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

Treasury yield curves or treasury zero-coupon yield curve are derived from treasury benchmark curves. The main interest in the market to estimate treasury yield curves is to provide insights into the evolution of market expectations.

The zero coupon rate or zero rate, the most common form of interest rate, is the yield implied by the different between a zero coupon bond's current purchase price and the value it pays at maturity. A given zero rate applies only to a single point in the future and, as such, can only be used to discount cash flows occurring on this date. Zero rates can have different compoundings: continuously, semi-annually, annually, etc. The continuously compounded zero rate has the simplest expression and computation mathematically.

Real-Time Bank Feed APIs Market Outlook

According to our latest research, the global Real-Time Bank Feed APIs market size reached USD 2.14 billion in 2024, reflecting robust adoption across banking and financial sectors. The market is projected to grow at a CAGR of 19.2% from 2025 to 2033, reaching an estimated USD 10.78 billion by 2033. This impressive growth trajectory is primarily driven by the increasing demand for seamless financial data integration, enhanced digital banking experiences, and the need for real-time transaction processing in a globally interconnected financial ecosystem.

One of the key growth factors fueling the Real-Time Bank Feed APIs market is the accelerating digital transformation initiatives within the banking and financial services industry. Banks and financial institutions are under immense pressure to modernize their legacy systems and deliver customer-centric digital solutions. Real-Time Bank Feed APIs enable seamless data exchange between banks and third-party applications, facilitating instant access to account balances, transaction histories, and payment statuses. This capability not only improves operational efficiency but also enhances customer experience by providing up-to-date financial information, which is critical in an era where consumers expect immediate access to their banking data.

Another significant driver is the proliferation of open banking regulations and standards across major economies. Regulatory frameworks such as PSD2 in Europe and similar initiatives in Asia Pacific and North America mandate banks to provide secure API access to customer data, provided customer consent is obtained. These regulations have catalyzed the adoption of Real-Time Bank Feed APIs by encouraging innovation and competition among financial service providers. Fintech companies, in particular, leverage these APIs to develop new financial products, streamline payment processing, and offer advanced analytics, thereby expanding the overall use cases and market penetration of Real-Time Bank Feed APIs.

The rapid growth of the fintech ecosystem is also contributing to the expansion of the Real-Time Bank Feed APIs market. Fintech startups and established technology firms are increasingly collaborating with banks to create integrated financial management platforms, automated accounting tools, and real-time fraud detection systems. The ability of Real-Time Bank Feed APIs to provide accurate, up-to-the-minute financial data is essential for these applications, driving their widespread adoption. Furthermore, the increasing use of artificial intelligence and machine learning in financial services amplifies the demand for real-time data feeds, as these technologies rely on timely and accurate information to deliver predictive insights and automated decision-making.

From a regional perspective, North America currently dominates the Real-Time Bank Feed APIs market, accounting for the largest share due to its mature banking infrastructure, high digital literacy, and strong presence of leading fintech innovators. Europe follows closely, propelled by stringent open banking regulations and a rapidly evolving financial services landscape. The Asia Pacific region is witnessing the fastest growth, driven by burgeoning digital banking adoption, supportive regulatory environments, and a large unbanked population transitioning to digital financial services. Latin America and the Middle East & Africa are gradually emerging as promising markets, fueled by increasing investments in digital infrastructure and growing demand for efficient banking solutions.

Component Analysis

The Real-Time Bank Feed APIs market is segmented by component into Software and Services, each playing a crucial role in the overall value chain. The software segment encompasses the core API platforms, integration tools, and middleware that enable the secure and efficient exchange of financial data between banks and third-party applications. These solutions are designed to

Sports Betting Data Feeds Market Outlook

According to our latest research, the global sports betting data feeds market size reached USD 1.75 billion in 2024, reflecting robust growth driven by digital transformation and the increasing legalization of sports betting worldwide. The market is projected to expand at a CAGR of 12.4% from 2025 to 2033, with the total market value forecasted to hit USD 5.06 billion by 2033. This growth trajectory is primarily attributed to the proliferation of online betting platforms, technological advancements in real-time data processing, and the evolving regulatory landscape that continues to favor the adoption of sports betting solutions.

One of the primary growth factors for the sports betting data feeds market is the exponential rise in global sports betting activities, both online and offline. As more countries move towards legalizing sports betting, operators are seeking advanced data feed solutions to enhance their offerings and ensure compliance with regulatory requirements. The surge in popularity of live and in-play betting has created a significant demand for real-time, accurate, and reliable data feeds. Sportsbooks and betting platforms are increasingly relying on sophisticated data feed providers to deliver up-to-the-second information on odds, player statistics, and match outcomes, which not only improves the user experience but also reduces the risk of fraud and errors. Furthermore, the integration of artificial intelligence and machine learning into data feed solutions is enabling operators to provide more personalized and engaging betting experiences, further fueling market growth.

Another key driver is the rapid technological advancements in data transmission and analytics. The emergence of cloud-based infrastructure and API-driven architectures has enabled seamless integration of data feeds into multiple betting platforms, enhancing scalability and operational efficiency. The adoption of advanced analytics tools allows operators to leverage historical and real-time data for predictive modeling, odds calculation, and risk management. In addition, the increasing use of mobile devices for sports betting has necessitated the development of lightweight, high-performance data feed solutions that can deliver instant updates to users regardless of their location. This technological evolution is not only expanding the addressable market but also intensifying competition among data feed providers, leading to continuous innovation and improvement in service quality.

The growing emphasis on regulatory compliance and integrity in sports betting is also shaping the market landscape. Governments and regulatory bodies are imposing stringent requirements on data accuracy, transparency, and anti-fraud measures, compelling operators to invest in high-quality data feed solutions. Data feed providers are responding by enhancing their offerings with features such as real-time monitoring, anomaly detection, and automated reporting to ensure compliance with evolving regulations. The collaboration between sports leagues, betting operators, and data providers is further strengthening the ecosystem, fostering trust and credibility among end-users. As a result, the sports betting data feeds market is witnessing increased adoption across various segments, including sportsbooks, online betting platforms, casinos, and fantasy sports operators.

From a regional perspective, North America and Europe continue to dominate the sports betting data feeds market, accounting for a significant share of global revenues. The United States, in particular, has witnessed a surge in sports betting activities following the repeal of PASPA, with several states legalizing and regulating the industry. Europe, with its well-established betting culture and mature regulatory framework, remains a key market for data feed providers. The Asia Pacific region is emerging as a lucrative market, driven by the rising popularity of online sports betting and the increasing adoption of digital payment solutions. Latin America and the Middle East & Africa are also witnessing steady growth, supported by favorable regulatory developments and expanding internet penetration.

Component Analysis

The sports betting data feeds market is segmented by component into software and services, each playing a pivotal role in shaping the industry’s trajectory. Software solutions form the backbone of data feed integr

US Stock News, offered by Benzinga, is the gateway to over 200 full-length stories and 1000 original content pieces created daily by an in-house editorial team. News events cover everything from M&A deals to Federal Reserve announcements.

A decisive advantage of this data feed is its structural format. REST API lets you filter news by date, company ticker, CIK, ISIN, and other identifiers. Response contains the text URL, image URL, tags, author, title, and timestamps. In addition to the API, news can be accessed via spreadsheet add-ons.

The primary price indicator for companies is the number of users who will be using or seeing earnings data. Individual, non-commercial users can always choose 0. No agreements or licenses are required to be signed. Finazon partnered with Benzinga to provide lower rates and let users enjoy the marketplace's synergy.

When there is a vast variety of metrics and tools available to gain market insight, Insider trading offers valuable clues to investors related to future share performance. We at Smart Insider provide global insider trading data and analysis on share transactions made by directors & senior staff in the shares of their own companies.

Monitoring all the insider trading activity is a huge task, we identify 'Smart Insiders' through specialist desktop and quantitative feeds that enable our clients to generate alpha.

Our experienced analyst team use quantitative and qualitative methods to identify the stocks most likely to outperform based on deep analysis of insider trades, and the insiders themselves. Using our easy-to-read derived data we help our clients better understand insider transactions activity to make informed 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 XML, XLSX or API via SFTP or Snowflake.

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

Tags: Stock Market Data, Equity Market Data, Insider Transactions Data, Insider Trading Intelligence, Trading, Investment Management, Alternative Investment, Asset Management, Equity Research, Market Analysis, United Kingdom, Europe

This dataset is available on Brisbane City Council’s open data website – data.brisbane.qld.gov.au. The site provides additional features for viewing and interacting with the data and for downloading the data in various formats.

This dataset contains information on markets in Brisbane. It includes locations, dates and times.

Brisbane City Council's events data containing dates, costs, booking requirements, venue and location for markets events in Brisbane.

The dataset was created using data from an external service called Trumba. The data is a transformed extract created using the Trumba Calendar API XML feed, that is limited to the next 1,000 events. The transformed extract is converted to a CSV file and uploaded into this dataset daily.

To access and view the data using the Source API (Trumba), use the information below and your preferred link in the Data and Resources section. The Source API is available for this dataset in:

• Trumba Calendar - API - XML feed is limited to the next 1,000 events
• Trumba Calendar - API - RSS feed is limited to the next 1,000 events
• Trumba Calendar - API - CSV feed is limited to the next 2,000 events
• Trumba Calendar - API - JSON feed is limited to the next 2,000 events.

The Data and resources section of this dataset contains further information for this dataset.

Low Bridge Clearance Digital Feed APIs Market Outlook

According to our latest research, the global Low Bridge Clearance Digital Feed APIs market size reached USD 1.24 billion in 2024, reflecting robust demand across transportation and logistics sectors. The market is forecasted to expand at a CAGR of 13.7% from 2025 to 2033, reaching a projected value of USD 4.02 billion by 2033. This impressive growth is primarily driven by the increasing need for real-time, accurate clearance data to enhance route planning, reduce accidents, and optimize logistics operations worldwide.

One of the primary growth factors for the Low Bridge Clearance Digital Feed APIs market is the rapid advancement in connected vehicle technologies and the proliferation of smart transportation infrastructure. As commercial fleets and logistics providers increasingly integrate digital solutions into their operations, the demand for APIs that deliver up-to-date clearance data has surged. These APIs enable seamless integration with navigation systems, fleet management platforms, and mapping services, providing actionable insights on bridge heights and potential hazards. The emphasis on reducing vehicle-bridge collision rates, which cause significant financial and operational losses, further accelerates adoption. Additionally, regulatory mandates in several regions requiring the use of advanced navigational aids for oversized vehicles have spurred market growth, as compliance becomes a critical operational requirement for transportation companies.

Another crucial driver is the growing focus on operational efficiency and cost reduction within the logistics and transportation industries. By leveraging Low Bridge Clearance Digital Feed APIs, fleet operators can avoid costly detours, property damage, and legal liabilities associated with bridge strikes. These APIs facilitate dynamic route planning, allowing vehicles to automatically reroute based on real-time clearance data, traffic conditions, and road closures. The integration of artificial intelligence and machine learning into these APIs further enhances their predictive capabilities, offering proactive risk mitigation and route optimization. As the industry shifts towards digital transformation and smart mobility, the adoption of robust digital feed APIs is becoming a competitive differentiator for logistics providers and transportation companies.

Furthermore, the increasing penetration of cloud computing and mobile technologies has made it easier for organizations of all sizes to access and deploy Low Bridge Clearance Digital Feed APIs. Cloud-based deployment models offer scalability, flexibility, and cost-effectiveness, enabling even small and medium-sized enterprises to benefit from advanced clearance data solutions. The expansion of smart city initiatives and infrastructure modernization projects, especially in emerging markets, is also fueling demand for digital feed APIs that support urban mobility, public transportation, and municipal planning. As governments and municipalities invest in intelligent transportation systems, the integration of clearance data APIs into public and private sector applications is set to become more widespread, underpinning the market’s sustained growth trajectory.

From a regional perspective, North America currently dominates the Low Bridge Clearance Digital Feed APIs market, supported by a mature transportation infrastructure, high adoption of fleet management technologies, and stringent regulatory frameworks. Europe follows closely, driven by cross-border logistics activities and a strong emphasis on road safety. Asia Pacific is emerging as a high-growth region, propelled by rapid urbanization, expanding logistics networks, and government investments in smart transportation solutions. Latin America and the Middle East & Africa, while smaller in market share, are witnessing increasing adoption as digital transformation initiatives gain momentum and infrastructure modernization accelerates. Collectively, these regional dynamics underscore the global relevance and expanding footprint of the Low Bridge Clearance Digital Feed APIs market.

Component Analysis

The Component segment of the Low Bridge Clearance Digital Feed APIs market is broadly categorized into Software, Hardware, and Services. Software solutions form the backbone of the market, providing the core API functionalities that collect, process, and disseminate real-time clearance data. These soft

The Cholesterol API market is experiencing steady growth, projected to reach over $400 million by 2033, driven by increasing pharmaceutical and feed applications. Discover key trends, regional analysis, and leading companies shaping this expanding market.

This dataset contains information on markets in Brisbane. It includes locations, dates and times.

Brisbane City Council's events data containing dates, costs, booking requirements, venue and location for markets events in Brisbane.

The dataset was created using data from an external service called Trumba. The data is a transformed extract created using the Trumba Calendar API XML feed, that is limited to the next 1,000 events. The transformed extract is converted to a CSV file and uploaded into this dataset daily.

To access and view the data using the Source API (Trumba), use the information below and your preferred link in the Data and Resources section. The Source API is available for this dataset in:

Trumba Calendar - API - XML feed is limited to the next 1,000 events

Trumba Calendar - API - RSS feed is limited to the next 1,000 events

Trumba Calendar - API - CSV feed is limited to the next 2,000 events

Trumba Calendar - API - JSON feed is limited to the next 2,000 events.

The Data and resources section of this dataset contains further information for this dataset.

Discover the booming bank feed market! Our comprehensive analysis reveals a CAGR of X% (estimated based on market trends), driven by cloud accounting software and automation. Explore market segmentation, key players (Xero, QuickBooks, etc.), and regional insights for North America, Europe, and beyond. Learn about growth drivers, restraints, and future predictions for the period 2019-2033.

Gain exclusive access to specialist Foreign Exchange (FX) data, and the tools to manage trading analysis, risk and operations with LSEG's FX Pricing Data.

Extensive and dependable pricing information spanning the entire range of financial markets. Encompassing worldwide coverage from stock exchanges, trading platforms, indicative contributed prices, assessed valuations, expert third-party sources, and our enhanced data offerings. User-friendly request-response, bulk access, and tailored desktop interfaces to meet nearly any organizational or application data need. Worldwide, real-time, delayed streaming, intraday updates, and meticulously curated end-of-day pricing information.

The global Vitamin A API market is projected to reach an estimated $1.6 billion by 2025, with a robust Compound Annual Growth Rate (CAGR) of approximately 5.5% anticipated between 2025 and 2033. This growth is primarily propelled by escalating demand across diverse sectors, particularly in animal feed additives where Vitamin A is crucial for livestock health and productivity, contributing significantly to the market's value. The human nutrition segment is also witnessing substantial expansion, driven by increasing consumer awareness regarding the health benefits of Vitamin A, including its role in vision, immune function, and skin health. The pharmaceutical industry further underpins this growth, utilizing Vitamin A APIs in a wide array of medicinal formulations. Emerging economies, especially in the Asia Pacific region, are expected to be significant contributors to market expansion due to growing disposable incomes, improving healthcare infrastructure, and a rising prevalence of dietary supplement consumption. Despite the strong growth trajectory, the Vitamin A API market faces certain restraints, including fluctuating raw material prices and stringent regulatory frameworks governing API production and quality. However, technological advancements in synthesis and purification processes, coupled with increasing investments in research and development by key players like DSM, BASF, and Zhejiang NHU, are expected to mitigate these challenges. The market is segmented by application into Animal Feed Additives, Human Nutrition, Pharmaceutical, and Cosmetics, with Animal Feed Additives and Human Nutrition holding the largest shares. By type, Food Grade and Feed Grade are the predominant categories. Geographically, Asia Pacific is poised to lead market growth, followed by North America and Europe, as these regions witness increased adoption of Vitamin A for both nutritional and therapeutic purposes. This report offers an in-depth analysis of the Vitamin A API (Active Pharmaceutical Ingredient) market, encompassing a thorough examination of its dynamics, growth trajectories, and future outlook. The study period spans from 2019 to 2033, with a base year of 2025 for estimations and a forecast period from 2025 to 2033, building upon historical data from 2019-2024. We delve into market size estimations in the million unit scale, providing actionable insights for stakeholders.

This repository includes python scripts and input/output data associated with the following publication:

[1] Brown, P.R.; O'Sullivan, F. "Spatial and temporal variation in the value of solar power across United States Electricity Markets". Renewable & Sustainable Energy Reviews 2019. https://doi.org/10.1016/j.rser.2019.109594

Please cite reference [1] for full documentation if the contents of this repository are used for subsequent work.

Many of the scripts, data, and descriptive text in this repository are shared with the following publication:

[2] Brown, P.R.; O'Sullivan, F. "Shaping photovoltaic array output to align with changing wholesale electricity price profiles". Applied Energy 2019, 256, 113734. https://doi.org/10.1016/j.apenergy.2019.113734

All code is in python 3 and relies on a number of dependencies that can be installed using pip or conda.

Contents

pvvm/*.py : Python module with functions for modeling PV generation and calculating PV energy revenue, capacity value, and emissions offset.

notebooks/*.ipynb : Jupyter notebooks, including:

pvvm-vos-data.ipynb: Example scripts used to download and clean input LMP data, determine LMP node locations, assign nodes to capacity zones, download NSRDB input data, and reproduce some figures in [1]

pvvm-example-generation.ipynb: Example scripts demonstrating the use of the PV generation model and a sensitivity analysis of PV generator assumptions

pvvm-example-plots.ipynb: Example scripts demonstrating different plotting functions

validate-pv-monthly-eia.ipynb: Scripts and plots for comparing modeled PV generation with monthly generation reported in EIA forms 860 and 923, as discussed in SI Note 3 of [1]

validate-pv-hourly-pvdaq.ipynb: Scripts and plots for comparing modeled PV generation with hourly generation reported in NREL PVDAQ database, as discussed in SI Note 3 of [1]

pvvm-energyvalue.ipynb: Scripts for calculating the wholesale energy market revenues of PV and reproducing some figures in [1]

pvvm-capacityvalue.ipynb: Scripts for calculating the capacity credit and capacity revenues of PV and reproducing some figures in [1]

pvvm-emissionsvalue.ipynb: Scripts for calculating the emissions offset of PV and reproducing some figures in [1]

pvvm-breakeven.ipynb: Scripts for calculating the breakeven upfront cost and carbon price for PV and reproducing some figures in [1]

html/*.html : Static images of the above Jupyter notebooks for viewing without a python kernel

data/lmp/*.gz : Day-ahead nodal locational marginal prices (LMPs) and marginal costs of energy (MCE), congestion (MCC), and losses (MCL) for CAISO, ERCOT, MISO, NYISO, and ISONE.

At the time of publication of this repository, permission had not been received from PJM to republish their LMP data. If permission is received in the future, a new version of this repository will be linked here with the complete dataset.

results/*.csv.gz : Simulation results associated with [1], including modeled energy revenue, capacity credit and revenue, emissions offsets, and breakeven costs for PV systems at all LMP nodes

Data notes

ISO LMP data are used with permission from the different ISOs. Adapting the MIT License (https://opensource.org/licenses/MIT), "The data are provided 'as is', without warranty of any kind, express or implied, including but not limited to the warranties of merchantibility, fitness for a particular purpose and noninfringement. In no event shall the authors or sources be liable for any claim, damages or other liability, whether in an action of contract, tort or otherwise, arising from, out of or in connection with the data or other dealings with the data." Copyright and usage permissions for the LMP data are available on the ISO websites, linked below.

ISO-specific notes on LMP data:

CAISO data from http://oasis.caiso.com/mrioasis/logon.do are used pursuant to the terms at http://www.caiso.com/Pages/PrivacyPolicy.aspx#TermsOfUse.

ERCOT data are from http://www.ercot.com/mktinfo/prices.

MISO data are from https://www.misoenergy.org/markets-and-operations/real-time--market-data/market-reports/ and https://www.misoenergy.org/markets-and-operations/real-time--market-data/market-reports/market-report-archives/.

PJM data were originally downloaded from https://www.pjm.com/markets-and-operations/energy/day-ahead/lmpda.aspx and https://www.pjm.com/markets-and-operations/energy/real-time/lmp.aspx. At the time of this writing these data are currently hosted at https://dataminer2.pjm.com/feed/da_hrl_lmps and https://dataminer2.pjm.com/feed/rt_hrl_lmps.

NYISO data from http://mis.nyiso.com/public/ are used subject to the disclaimer at https://www.nyiso.com/legal-notice.

ISONE data are from https://www.iso-ne.com/isoexpress/web/reports/pricing/-/tree/lmps-da-hourly and https://www.iso-ne.com/isoexpress/web/reports/pricing/-/tree/lmps-rt-hourly-final. The Material is provided on an "as is" basis. ISO New England Inc., to the fullest extent permitted by law, disclaims all warranties, either express or implied, statutory or otherwise, including but not limited to the implied warranties of merchantability, non-infringement of third parties' rights, and fitness for particular purpose. Without limiting the foregoing, ISO New England Inc. makes no representations or warranties about the accuracy, reliability, completeness, date, or timeliness of the Material. ISO New England Inc. shall have no liability to you, your employer or any other third party based on your use of or reliance on the Material.

Data workup: LMP data were downloaded directly from the ISOs using scripts similar to the pvvm.data.download_lmps() function (see below for caveats), then repackaged into single-node single-year files using the pvvm.data.nodalize() function. These single-node single-year files were then combined into the dataframes included in this repository, using the procedure shown in the pvvm-vos-data.ipynb notebook for MISO. We provide these yearly dataframes, rather than the long-form data, to minimize file size and number. These dataframes can be unpacked into the single-node files used in the analysis using the pvvm.data.copylmps() function.

Usage notes

Code is provided under the MIT License, as specified in the pvvm/LICENSE file and at the top of each *.py file.

Updates to the code, if any, will be posted in the non-static repository at https://github.com/patrickbrown4/pvvm_vos. The code in the present repository has the following version-specific dependencies:

matplotlib: 3.0.3

numpy: 1.16.2

pandas: 0.24.2

pvlib: 0.6.1

scipy: 1.2.1

tqdm: 4.31.1

To use the NSRDB download functions, you will need to modify the "settings.py" file to insert a valid NSRDB API key, which can be requested from https://developer.nrel.gov/signup/. Locations can be specified by passing (latitude, longitude) floats to pvvm.data.downloadNSRDBfile(), or by passing a string googlemaps query to pvvm.io.queryNSRDBfile(). To use the googlemaps functionality, you will need to request a googlemaps API key (https://developers.google.com/maps/documentation/javascript/get-api-key) and insert it in the "settings.py" file.

Note that many of the ISO websites have changed in the time since the functions in the pvvm.data module were written and the LMP data used in the above papers were downloaded. As such, the pvvm.data.download_lmps() function no longer works for all ISOs and years. We provide this function to illustrate the general procedure used, and do not intend to maintain it or keep it up to date with the changing ISO websites. For up-to-date functions for accessing ISO data, the following repository (no connection to the present work) may be helpful: https://github.com/catalyst-cooperative/pudl.

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.

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When you want to show charging station information on a map or in an application, high quality data is crucial for the customer experience. Our real-time API is the easy solution to all your EV Charging Station related data needs. It is based on the industry standard OCPI protocol, and optionally we can add many additional enriching features.

Location attributes include coordinates, address, operator, power, connector type, opening times, access type (public / restricted / private), predicted occupancy, reliability score, and accepted payment methods. Tariff attributes include price per kWh, per hour charging and/or parking, flat fees, and subscription fees. Attributes are available for all countries in our database. The price of the data is dependent on the geographies chosen, the length of the subscription, and the intended use.

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Discover the booming Vitamin C API market! Explore key trends, drivers, and restraints shaping this $2.5B (2025) industry, projected for significant growth through 2033. Learn about leading companies, regional market shares, and applications in food, pharma, and cosmetics.