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 associated with 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.

Impact of Covid-19 on the Financial Data Service Market

Covid-19 significantly impacted the Financial Data Service Market as companies increasingly relied on accurate data analytics for rapid decision-making amid market volatility. During the pandemic, financial data providers observed heightened demand for real-time and historical data to model economic scenarios and assess risks accurately. This shift spurred technological advancements a...

In 2024, stock markets in the United States accounted for roughly 60 percent of world stocks. The next largest country by stock market share was Japan, followed by the United Kingdom. The New York Stock Exchange (NYSE) and the NASDAQ are the largest stock exchange operators worldwide. What is a stock exchange? The first modern publicly traded company was the Dutch East Industry Company, which sold shares to the general public to fund expeditions to Asia. Since then, groups of companies have formed exchanges in which brokers and dealers can come together and make transactions in one space. Stock market indices group companies trading on a given exchange, giving an idea of how they evolve in real time. Appeal of stock ownership Over half of adults in the United States are investing money in the stock market. Stocks are an attractive investment because the possible return is higher than offered by other financial instruments.

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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Expert industry market research on the Financial Data Service Providers in the US (2005-2030). Make better business decisions, faster with IBISWorld's industry market research reports, statistics, analysis, data, trends and forecasts.

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Alternative Data Market Size 2025-2029

The alternative data market size is forecast to increase by USD 60.32 billion at a CAGR of 52.5% between 2024 and 2029.

The market is experiencing significant growth due to the increased availability and diversity of data sources. This trend is driven by the rise of alternative data-driven investment strategies, which offer unique insights and opportunities for businesses and investors. However, challenges persist in the form of issues related to data quality and standardization. big data analytics and machine learning help businesses gain insights from vast amounts of data, enabling data-driven innovation and competitive advantage. Data governance, data security, and data ethics are crucial aspects of managing alternative data.
As more data becomes available, ensuring its accuracy and consistency is crucial for effective decision-making. The market analysis report provides an in-depth examination of these factors and their impact on the growth of the market. With the increasing importance of data-driven strategies, staying informed about the latest trends and challenges is essential for businesses looking to remain competitive in today's data-driven economy.

What will be the Size of the Alternative Data Market During the Forecast Period?

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Alternative data, the non-traditional information sourced from various industries and domains, is revolutionizing business landscapes by offering new opportunities for data monetization. This trend is driven by the increasing availability of data from various sources such as credit card transactions, IoT devices, satellite data, social media, and more. Data privacy is a critical consideration in the market. With the increasing focus on data protection regulations, businesses must ensure they comply with stringent data privacy standards. Data storytelling and data-driven financial analysis are essential applications of alternative data, providing valuable insights for businesses to make informed decisions. Data-driven product development and sales prediction are other significant areas where alternative data plays a pivotal role.
Moreover, data management platforms and analytics tools facilitate data integration, data quality, and data visualization, ensuring data accuracy and consistency. Predictive analytics and data-driven risk management help businesses anticipate trends and mitigate risks. Data enrichment and data-as-a-service are emerging business models that enable businesses to access and utilize alternative data. Economic indicators and data-driven operations are other areas where alternative data is transforming business processes.

How is the Alternative Data Market Segmented?

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

Type

  Credit and debit card transactions
  Social media
  Mobile application usage
  Web scrapped data
  Others


End-user

  BFSI
  IT and telecommunication
  Retail
  Others


Geography

  North America

    Canada
    Mexico
    US


  Europe

    Germany
    UK
    France
    Italy


  APAC

    China
    India
    Japan


  South America



  Middle East and Africa

By Type Insights

The credit and debit card transactions segment is estimated to witness significant growth during the forecast period.

Alternative data derived from card and debit card transactions offers valuable insights into consumer spending behaviors and lifestyle choices. This data is essential for market analysts, financial institutions, and businesses seeking to enhance their strategies and customer experiences. The two primary categories of card transactions are credit and debit. Credit card transactions provide information on discretionary spending, luxury purchases, and credit management skills. In contrast, debit card transactions reveal essential spending habits, budgeting strategies, and daily expenses. By analyzing this data using advanced methods, businesses can gain a competitive advantage, understand market trends, and cater to consumer needs effectively. IT & telecommunications companies, hedge funds, and other organizations rely on web scraped data, social and sentiment analysis, and public data to supplement their internal data sources. Adhering to GDPR regulations ensures ethical data usage and compliance.

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The credit and debit card transactions segment was valued at USD 228.40 million in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 56% to the growth of the global market during the forecast period.

T

Korean Companies’ Stock Market Data provides important information to analyze and predict trends in stock trading. This data includes trading volume, price fluctuations, and stock indices. Collected from stock exchanges and financial data sources, it helps investors predict stock market movements and develop investment strategies, which are crucial for assessing the value of publicly traded Korean companies.

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 44 companies listed on the Namibian Stock Exchange (XNAM) in Namibia. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

Top 5 used data fields in the End-of-Day Pricing Dataset for Namibia:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

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Top 5 financial instruments with End-of-Day Pricing Data in Namibia:

Namibia Stock Exchange (NSX) Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Namibia Stock Exchange. This index provides an overview of the overall market performance in Namibia.

Namibia Stock Exchange (NSX) Foreign Company Index: The index that tracks the performance of foreign companies listed on the Namibia Stock Exchange. This index reflects the performance of international companies operating in Namibia.

Company X: A prominent Namibian company with diversified operations across various sectors, such as telecommunications, energy, or banking. This company's stock is widely traded on the Namibia Stock Exchange.

Company Y: A leading financial institution in Namibia, offering banking, insurance, or investment services. This company's stock is actively traded on the Namibia Stock Exchange.

Company Z: A major player in the Namibian agricultural sector, involved in the production and distribution of agricultural products. This company's stock is listed and actively traded on the Namibia Stock Exchange.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Namibia, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

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Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in Namibia ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in Namibia?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Namibia exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

1. How do I pay for this dataset?

Techsalerator accepts various payment methods, including credit cards, direct transfers, ACH, and wire transfers, facilitating a convenient and secure payment process.

1. How do I receive the data?

‍Techsalerator provides the End-of-Day Pricing Data through multiple delivery methods, such as FTP, SFTP, S3 bucket, or email, ensuring easy access and integration into your systems. The dataset is available in formats like JSON, CSV, TXT, or XLS, allowing seamless data processing.

California Resources stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Financial Research Software Market size was valued at USD 1.23 Billion in 2024 and is projected to reach USD 1.82 Billion by 2031, growing at a CAGR of 3.5% during the forecast period 2024-2031.

Global Financial Research Software Market Drivers

Growing Demand for Data Analytics: Increasing demand for data-driven insights and analytics in the financial sector drives the adoption of financial research software to analyze market trends, investment opportunities, risk factors, and financial performance metrics.

Technological Advancements: Ongoing advancements in financial research software, including artificial intelligence (AI), machine learning (ML), natural language processing (NLP), and big data analytics, enhance data processing capabilities, improve accuracy, and enable predictive modeling for investment decision-making.

Regulatory Compliance Requirements: Stringent regulatory requirements and compliance standards in the financial industry drive the adoption of financial research software to ensure regulatory compliance, risk management, and transparency in reporting and disclosure practices.

Investment Management and Portfolio Optimization: Financial research software enables investment professionals, portfolio managers, and asset allocators to conduct comprehensive research, perform quantitative analysis, and optimize investment portfolios to maximize returns and mitigate risks.

Rise of Robo-Advisors and Fintech Solutions: The rise of robo-advisors, digital wealth management platforms, and fintech solutions drives demand for financial research software with automated investment algorithms, portfolio rebalancing tools, and personalized financial advice for retail investors and wealth management clients.

Globalization and Market Integration: Globalization of financial markets and increased market integration drive the need for financial research software that provides real-time market data, news feeds, and economic indicators to support informed decision-making in a dynamic and interconnected marketplace.

Shift Towards ESG Investing: The growing focus on environmental, social, and governance (ESG) factors in investment decision-making drives demand for financial research software with ESG data integration, sustainability metrics, and impact analysis tools to support responsible investing strategies.

Risk Management and Stress Testing: Financial research software enables financial institutions and investment firms to conduct risk assessments, scenario analysis, and stress testing to evaluate portfolio resilience, liquidity risk, credit risk, and market volatility in various market conditions.

Alternative Data Sources and Quantitative Analysis: Financial research software integrates alternative data sources, such as social media sentiment, satellite imagery, and consumer behavior data, into quantitative models and analytical frameworks to gain insights into market trends and investment opportunities.

Demand for Customization and Integration: Financial institutions and investment professionals seek customizable financial research software solutions that can be tailored to their specific needs, integrated with existing systems and workflows, and scalable to accommodate future growth and expansion.

Robinhood has commaned the largest share of the retail investing market in the United States since at least early 2020, with its market share fluctuating between one third and one half of the market over this period. For comparison, the next highest market share is held by Fidelity, with between nine and 20 percent of the market. Robinhood is a smartphone-based app which allows retail investors to easily engage in commission-free share trading.

1st Source stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Index returns, market cap, constituent detail data from various index providers, all linked to S&P Global companies and securities.

Ten years of daily data for the Dow Jones Industrial Average (DJIA) market index. Each point of the dataset is represented by the daily closing price for the DJIA. Historical data can be downloaded via the red button on the upper right corner of the chart.

The Report Covers Financial Data Service Providers Industry and It is Segmented by Deployment (On-Premise, On-Cloud), Solution (Database Management and Planning, Analysis and Reporting), End-User Vertical (BFSI, Healthcare, Manufacturing, Government, IT and Telecom), and Geography. The Market Sizes and Forecasts are Provided in Terms of Value (USD) for all the Above Segments.

Tribune Resources stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

The stock market is an important part of the capital market, and the research on the price fluctuation of the stock market has always been a hot topic for scholars. As a dynamic and complex system, the stock market is affected by various factors. However, with the development of information technology, information presents multisource and heterogeneous characteristics, and the transmission speed and mode of information have changed greatly. The explanation and influence of multi-source and heterogeneous information on stock market price fluctuations need further study. In this paper, a graph fusion and embedding method for multi-source heterogeneous information of Chinese stock market is established. Relational dimension information is introduced to realize the effective fusion of multi-source heterogeneous data information. A multi-attention graph neural network based on nodes and semantics is constructed to mine the implied semantics of fusion graph data and capture the influence of multi-source heterogeneous information on stock market price fluctuations. Experiments show that the proposed multi-source heterogeneous information fusion methods is superior to tensor or vector fusion method, and the constructed multi-attention diagram neural network has a better ability to explain stock market price fluctuations.

The Alternative Data Market size was valued at USD 7.20 billion in 2023 and is projected to reach USD 126.50 billion by 2032, exhibiting a CAGR of 50.6 % during the forecasts period. The use and processing of information that is not in financial databases is known as the alternative data market. Such data involves posts in social networks, satellite images, credit card transactions, web traffic and many others. It is mostly used in financial field to make the investment decisions, managing risks and analyzing competitors, giving a more general view on market trends as well as consumers’ attitude. It has been found that there is increasing requirement for the obtaining of data from unconventional sources as firms strive to nose ahead in highly competitive markets. Some current trend are the finding of AI and machine learning to drive large sets of data and the broadening utilization of the so called “Alternative Data” across industries that are not only the finance industry. Recent developments include: In April 2023, Thinknum Alternative Data launched new data fields to its employee sentiment datasets for people analytics teams and investors to use this as an 'employee NPS' proxy, and support highly-rated employers set up interviews through employee referrals. , In September 2022, Thinknum Alternative Data announced its plan to combine data Similarweb, SensorTower, Thinknum, Caplight, and Pathmatics with Lagoon, a sophisticated infrastructure platform to deliver an alternative data source for investment research, due diligence, deal sourcing and origination, and post-acquisition strategies in private markets. , In May 2022, M Science LLC launched a consumer spending trends platform, providing daily, weekly, monthly, and semi-annual visibility into consumer behaviors and competitive benchmarking. The consumer spending platform provided real-time insights into consumer spending patterns for Australian brands and an unparalleled business performance analysis. .

This dataset contains several daily features of S&P 500, NASDAQ Composite, Dow Jones Industrial Average, RUSSELL 2000, and NYSE Composite from 2010 to 2017. It covers features from various categories of technical indicators, futures contracts, price of commodities, important indices of markets around the world, price of major companies in the U.S. market, and treasury bill rates. Sources and thorough description of features have been mentioned in the paper of "CNNpred: CNN-based stock market prediction using a diverse set of variables".

the dataset can used for the test of models of deep learning which include structured data: stock price and unstructured data: stock bar posts. so, the dataset is Multi-source Heterogeneous Data.