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.

AXISBANK OHLCV Data: Multi-Interval Historical Stock Prices (NSE)

Overview

This dataset provides comprehensive historical Open, High, Low, Close, and Volume (OHLCV) data for Axis Bank (AXISBANK), a prominent Indian stock listed on the National Stock Exchange (NSE). The data has been consolidated from various time intervals (1-minute, 5-minute, 15-minute, and 1-day), offering a granular yet unified view for diverse analytical needs, from high-frequency trading simulations to long-term trend analysis.

Data Source

The raw data was collected programmatically using the Groww API. The specific API endpoint used for fetching charting data is: https://groww.in/v1/api/charting_service/v4/chart/exchange/NSE/segment/CASH. While efforts have been made during data fetching and consolidation to ensure accuracy, please be aware that financial data can sometimes be subject to minor corrections or revisions by data providers.

Dataset Contents

This dataset is provided as a single, unified CSV file (e.g., unified_axisbank_ohlcv_data.csv), which has been consolidated from multiple JSON files representing different time intervals (1m, 5m, 15m, 1d).

The unified CSV file contains the following columns:

• Symbol: The stock ticker symbol (AXISBANK).
• Interval: The original time interval of the candle (1m, 5m, 15m, 1d).
• DateTime: The human-readable timestamp of the candle (derived from Unix Timestamp, e.g., YYYY-MM-DD HH:MM:SS).
• Open: The opening price of the stock during that interval.
• High: The highest price reached during that interval.
• Low: The lowest price reached during that interval.
• Close: The closing price of the stock during that interval.
• Volume: The trading volume (number of shares traded) during that interval.
• Timestamp: The raw Unix timestamp.

Overall Date Range and Record Count: The exact historical date range and total number of records for the complete dataset depend on the full content and consolidation process of the original JSON files. Your conversion script will provide the precise earliest and latest dates, as well as the total number of records in this unified CSV file. Based on the original file snippets, the data appears to span from at least mid-2022 into mid-2025.

Potential Use Cases

This dataset can be highly valuable for various applications in quantitative finance and data science, including: * Algorithmic Trading Strategy Development: Backtesting and optimizing trading strategies across different timeframes for AXISBANK. * Technical Analysis: Generating charts, calculating technical indicators (e.g., Moving Averages, RSI, MACD, Bollinger Bands) specific to AXISBANK. * Machine Learning for Price Prediction: Training models to forecast future stock prices, trends, or volatility for AXISBANK. * Market Trend Analysis: Studying short-term and long-term market behavior, liquidity, and price action of Axis Bank. * Educational Purposes: A clean, multi-interval dataset ideal for learning and practicing data analysis with financial time series.

Disclaimer

This dataset is provided for informational and educational purposes only. It should not be considered financial advice, investment recommendations, or a solicitation to buy or sell any securities. Trading and investing in financial markets involve significant risk, and past performance is not indicative of future results. Always conduct your own thorough research and consult with a qualified financial advisor before making any investment decisions. The creators of this dataset are not liable for any losses incurred from its use.

Cryptocurrencies

Finage offers you more than 1700+ cryptocurrency data in real time.

With Finage, you can react to the cryptocurrency data in Real-Time via WebSocket or unlimited API calls. Also, we offer you a 7-year historical data API.

You can view the full Cryptocurrency market coverage with the link given below. https://finage.s3.eu-west-2.amazonaws.com/Finage_Crypto_Coverage.pdf

Update

Unfortunately, the API this dataset used to pull the stock data isn't free anymore. Instead of having this auto-updating, I dropped the last version of the data files in here, so at least the historic data is still usable.

Content

This dataset provides free end of day data for all stocks currently in the Dow Jones Industrial Average. For each of the 30 components of the index, there is one CSV file named by the stock's symbol (e.g. AAPL for Apple). Each file provides historically adjusted market-wide data (daily, max. 5 years back). See here for description of the columns: https://iextrading.com/developer/docs/#chart

Since this dataset uses remote URLs as files, it is automatically updated daily by the Kaggle platform and automatically represents the latest data.

Acknowledgements

List of stocks and symbols as per https://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average

Thanks to https://iextrading.com for providing this data for free!

Terms of Use

Data provided for free by IEX. View IEX’s Terms of Use.

API Crude Oil Stock Change in the United States decreased to -3.42 BBL/1Million in September 12 from 1.25 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.

Sports Data API Market size was valued at USD 4.78 Billion in 2024 and is projected to reach USD 31.13 Billion by 2032, growing at a CAGR of 26.4% during the forecast period 2026 to 2032. Real-time sports analytics are being increasingly sought after by teams and broadcasters. Instant access to performance data and insights is being used to enhance strategies and improve fan engagement.Fantasy sports platforms are being widely adopted by sports fans globally. APIs are being used to provide detailed player stats and performance metrics, enriching the fantasy sports experience.

Smart Insider’s Global Share Buyback Database offers invaluable insights to investors on public equity market data. We provide detailed, up-to-date share buyback data covering over 55,000 companies globally including Africa, that’s every company that reports Buybacks through regulatory processes.

Our Share buyback data includes detailed information on all major buyback transactions including source announcements and derived analysis fields. Our platform adds a visual representation of the data, allowing investors to quickly identify patterns and make decisions based on their findings.

Get detailed share buyback insights with Smart Insider and stay ahead of the curve with accurate, historical buyback insight that helps you make better investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as CSV, XML or XLSX via SFTP, API or Snowflake.

Sample dataset for Desktop Service has been provided with limited fields. Upon request, we can provide a detailed Quant sample.

Tags: Equity Market Data, Stock Market Data, Corporate Actions Data, Corporate Buyback Data, Company Financial Data, Insider Trading Data, Africa

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.

Forex Symbols

Finage offers you more than 1300+ forex data as real-time.

With Finage, you can react to the forex data in Real-Time via WebSocket or unlimited API calls. Also, we offer you a 15-year historical data API.

Commodities Bonds Metals Forex You can view the full FX market coverage with the link given below. https://finage.s3.eu-west-2.amazonaws.com/Finage_FX_Symbol_List.pdf

Cryptocurrency historical datasets from January 2012 (if available) to October 2021 were obtained and integrated from various sources and Application Programming Interfaces (APIs) including Yahoo Finance, Cryptodownload, CoinMarketCap, various Kaggle datasets, and multiple APIs. While these datasets used various formats of time (e.g., minutes, hours, days), in order to integrate the datasets days format was used for in this research study. The integrated cryptocurrency historical datasets for 80 cryptocurrencies including but not limited to Bitcoin (BTC), Ethereum (ETH), Binance Coin (BNB), Cardano (ADA), Tether (USDT), Ripple (XRP), Solana (SOL), Polkadot (DOT), USD Coin (USDC), Dogecoin (DOGE), Tron (TRX), Bitcoin Cash (BCH), Litecoin (LTC), EOS (EOS), Cosmos (ATOM), Stellar (XLM), Wrapped Bitcoin (WBTC), Uniswap (UNI), Terra (LUNA), SHIBA INU (SHIB), and 60 more cryptocurrencies were uploaded in this online Mendeley data repository. Although the primary attribute of including the mentioned cryptocurrencies was the Market Capitalization, a subject matter expert i.e., a professional trader has also guided the initial selection of the cryptocurrencies by analyzing various indicators such as Relative Strength Index (RSI), Moving Average Convergence/Divergence (MACD), MYC Signals, Bollinger Bands, Fibonacci Retracement, Stochastic Oscillator and Ichimoku Cloud. The primary features of this dataset that were used as the decision-making criteria of the CLUS-MCDA II approach are Timestamps, Open, High, Low, Closed, Volume (Currency), % Change (7 days and 24 hours), Market Cap and Weighted Price values. The available excel and CSV files in this data set are just part of the integrated data and other databases, datasets and API References that was used in this study are as follows: [1] https://finance.yahoo.com/ [2] https://coinmarketcap.com/historical/ [3] https://cryptodatadownload.com/ [4] https://kaggle.com/philmohun/cryptocurrency-financial-data [5] https://kaggle.com/deepshah16/meme-cryptocurrency-historical-data [6] https://kaggle.com/sudalairajkumar/cryptocurrencypricehistory [7] https://min-api.cryptocompare.com/data/price?fsym=BTC&tsyms=USD [8] https://min-api.cryptocompare.com/ [9] https://p.nomics.com/cryptocurrency-bitcoin-api [10] https://www.coinapi.io/ [11] https://www.coingecko.com/en/api [12] https://cryptowat.ch/ [13] https://www.alphavantage.co/ This dataset is part of the CLUS-MCDA (Cluster analysis for improving Multiple Criteria Decision Analysis) and CLUS-MCDAII Project: https://aimaghsoodi.github.io/CLUSMCDA-R-Package/ https://github.com/Aimaghsoodi/CLUS-MCDA-II https://github.com/azadkavian/CLUS-MCDA

Description

This project involves collecting and analyzing financial data for Apple Inc. (AAPL) using the Alpha Vantage API. The data includes historical stock prices, dividend payments, and stock splits, aiming to provide a comprehensive view of Apple's financial performance and corporate actions over time.

Detail

The project consists of three main datasets:

Stock Price Data: Daily records of AAPL’s stock prices, including opening, high, low, and closing prices, as well as trading volume.

Dividend Data: Historical records of dividend payments by AAPL, detailing declaration dates, record dates, payment dates, and dividend amounts.

Stock Split Data: Records of stock split events, showing the date of each split and the split ratio.

The data is sourced from the Alpha Vantage API, which provides comprehensive financial market data. The datasets are cleaned and formatted to ensure consistency and accuracy, then saved in CSV files for easy access and analysis.

Usage

The collected data can be used for various financial analyses and insights:

Stock Price Analysis: Evaluate AAPL’s stock price trends, volatility, and trading volumes over time.

Dividend Analysis: Analyze dividend payment trends, yield, and changes in dividend policy.

Stock Split Analysis: Understand the impact of stock splits on AAPL’s stock price and overall market behavior.

This data can be used by investors, financial analysts, and researchers to make informed decisions or conduct further financial research. It can also be integrated into financial models or visualizations to provide a clearer picture of Apple’s financial health and corporate actions.

Summary

The project provides a detailed dataset of Apple Inc.’s financial data, including stock prices, dividends, and stock splits. By sourcing data from the Alpha Vantage API and carefully formatting it, the project offers valuable insights into Apple’s historical financial performance. The data is organized into CSV files, making it accessible for analysis, research, and decision-making purposes.

Smart Insider’s Global Share Buyback Database offers invaluable insights to investors on corporate actions data. We provide detailed, up-to-date share buyback data covering over 55,000 companies globally and over 20K+ from Asia, that’s every company that reports Buybacks through regulatory processes.

Our Share buyback data includes detailed information on all major buyback transactions including source announcements and derived analysis fields. Our platform adds a visual representation of the data, allowing investors to quickly identify patterns and make decisions based on their findings.

Get detailed share buyback insights with Smart Insider and stay ahead of the curve with accurate, historical buyback insight that helps you make better investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as CSV, XML or XLSX via SFTP, API or Snowflake.

Sample dataset for Desktop Service has been provided with limited fields. Upon request, we can provide a detailed Quant sample.

Tags: Equity Market Data, Stock Market Data, Corporate Actions Data, Corporate Buyback Data, Company Financial Data, Insider Trading Data

Snapshot img

API Management Market Size 2025-2029

The API management market size is forecast to increase by USD 3.75 billion at a CAGR of 12.3% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing adoption of digital payment solutions and the proliferation of digital wallets. However, challenges persist, including poor internet connectivity in developing countries, which can hinder the adoption and effective implementation of Api Management solutions. Companies must navigate these challenges to capitalize on the market's potential. Strategies such as investing in offline solutions and partnering with local providers can help overcome connectivity issues and expand market reach.
Additionally, focusing on security and scalability will be crucial, as businesses demand reliable and secure Api Management solutions to support their digital initiatives. These trends reflect the digital transformation underway in various industries, as businesses seek to enhance customer experience and streamline operations. Overall, the market presents opportunities for innovation and growth, with companies that address the unique challenges of this dynamic landscape poised to succeed.

What will be the Size of the API Management Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

The market is experiencing significant innovation, with a focus on enhancing API Return on Investment (ROI) through multi-cloud API adoption and API-driven development. API maturity is on the rise, driving the need for advanced API logging, performance benchmarking, and usage analytics. API interoperability and standardization are crucial to addressing integration challenges in complex API ecosystems. API observability and developer experience are becoming key differentiators, with the emergence of API documentation generators and debugging tools. API adoption rates continue to grow, fueled by the increasing use of composite and hybrid cloud APIs, serverless functions, and microservices orchestration.

The market is experiencing significant growth, driven by the increasing adoption of digital payment solutions and the proliferation of digital wallets. API platform comparisons and compliance are essential for businesses navigating the diverse landscape of API offerings. API monetization strategies, such as API-led connectivity and edge computing APIs, are gaining traction. API evolution is ongoing, with a shift towards API-first design and headless CMS integration. API usage patterns are evolving, requiring new testing frameworks and security measures to address API performance optimization and vulnerabilities. Ultimately, API governance policies and discovery tools are essential for managing the complexities of API consumption and ensuring compliance in the dynamic API market.

How is this API Management Industry segmented?

The api management industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Deployment

  Cloud
  On-premises


Solution

  API gateways
  API lifecycle management
  API security
  API analytics and monitoring
  API developer portals


End-user

  Large enterprises
  SMEs


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  Middle East and Africa

    UAE


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Deployment Insights

The cloud segment is estimated to witness significant growth during the forecast period. The market is experiencing significant growth, driven by the digital transformation sweeping across industries. Cloud-based API solutions dominate the market, enabling seamless communication and data transfer between applications and the cloud. This segment's dominance is attributed to the proliferation of IoT and Big Data, which enhance application interfaces for superior customer experiences. Additionally, the increasing awareness of security vulnerabilities and the demand for automation have fueled the market's expansion in sectors like BFSI, e-commerce, healthcare and life sciences, education, and retail. Cloud APIs facilitate the integration of various cloud and on-premises applications, simplifying API provisioning, activation, setup, monitoring, and troubleshooting for developers and administrators.

Agile development methodologies, such as DevOps and CI/CD, have further accelerated the adoption of cloud APIs. APIs have become essential components of modern application architectures, including microservices, event-driven, and real-time systems. GraphQL APIs and service meshes have emerged as popu

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.

The global API management market size was estimated at USD 5.4 billion in 2021 and is predicted to surpass over USD 47 billion by 2030 and poised to reach at a CAGR of 31.1% during the forecast period 2022 to 2030

The ETF Holdings API provides data on small-cap, mid-cap and large-cap ETFs. When you choose the group of ETFs you want to obtain data on, you can select their stock ticker symbols as a filtering parameter, so that Tradefeeds systems provides you with the desired data. The ETF data collected in Tradefeeds ETF Holdings Database is sourced from reliable partners in the financial industry: investments funds, brokerages and financial advisors. You can get current and historical ETF holdings data in a JSON format or excel and CSV file.

The Sports Data API market is experiencing robust growth, fueled by the increasing popularity of sports betting, fantasy sports, and the broader digitalization of the sports industry. The market's expansion is driven by the rising demand for real-time, accurate, and comprehensive sports data among various stakeholders, including sportsbooks, media companies, fantasy sports platforms, and app developers. Technological advancements, particularly in data analytics and machine learning, are enabling the creation of more sophisticated and valuable data products, further stimulating market growth. The integration of data APIs into existing platforms is becoming increasingly seamless, lowering the barrier to entry for businesses looking to leverage sports data. Competition is fierce, with established players like Sportradar and Genius Sports facing challenges from agile newcomers and specialized providers focusing on niche sports or data types. This competitive landscape fosters innovation and drives down prices, making sports data more accessible to a wider range of users. Despite the strong growth, the market faces challenges such as data security concerns, regulatory complexities related to gambling, and the need for consistent data standardization across different sports and leagues. The market is segmented by data type (e.g., live scores, player statistics, historical results), sport (e.g., soccer, basketball, American football), and customer type (e.g., media, gaming, betting). Geographic distribution shows significant traction in North America and Europe, but Asia-Pacific and other emerging markets are expected to witness rapid growth due to the expanding digital economy and rising interest in sports. While precise figures for market size and CAGR are not provided, a conservative estimate based on industry reports and comparable sectors indicates a market size of approximately $2 billion in 2025, growing at a compound annual growth rate (CAGR) of around 15% between 2025 and 2033. This projection reflects the ongoing technological advancements and the increasing demand for sophisticated sports data analytics capabilities. The forecast period (2025-2033) will likely see significant consolidation and strategic partnerships among existing players and further expansion of the market's geographical reach.

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Finage offers you a public server, VPS, and dedicated server for your applications. Edit, manage and build your own plans on your private server. Change the incoming data structure in minutes.

The IvyDB Signed Volume dataset, available as an add-on product for IvyDB US, contains daily data on detailed option trading volume. Trades in the IvyDB US dataset are assigned as either buyer-initiated or seller-initiated based on the trade price and the bid-ask quote at the time of the trade. The total assigned daily volume is aggregated and updated nightly.

The Semaglutide API market is experiencing significant growth driven by the rising prevalence of obesity and type 2 diabetes globally. Semaglutide, a glucagon-like peptide-1 (GLP-1) receptor agonist, is predominantly used in diabetes management and weight loss therapies, offering effective solutions for patients str