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The global Stock Market API market is experiencing robust growth, driven by the increasing demand for real-time and historical financial data across various sectors. The proliferation of algorithmic trading, quantitative analysis, and the development of sophisticated financial applications are key factors fueling this expansion. The market is segmented by deployment (cloud-based and on-premises) and user type (SMEs and large enterprises), with cloud-based solutions gaining significant traction due to their scalability, cost-effectiveness, and accessibility. Large enterprises, with their extensive data processing needs and investment in advanced analytics, currently dominate the market share, but the SME segment is exhibiting impressive growth potential as access to affordable and user-friendly APIs becomes increasingly widespread. Geographic expansion is also a significant driver, with North America and Europe holding substantial market shares, while Asia-Pacific is emerging as a rapidly growing region fueled by increasing technological adoption and economic expansion. While competitive pressures from numerous providers and data security concerns present some restraints, the overall market outlook remains highly positive, projected to maintain a strong Compound Annual Growth Rate (CAGR) over the forecast period (2025-2033). The competitive landscape is characterized by a diverse range of established players and emerging startups. Established players like Refinitiv and Bloomberg offer comprehensive data solutions, while smaller companies like Alpha Vantage and Marketstack provide specialized APIs focusing on specific data sets or user needs. This competitive environment fosters innovation, driving the development of new features and capabilities within Stock Market APIs. The increasing demand for integrated data solutions—combining market data with alternative data sources—is another key trend shaping the market. Future growth will likely be fueled by the expansion of fintech, the rise of robo-advisors, and increasing adoption of APIs in academic research and financial education. The market's continued evolution necessitates ongoing adaptation and innovation from both established players and new entrants to cater to the evolving needs of a dynamic and technology-driven financial ecosystem. This ongoing innovation and increasing demand will drive the market to significant growth over the next decade.
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The best choice for those looking for license-free US market data for commercial use is US Equities Basic, which includes data display, redistribution, professional trading, and more.
US Equities Basic is based upon a derived IEX feed. The volume coverage is 3-5% of the total trading volume in North America, which helps entities mitigate license expenses and start with real-time data.
US Equities Basic provides raw quotes, trades, aggregated time series (OHLCV), and snapshots. Both REST API and WebSocket API are available.
End-of-day price information disseminated after 12:00 AM EST does not require licensing in the United States by law. This applies to all exchanges, even those not included in the US Equities Basic. Finazon combines all price information after every trading day, meaning that while markets are open, real-time prices are available from a subset of exchanges, and when markets close, data is synced and contains 100% of US volume. All historical prices are adjusted for corporate actions and splits.
Tip: Individuals with non-professional usage are not required to get exchange licenses for real-time data and, hence, are better off with the US Equities Max dataset.
Finnhub is the ultimate stock api in the market, providing real-time and historical price for global stocks with Rest API and websocket. We also support a tons of other financial data like stock fundamentals, analyst estimates, fundamental data and more. Download the file to access balance sheet of Amazon.
Twelve Data is a technology-driven company that provides financial market data, financial tools, and dedicated solutions. Large audiences - from individuals to financial institutions - use our products to stay ahead of the competition and success.
At Twelve Data we feel responsible for where the markets are going and how people are able to explore them. Coming from different technological backgrounds, we see how the world is lacking the unique and simple place where financial data can be accessed by anyone, at any time. This is what distinguishes us from others, we do not only supply the financial data but instead, we want you to benefit from it, by using the convenient format, tools, and special solutions.
We believe that the human factor is still a very important aspect of our work and therefore our ethics guides us on how to treat people, with convenient and understandable resources. This includes world-class documentation, human support, and dedicated solutions.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
API Crude Oil Stock Change in the United States increased to 1.54 BBL/1Million in July 25 from -0.58 BBL/1Million in the previous week. This dataset provides - United States API Crude Oil Stock Change- actual values, historical data, forecast, chart, statistics, economic calendar and news.
Eximpedia Export import trade data lets you search trade data and active Exporters, Importers, Buyers, Suppliers, manufacturers exporters from over 209 countries
Data on petroleum and crude oil stocks. Weekly, monthly, and annual data available. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
API Distillate Stocks in the United States increased to 0.80 BBL/1Million in July 11 from -0.80 BBL/1Million in the previous week. This dataset provides - United States API Distillate Stocks Change- actual values, historical data, forecast, chart, statistics, economic calendar and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Free-Cash-Flow-To-Equity Time Series for Api Group Corp. APi Group Corporation provides safety and specialty services worldwide. The company offers end-to-end integrated occupancy systems, such as fire protection services; heating, ventilation, and air conditioning solutions; and entry systems, elevators, and escalators, including design, installation, inspection, and service of these integrated systems. It also provides various infrastructure and specialized industrial plant services comprising maintenance and repair of underground electric, gas, water, sewer, and telecommunications infrastructure; engineering and design, fabrication, installation, maintenance service and repair, retrofitting and upgrading, pipeline infrastructure, access and road construction, supporting facilities, and integrity management and maintenance. The company serves commercial, education, healthcare, high tech, industrial, and special-hazard settings, as well as private and public utilities, communications, healthcare, education, transportation, manufacturing, industrial plants and governmental agencies. The company was formerly known as J2 Acquisition Limited and changed its name to APi Group Corporation in October 2019. APi Group Corporation was founded in 1926 and is headquartered in New Brighton, Minnesota.
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.
Eximpedia Export import trade data lets you search trade data and active Exporters, Importers, Buyers, Suppliers, manufacturers exporters from over 209 countries
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
API Gasoline Stocks in the United States increased to 1.90 BBL/1Million in July 11 from -2.20 BBL/1Million in the previous week. This dataset provides - United States Api Gasoline Stocks- actual values, historical data, forecast, chart, statistics, economic calendar and news.
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This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.
Historical daily stock prices (open, high, low, close, volume)
Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)
Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)
Feature engineering based on financial data and technical indicators
Sentiment analysis data from social media and news articles
Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
Researchers investigating the effectiveness of machine learning in stock market prediction
Analysts developing quantitative trading Buy/Sell strategies
Individuals interested in building their own stock market prediction models
Students learning about machine learning and financial applications
The dataset may include different levels of granularity (e.g., daily, hourly)
Data cleaning and preprocessing are essential before model training
Regular updates are recommended to maintain the accuracy and relevance of the data
https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html
This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.
Historical daily stock prices (open, high, low, close, volume)
Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)
Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)
Feature engineering based on financial data and technical indicators
Sentiment analysis data from social media and news articles
Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
Researchers investigating the effectiveness of machine learning in stock market prediction
Analysts developing quantitative trading Buy/Sell strategies
Individuals interested in building their own stock market prediction models
Students learning about machine learning and financial applications
The dataset may include different levels of granularity (e.g., daily, hourly)
Data cleaning and preprocessing are essential before model training
Regular updates are recommended to maintain the accuracy and relevance of the data
Twelve Data is a technology-driven company that provides financial market data, financial tools, and dedicated solutions. Large audiences - from individuals to financial institutions - use our products to stay ahead of the competition and success.
At Twelve Data we feel responsible for where the markets are going and how people are able to explore them. Coming from different technological backgrounds, we see how the world is lacking the unique and simple place where financial data can be accessed by anyone, at any time. This is what distinguishes us from others, we do not only supply the financial data but instead, we want you to benefit from it, by using the convenient format, tools, and special solutions.
We believe that the human factor is still a very important aspect of our work and therefore our ethics guides us on how to treat people, with convenient and understandable resources. This includes world-class documentation, human support, and dedicated solutions.
Global Stock Market Data. More than 150 pricing sources, including biggest world stock exchanges. Pay only for the stock exchanges, parameters or regions you need. Flexible in customizing our product to the customer's needs. Free test access as long as you need for integration. Reliable sources: stock exchanges and market participants. The cost depends on the amount of required parameters and re-distribution right.
Eximpedia Export import trade data lets you search trade data and active Exporters, Importers, Buyers, Suppliers, manufacturers exporters from over 209 countries
This dataset contains Weekly U.S. Ending Stocks of Distillate Fuel Oil 2015-2022. Data from US Energy information administration.This series is available through the EIA open data API and can be downloaded to Excel or embedded as an interactive chart or map on your website.
Eximpedia Export import trade data lets you search trade data and active Exporters, Importers, Buyers, Suppliers, manufacturers exporters from over 209 countries
The Dataset here consists of Stock Value of Apple(AAPL) and Microsoft(MSFT) from 2006 to 2016 and News summary, abstract and snippets on News featuring these two tech giants during the same period. We are trying to understand and depict the impact of News stories on the stock prices. The News snippets, summary and abstracted were retrieved from The New York Times API. The stock values were obtained from Yahoo Finance.
The final data set is created by applying sentiment analysis on those News string and converting them into a score. For this purpose, Natural Language Toolkit(NLTK) was used. The final dataset were further used for a Regression Model.
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The global Stock Market API market is experiencing robust growth, driven by the increasing demand for real-time and historical financial data across various sectors. The proliferation of algorithmic trading, quantitative analysis, and the development of sophisticated financial applications are key factors fueling this expansion. The market is segmented by deployment (cloud-based and on-premises) and user type (SMEs and large enterprises), with cloud-based solutions gaining significant traction due to their scalability, cost-effectiveness, and accessibility. Large enterprises, with their extensive data processing needs and investment in advanced analytics, currently dominate the market share, but the SME segment is exhibiting impressive growth potential as access to affordable and user-friendly APIs becomes increasingly widespread. Geographic expansion is also a significant driver, with North America and Europe holding substantial market shares, while Asia-Pacific is emerging as a rapidly growing region fueled by increasing technological adoption and economic expansion. While competitive pressures from numerous providers and data security concerns present some restraints, the overall market outlook remains highly positive, projected to maintain a strong Compound Annual Growth Rate (CAGR) over the forecast period (2025-2033). The competitive landscape is characterized by a diverse range of established players and emerging startups. Established players like Refinitiv and Bloomberg offer comprehensive data solutions, while smaller companies like Alpha Vantage and Marketstack provide specialized APIs focusing on specific data sets or user needs. This competitive environment fosters innovation, driving the development of new features and capabilities within Stock Market APIs. The increasing demand for integrated data solutions—combining market data with alternative data sources—is another key trend shaping the market. Future growth will likely be fueled by the expansion of fintech, the rise of robo-advisors, and increasing adoption of APIs in academic research and financial education. The market's continued evolution necessitates ongoing adaptation and innovation from both established players and new entrants to cater to the evolving needs of a dynamic and technology-driven financial ecosystem. This ongoing innovation and increasing demand will drive the market to significant growth over the next decade.