View Refinitiv's New York Stock Exchange (NYSE) Market Data and benefit from full-depth market-by-price data, available as real-time and historical records.

TagX is your trusted partner for stock market and financial data solutions. We specialize in delivering real-time and end-of-day data feeds that power software, trading algorithms, and risk management systems globally. Whether you're a financial institution, hedge fund, or individual investor, our reliable datasets provide essential insights into market trends, historical pricing, and key financial metrics.

TagX is committed to precision and reliability in stock market data. Our comprehensive datasets include critical information such as date, open/close/high/low prices, trading volume, EPS, P/E ratio, dividend yield, and more. Tailor your dataset to match your specific requirements, choosing from a wide range of parameters and coverage options across primary listings on NASDAQ, AMEX, NYSE, and ARCA exchanges.

Key Features of TagX Stock Market Data:

Custom Dataset Requests: Customize your data feed to focus on specific metrics and parameters crucial to your trading strategy.

Extensive Coverage: Access data from reputable exchanges and market participants, ensuring accuracy and completeness in your analyses.

Flexible Pricing Models: Choose pricing structures based on your selected parameters, offering cost-effective solutions tailored to your needs.

Why Choose TagX? Partner with TagX for precise, dependable, and customizable stock market data solutions. Whether you require real-time updates or end-of-day valuations, our datasets are designed to support informed decision-making and enhance your competitive edge in the financial markets. Trust TagX to deliver the data integrity and accuracy essential for maximizing your trading potential.

According to Cognitive Market Research, the global Financial Data Service market size will be USD 24152.5 million in 2024. It will expand at a compound annual growth rate (CAGR) of 8.50% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 9661.00 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.7% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 7245.75 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 5555.08 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.5% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 1207.63 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.9% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 483.05 million in 2024 and will grow at a compound annual growth rate (CAGR) of 8.2% from 2024 to 2031.
Datafeed/API solutions are the dominant segment, as they allow seamless data integration into existing systems and platforms, making them ideal for companies requiring real-time data across multiple applications

Market Dynamics of Financial Data Service Market

Key Drivers for Financial Data Service Market

Increased Data-Driven Decision-Making to Boost Market Growth

As digital transformation sweeps through financial services, data-driven decision-making has become essential for businesses to remain competitive. Institutions, both financial and non-financial, are increasingly leveraging financial data to guide strategic investments, manage risks, and streamline operations. By utilizing real-time data and predictive analytics, companies gain actionable insights to optimize their investment portfolios and financial planning. With the enhanced capability to analyze data trends and assess market scenarios, businesses can mitigate risks more effectively, making this driver critical to the growth of the financial data service market. For instance, in September 2022, Alibaba Cloud, the digital technology and intellectual backbone of Alibaba Group, launched a comprehensive suite of Alibaba Cloud for Financial Services solutions. Comprising over 70 products, these solutions are designed to help financial services institutions of all sizes across banking, FinTech, insurance, and securities, digitalize their operations

Advancements in Analytics Technology to Drive Market Growth

The integration of advanced analytics technologies like artificial intelligence (AI) and machine learning (ML) in financial data services has significantly enhanced the accuracy and scope of market insights. AI and ML enable companies to process vast amounts of financial data, identify patterns, and make predictions, thus facilitating strategic planning and investment optimization. These technologies also allow for real-time insights, giving firms a competitive advantage in rapidly evolving markets. With continuous improvements in AI and ML, the demand for advanced data services is expected to grow, positioning this as a key driver of market expansion.

Restraint Factor for the Financial Data Service Market

High Cost of Data Services Will Limit Market Growth

The high cost of premium financial data services is a significant restraint, particularly for small and medium-sized enterprises (SMEs). Many advanced platforms and data feeds come with substantial subscription fees, limiting their accessibility to larger organizations with more considerable budgets. This cost barrier restricts smaller firms from fully integrating advanced data insights into their operations. As a result, high subscription costs prevent widespread adoption among SMEs, hindering the financial data service market’s overall growth potential.

Trends for the Financial Data Service Market

Blockchain-based Data Services as an opportunity for the market

Blockchain-based data services offer a secure, transparent, and decentralized approach to financial data management. By leveraging blockchain technology, finance data services can provide tamper-proof and auditable data storage, ensuring the integrity and accuracy of financial data. This can help...

View LSEG's ICE Data Pricing and Reference Data, and find real-time market data, time-sensitive pricing, and reference data for securities trading.

Browse LSEG's market-leading global Pricing and Market Data for the financial markets, providing the broadest range of cross-asset market and pricing data.

Access LSEG's London Stock Exchange (LSE) Market Data, and find benchmarks, indices, and real-time and historic market information.

Explore LSEG's Toronto Stock Exchange (TSX) Market Data, representing a broad range of businesses from Canada and abroad.

All historical per-share time series, including prices, earnings per share, dividends per share, assets per share, cash flow per share, etc. need to be adjusted before meaningful conclusions can be drawn about growth rates, trends, etc.

The feed has all necessary fields so that clients can identify the country, security, currency, event and adjustment factor. Further the feed has been designed for clients to database the records or apply directly to price series data. The file also covers all corporate actions spanning multiple currencies for the same event.

The main benefit of this feed over competitor feeds is that it can be fully automated allowing the handling of messy cancellations and corporate action changes to happen seamlessly in the background. EDI has recently launched a new version (2) of the Worldwide Adjustment Factor feed service. The major three additions are as follows:

• Inclusion of FIGI codes. FIGI codes have been added which will allow clients to crosscheck data sets. • Fields that were sub-fields in the Detail field of the previous version now have their own fields. For example, DivType was in the Detail field (event description) as DIVPERIOD= This will allow for easier integration of the data. • The Reason codes are different, expanded to 3 characters enabling higher level groupings of reasons. For example, all dividend reasons begin with 01, with the 3rd character depending on whether it is cash, script or both. This allows greater granularity when deciding to apply or not.

The global bank feed market is experiencing robust growth, driven by the increasing adoption of cloud-based accounting software and the rising demand for automated financial data management solutions across SMEs and large enterprises. The market's expansion is fueled by several key factors: the need for improved financial accuracy and efficiency, enhanced regulatory compliance requirements, and the desire for real-time financial insights. Direct feed solutions, which offer a seamless integration with banking systems, are witnessing higher adoption rates compared to indirect feeds, reflecting a preference for streamlined and automated processes. Large enterprises, with their complex financial structures, are major contributors to market growth, while the SME segment is also expanding rapidly, fueled by the accessibility and affordability of cloud-based accounting solutions. Geographic variations exist, with North America and Europe currently dominating the market due to higher technological adoption and a well-established fintech ecosystem. However, regions like Asia-Pacific are projected to show significant growth in the coming years driven by increasing digitalization and economic expansion. Competitive pressures are high, with numerous established players and emerging fintech companies vying for market share. The market's future trajectory suggests continued expansion, driven by ongoing technological advancements such as AI-powered data analysis and enhanced security features within bank feed solutions. Despite the promising growth, the market faces certain challenges. Integration complexities with diverse banking systems and data security concerns remain significant hurdles. Furthermore, the reliance on secure APIs and the need for continuous updates to adapt to evolving banking systems and regulations pose ongoing operational challenges for providers. Data privacy regulations like GDPR also influence market dynamics, necessitating robust compliance measures. However, innovative solutions addressing these challenges, coupled with the inherent advantages of automated bank feeds, are expected to mitigate these restraints and sustain market expansion throughout the forecast period. The market's evolution will likely be shaped by partnerships and acquisitions amongst existing players, as well as the entry of new companies with disruptive technologies.

With LSEG's Hong Kong Stock Exchange Issuer Information feed Service (IIS), gain real-time trading news and announcements from HKEX listed companies.

The Techfit tool provides a means to identify suitable feed technologies to address four key constraints: dry season feed availability, growing season feed availability, feed quantity and feed quality. The feasibility of introducing each technology is assessed using proxies for seven attributes: land availability, water availability, labour, capital expenditure, access to inputs, requirement for skill/knowledge and market-pull. Travel time to financial service providers, input providers and market outlets were generated based on financial and agricultural points of interest (POI) and a travel friction surface layer. Financial and agricultural points of interest are available for Uganda and Kenya through the FinScope database. The database identifies the locations of credit facilities, abattoirs, sale-yards, milk chilling plants, dairy processors and input suppliers. The points of interests were filtered to only include operational facilities. The travel time to these points were then calculated as the accumulated cost from a given pixel to a POI, where the cost in minutes is defined by the friction layer (accumulated cost calculated using the accCost function in the gDistance package in R). Separate layers were created for financial services, livestock market outlets, dairy market outlets veterinary service providers and agri-input suppliers.

Comprehensive information on all Irish-resident money market funds. The data details stock and transactions on a monthly basis, with information on the scale, composition, geographical and sectoral exposures of funds’ assets and liabilities including shares issued and debt securities. This data is transmitted to the Central Statistics Office and the European Central Bank to feed into Irish and euro area balance of payments and national accounts statistics and the key broad money supply measure, M3. The data also feeds the measurement of shadow banking based on Financial Stability Board definitions.

Estimate income and evaluate stocks and ETFs based on accurate two year forward dividend forecasts across 25k+ securities globally.

Use our forward dividend prediction data feed to obtain up-to-date information on the dates and payments of thousands of securities across 1000+ indices / 100+ countries.

Our single stock and ETF dividend forecast data elements include:

-Predicted ex, record and pay dates -Amount and currency -Dividend type / frequency -Unique Dividend Forecast Data Methodology

In these times of accelerating change our tech-driven approach gives us a powerful and disruptive edge over the older, more traditional forecasting methodologies Working from EDI’s global corporate actions database (dating back to 2012) our dividend projections are based on a combination of stated dividend policies and predictable patterns. The estimate data is generated by a dedicated London team working with our proprietary algorithm and enhanced with manual analyst input where required. This algorithm+analyst approach gives estimates with both huge scale and strong accuracy – our forward-looking data runs two full fiscal years ahead for well over 25,000 securities including equity, ADR and ETF future projections.

Our Woodseer single stock forecast data-set went live in January 2017, and the ETF dividend forecast product launched in July 2019 with detailed forward projections (dates and amounts) for over 1400 ETFs including 700+ US-listed. Working closely with a specialist ETF data provider we combine their compositional ETF data with our own underlying security estimates to produce accurate ‘bottom-up’ forecasts.

Clients include asset managers and custodians, index providers, options market makers, hedge funds, single stock and index traders.

Browse LSEG's I/B/E/S Estimates, discover our range of data, indices & benchmarks. Our Data Catalogue offers unrivalled data and delivery mechanisms.

Corn rose to 399.78 USd/BU on July 23, 2025, up 0.13% from the previous day. Over the past month, Corn's price has fallen 3.96%, and is down 4.36% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Corn - values, historical data, forecasts and news - updated on July of 2025.

Access our data for free: https://matrix.blocksize.capital/auth/open/sign-up

Blocksize’s 24-Hour VWAP Feed provides a reliable, single-point reference price for digital assets, calculated once daily at 00:00 UTC. Designed to serve institutions, fund managers, and DeFi protocols, this product delivers a transparent, volume-weighted average price based on aggregated trading activity across a broad set of vetted exchanges. It is especially valuable for portfolio valuation, backtesting, performance benchmarking, and regulatory reporting.

The feed calculates the volume-weighted average price (VWAP) by capturing trade data across all accepted markets within a rolling 24-hour period. Each data point reflects a weighted average of executed transaction prices, proportionate to trading volume, ensuring that high-volume trades exert greater influence on the final price. The output is standardized and delivered in major fiat currencies such as USD and EUR, making it easy to integrate into financial models, reporting dashboards, or pricing mechanisms.

To ensure reliability and data integrity, the feed is governed by strict quality assurance protocols. Trade events from exchanges with technical issues or anomalous behavior are excluded from the calculation. If a market fails to report during the full 24-hour period, the feed automatically adjusts by relying on other verified sources. In the unlikely case where no qualifying trade data is available from any source, the system provides fallback pricing based on the most recently validated data — maintaining both accuracy and availability.

This daily feed is ideal for clients who need a consistent and unbiased pricing snapshot to serve as a reference rate, closing price, or benchmark across a range of financial and on-chain applications. Backed by Blocksize’s commitment to data transparency, uptime, and regulatory alignment, the 24-Hour VWAP Feed is a cornerstone pricing tool for serious market participants.

Our Customers:

• Oracles & DeFi Protocols and Applications
• Asset & Fund Managers investing in digital assets
• Asset Custodians storing digital assets
• Banks, Brokers with crypto offering
• Traditional Data Providers planning to extend their offering to digital assets
• Information Provider platforms

Questions? Reach out to our qualified data team.

PII Statement: Our datasets does not include personal, pseudonymized, or sensitive user data

Explore Options Price Reporting Authority (OPRA) through LSEG. OPRA collects, consolidates and disseminates information for US Options.

Wheat fell to 539.78 USd/Bu on July 24, 2025, down 0.13% from the previous day. Over the past month, Wheat's price has risen 2.18%, and is up 0.38% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Wheat - values, historical data, forecasts and news - updated on July of 2025.

Feeder Cattle fell to 329.08 USd/Lbs on July 24, 2025, down 0.86% from the previous day. Over the past month, Feeder Cattle's price has risen 8.98%, and is up 27.55% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Feeder Cattle - values, historical data, forecasts and news - updated on July of 2025.

Transform today’s vast amounts of unstructured data into actionable insights that maximize your returns, with LSEG News Analytics.