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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.
The date for every symbol is saved in CSV format with common fields:
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.
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Use our Stock prices 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.
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The main stock market index of United States, the US500, rose to 6467 points on August 22, 2025, gaining 1.52% from the previous session. Over the past month, the index has climbed 1.70% and is up 14.77% 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.
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.
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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.
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Dataset Information
This dataset includes daily price data for various stocks.
Instruments Included
7000+ US Stocks
Dataset Columns
symbol: The symbol of the stock. date: The date of the data. open: The opening price of the stock. high: The highest price of the stock. low: The lowest price of the stock. close: The closing price of the stock. volume: The volume of the stock. adj_close: The adjusted closing price of the stock.
Data Splits
The… See the full description on the dataset page: https://huggingface.co/datasets/paperswithbacktest/Stocks-Daily-Price.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The latest closing stock price for Exxon as of June 27, 2025 is 109.38. An investor who bought $1,000 worth of Exxon stock at the IPO in 1984 would have $41,833 today, roughly 42 times their original investment - a 9.60% compound annual growth rate over 41 years. The all-time high Exxon stock closing price was 122.12 on October 07, 2024. The Exxon 52-week high stock price is 126.34, which is 15.5% above the current share price. The Exxon 52-week low stock price is 97.80, which is 10.6% below the current share price. The average Exxon stock price for the last 52 weeks is 112.58. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The dataset contains historical technical data of Dhaka Stock Exchange (DSE). The data was collected from different sources found in the internet where the data was publicly available. The data available here are used for information and research purposes and though to the best of our knowledge, it does not contain any mistakes, there might still be some mistakes. It is not encourages to use this dataset for portfolio management purposes and use this dataset out of your own interest. The contributors do not hold any liability if it is used for any purposes.
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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.
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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.
We offer three easy-to-understand equity data packages to fit your business needs. Visit intrinio.com/pricing to compare packages.
Bronze
The Bronze package is ideal for developing your idea and prototyping your platform with high-quality EOD equity pricing data, standardized financial statement data, and supplementary fundamental datasets.
When you’re ready for launch, it’s a seamless transition to our Silver package for additional data sets, 15-minute delayed equity pricing data, expanded history, and more.
Bronze Benefits:
Silver
The Silver package is ideal for startups that are in development, testing, or in the beta launch phase. Hit the ground running with 15-minute delayed and historical intraday and EOD equity prices, plus our standardized and as-reported financial statement data with nine supplementary data sets, including insider transactions and institutional ownership.
When you’re ready to scale, easily move up to the Gold package for our full range of data sets and full history, real-time equity pricing data, premium support options, and much more.
Silver Benefits:
Gold
The Gold package is ideal for funded companies that are in the growth or scaling stage, as well as institutions that are innovating within the fintech space. This full-service solution offers our complete collection of equity pricing data feeds, from real-time to historical EOD, plus standardized financial statement data and nine supplementary feeds.
You’ll also have access to our wide range of modern access methods, third-party data via Intrinio’s API with licensing assistance, support from our team of expert engineers, custom delivery architectures, and much more.
Gold Benefits:
Platinum
Don’t see a package that fits your needs? Our team can design premium custom packages for institutions.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The latest closing stock price for TE Connectivity as of June 13, 2025 is 162.62. An investor who bought $1,000 worth of TE Connectivity stock at the IPO in 2007 would have $5,022 today, roughly 5 times their original investment - a 10.49% compound annual growth rate over 18 years. The all-time high TE Connectivity stock closing price was 166.39 on June 10, 2025. The TE Connectivity 52-week high stock price is 167.94, which is 3.3% above the current share price. The TE Connectivity 52-week low stock price is 116.30, which is 28.5% below the current share price. The average TE Connectivity stock price for the last 52 weeks is 149.00. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.
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Graph and download economic data for American Railroad Stock Prices for United States (M1105AUSM505NNBR) from Jan 1857 to Dec 1929 about railroad, equity, and USA.
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France's main stock market index, the FR40, rose to 7970 points on August 22, 2025, gaining 0.40% from the previous session. Over the past month, the index has climbed 1.52% and is up 5.18% 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 August of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Revelyst stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.
As of April 2025, stocks from HYBE Corporation had the highest stock prices among the listed leading K-pop companies in South Korea, at ******* South Korean won per share. This set it apart from the other agencies, with SM Entertainment coming closest at ******* won per share. HYBE Corporation, formerly known as Big Hit Entertainment, is home to the globally popular K-pop group BTS. Having only entered the stock exchange market in 2020, the company has since stayed ahead of its competition.
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License information was derived automatically
DIA stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The latest closing stock price for Arq as of June 13, 2025 is 4.98. An investor who bought $1,000 worth of Arq stock at the IPO in 2003 would have $3,385 today, roughly 3 times their original investment - a 6.95% compound annual growth rate over 22 years. The all-time high Arq stock closing price was 21.95 on November 29, 2013. The Arq 52-week high stock price is 8.11, which is 62.9% above the current share price. The Arq 52-week low stock price is 3.34, which is 32.9% below the current share price. The average Arq stock price for the last 52 weeks is 5.72. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.
The Federal National Mortgage Association, commonly known as Fannie Mae, was created by the U.S. congress in 1938, in order to maintain liquidity and stability in the domestic mortgage market. The company is a government-sponsored enterprise (GSE), meaning that while it was a publicly traded company for most of its history, it was still supported by the federal government. While there is no legally binding guarantee of shares in GSEs or their securities, it is generally acknowledged that the U.S. government is highly unlikely to let these enterprises fail. Due to these implicit guarantees, GSEs are able to access financing at a reduced cost of interest. Fannie Mae's main activity is the purchasing of mortgage loans from their originators (banks, mortgage brokers etc.) and packaging them into mortgage-backed securities (MBS) in order to ease the access of U.S. homebuyers to housing credit. The early 2000s U.S. mortgage finance boom During the early 2000s, Fannie Mae was swept up in the U.S. housing boom which eventually led to the financial crisis of 2007-2008. The association's stated goal of increasing access of lower income families to housing finance coalesced with the interests of private mortgage lenders and Wall Street investment banks, who had become heavily reliant on the housing market to drive profits. Private lenders had begun to offer riskier mortgage loans in the early 2000s due to low interest rates in the wake of the "Dot Com" crash and their need to maintain profits through increasing the volume of loans on their books. The securitized products created by these private lenders did not maintain the standards which had traditionally been upheld by GSEs. Due to their market share being eaten into by private firms, however, the GSEs involved in the mortgage markets began to also lower their standards, resulting in a 'race to the bottom'. The fall of Fannie Mae The lowering of lending standards was a key factor in creating the housing bubble, as mortgages were now being offered to borrowers with little or no ability to repay the loans. Combined with fraudulent practices from credit ratings agencies, who rated the junk securities created from these mortgage loans as being of the highest standard, this led directly to the financial panic that erupted on Wall Street beginning in 2007. As the U.S. economy slowed down in 2006, mortgage delinquency rates began to spike. Fannie Mae's losses in the mortgage security market in 2006 and 2007, along with the losses of the related GSE 'Freddie Mac', had caused its share value to plummet, stoking fears that it may collapse. On September 7th 2008, Fannie Mae was taken into government conservatorship along with Freddie Mac, with their stocks being delisted from stock exchanges in 2010. This act was seen as an unprecedented direct intervention into the economy by the U.S. government, and a symbol of how far the U.S. housing market had fallen.
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License information was derived automatically
Airbnb Stock Price dataset
A simple dataset containing 746 rows of Airbnb's stock price.
Dataset structure
date (float64): Date of the stock price expressed as the epoch from 1/1/1970. open (float64): Price of the stock when the stock market opened. close_last (float64): Price of the stock when the stock market closed. volume (float64): Number of shares traded. high (float64): Highest price of the stock during the day. low (float64): Lowest price of the stock during the… See the full description on the dataset page: https://huggingface.co/datasets/BatteRaquette58/airbnb-stock-price.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
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.
The date for every symbol is saved in CSV format with common fields:
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.