https://brightdata.com/licensehttps://brightdata.com/license
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
NASDAQ (National Association of Securities Dealers Automated Quotation) is the world's second largest automated and electronic stock exchange and securities market in the United States, the first being the New York Stock Exchange, with more than 8,000 companies and corporations. It has more trading volume per hour than any other stock exchange in the world. More than 7,000 small and mid-cap stocks are traded on the NASDAQ. It is characterized by comprising high-tech companies in electronics, computers, telecommunications, biotechnology, and many others.
This dataset was created as a result of an automatic extraction of open & public data available in nasdaq.com, using web scraping techniques. The only purpose of creating it was for academic reasons
End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
DAX
http://www.gnu.org/licenses/lgpl-3.0.htmlhttp://www.gnu.org/licenses/lgpl-3.0.html
The National Stock Exchange of India Ltd. (NSE) is an Indian stock exchange located at Mumbai, Maharashtra, India. National Stock Exchange (NSE) was established in 1992 as a demutualized electronic exchange. It was promoted by leading financial institutions on request of the Government of India. It is India’s largest exchange by turnover. In 1994, it launched electronic screen-based trading. Thereafter, it went on to launch index futures and internet trading in 2000, which were the first of its kind in the country.
With the help of NSE, you can trade in the following segments:
Equities
Indices
Mutual Funds
Exchange Traded Funds
Initial Public Offerings
Security Lending and Borrowing Scheme
https://cdn6.newsnation.in/images/2019/06/24/Sharemarket-164616041_6.jpg" alt="Stock image">
Companies on successful IPOs gets their Stocks traded over different Stock Exchnage platforms. NSE is one important platofrm in India. There are thousands of companies trading their stocks in NSE. But, I have chosen two popular and high rated IT service companies of India; TCS and INFOSYS. and the third one is the benchmark for Indian IT companies , i.e. NIFTY_IT_INDEX .
The dataset contains three csv files. Each resembling to INFOSYS, NIFTY_IT_INDEX, and TCS, respectively. One can easily identify that by the name of CSV files.
Timeline of Data recording : 1-1-2015 to 31-12-2015.
Source of Data : Official NSE website.
Method : We have used the NSEpy api to fetch the data from NSE site. I have also mentioned my approach in this Kernel - "**WebScraper to download data for NSE**". Please go though that to better understand the nature of this dataset.
INFOSYS - 248 x 15 || NIFTY_IT_INDEX - 248 x 7 || **TCS - 248 x 15
Colum Descriptors:
Date
: date on which data is recorded
Symbol
: NSE symbol of the stock
Series
: Series of that stock | EQ - Equity
OTHER SERIES' ARE:
EQ: It stands for Equity. In this series intraday trading is possible in addition to delivery.
BE: It 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.
BL: This series is for facilitating block deals. Block deal is a trade, with a minimum quantity of 5 lakh shares or minimum value of Rs. 5 crore, executed through a single transaction, on the special “Block Deal window”. The window is opened for only 35 minutes in the morning from 9:15 to 9:50AM.
BT: This series provides an exit route to small investors having shares in the physical form with a cap of maximum 500 shares.
GC: This series allows Government Securities and Treasury Bills to be traded under this category.
IL: This series allows only FIIs to trade among themselves. Permissible only in those securities where maximum permissible limit for FIIs is not breached.
Prev Close
: Last day close point
Open
: current day open point
High
: current day highest point
Low
: current day lowest point
Last
: the final quoted trading price for a particular stock, or stock-market index, during the most recent day of trading.
Close
: Closing point for the current day
VWAP
: volume-weighted average price is the ratio of the value traded to total volume traded over a particular time horizon
Volume
: the amount of a security that was traded during a given period of time. For every buyer, there is a seller, and each
transaction contributes to the count of total volume.
Turnover
: Total Turnover of the stock till that day
Trades
: Number of buy or Sell of the stock.
Deliverable
: Volumethe quantity of shares which actually move from one set of people (who had those shares in their demat account before today and are selling today) to another set of people (who have purchased those shares and will get those shares by T+2 days in their demat account).
%Deliverble
: percentage deliverables of that stock
I woul dlike to acknowledge all my sincere thanks to the brains behind NSEpy api, and in particular SWAPNIL JARIWALA , who is also maintaining an amazing open source github repo for this api.
I have also built a starter kernel for this dataset. You can find that right here .
I am so excited to see your magical approaches for the same dataset.
End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The main stock market index of United States, the US500, fell to 6238 points on August 1, 2025, losing 1.60% from the previous session. Over the past month, the index has climbed 0.17% and is up 16.67% compared to the same time last year, 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 August of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States US: Stocks Traded: Total Value data was reported at 39,785.881 USD bn in 2017. This records a decrease from the previous number of 42,071.330 USD bn for 2016. United States US: Stocks Traded: Total Value data is updated yearly, averaging 17,934.293 USD bn from Dec 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 47,245.496 USD bn in 2008 and a record low of 1,108.421 USD bn in 1984. United States US: Stocks Traded: Total Value data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; 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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset is about stocks. It has 451 rows and is filtered where the exchange is Stock Exchange of Thailand. It features 8 columns including stock name, company, exchange, and exchange symbol.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Stock Market Tweets Data
Overview
This dataset is the same as the Stock Market Tweets Data on IEEE by Bruno Taborda.
Data Description
This dataset contains 943,672 tweets collected between April 9 and July 16, 2020, using the S&P 500 tag (#SPX500), the references to the top 25 companies in the S&P 500 index, and the Bloomberg tag (#stocks).
Dataset Structure
created_at: The exact time this tweet was posted. text: The text of the tweet, providing… See the full description on the dataset page: https://huggingface.co/datasets/StephanAkkerman/stock-market-tweets-data.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Greece's main stock market index, the Athens General, fell to 1960 points on August 1, 2025, losing 1.73% from the previous session. Over the past month, the index has climbed 3.49% and is up 36.98% 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 August of 2025.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This Stock Market Dataset is designed for predictive analysis and machine learning applications in financial markets. It includes 13647 records of simulated stock trading data with features commonly used in stock price forecasting.
🔹 Key Features Date – Trading day timestamps (business days only) Open, High, Low, Close – Simulated stock prices Volume – Trading volume per day RSI (Relative Strength Index) – Measures market momentum MACD (Moving Average Convergence Divergence) – Trend-following momentum indicator Sentiment Score – Simulated market sentiment from financial news & social media Target – Binary label (1: Price goes up, 0: Price goes down) for next-day prediction This dataset is useful for training hybrid deep learning models such as LSTM, CNN, and Attention-based networks for stock market forecasting. It enables financial analysts, traders, and AI researchers to experiment with market trends, technical analysis, and sentiment-based predictions.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Hascol
End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset is about stocks. It has 25 rows and is filtered where the exchange is Vilnius Stock Exchange. It features 8 columns including stock name, company, exchange, and exchange symbol.
https://academictorrents.com/nolicensespecifiedhttps://academictorrents.com/nolicensespecified
4974 Stock Symbols End of day data. Includes close open high low volume and date. Data was collected from Google finance public data. +—————+——————+ | Table | Size in MB | +—————+——————+ | surf_eod | 1109.00 | +—————+——————+ 1 row in set (0.00 sec) mysql> SELECT COUNT(DISTINCT( ticker )) FROM surf_eod; +—————————————-+ | COUNT(DISTINCT( ticker )) | +—————————————-+ | 4974 | +—————————————-+ 1 row in set (6.31 sec) mysql> describe surf_eod; +————+——————-+—&mdash
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
This table contains 14 series, with data starting from 1953 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Stock market statistics (14 items: Toronto Stock Exchange; value of shares traded; United States common stocks; Dow-Jones industrials; high; United States common stocks; Dow-Jones industrials; low; Toronto Stock Exchange; volume of shares traded ...).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United Kingdom's main stock market index, the GB100, fell to 9069 points on August 1, 2025, losing 0.70% from the previous session. Over the past month, the index has climbed 3.35% and is up 10.93% compared to the same time last year, 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 August of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset is about stocks. It has 969 rows and is filtered where the exchange is Sao Paolo Stock Exchange. It features 8 columns including stock name, company, exchange, and exchange symbol.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
Global Top Index: Exploring Trends in Stock Markets
About the Dataset
The Global Top Index dataset offers a detailed view of daily trading activities from several of the world's leading stock market indices. This dataset is ideal for conducting comprehensive analyses to uncover insights and predictive trends in the international stock markets.
Dataset Contents
The dataset encompasses the following key data points for each trading session across multiple dates… See the full description on the dataset page: https://huggingface.co/datasets/pettah/global-top-Index-exploring-trends-in-stock-Market.
https://brightdata.com/licensehttps://brightdata.com/license
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.