharest Stock Exchange Foreign Company Index: The index that tracks the performance of foreign companies listed on the Bucharest Stock Exchange. This index reflects the performance of international companies operating in Romania.

Company A: A prominent Romanian company with diversified operations across various sectors, such as manufacturing, technology, or finance. This company's stock is widely traded on the Bucharest Stock Exchange.

Company B: A leading financial institution in Romania, offering banking, insurance, or investment services. This company's stock is actively traded on the Bucharest Stock Exchange.

Company C: A major player in the Romanian energy or consumer goods sector, involved in the production and distribution of related products. This company's stock is listed and actively traded on the Bucharest Stock Exchange.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Romania, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

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Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in Romania ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in Romania ?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Romania exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

1. How do I pay for this dataset?

Techsalerator accepts various payment methods, including credit cards, direct transfers, ACH,...

This dataset is about stocks. It has 476 rows and is filtered where the exchange is Canadian Securities Exchange. It features 8 columns including stock name, company, exchange, and exchange symbol.