MT Newswires offers premium intra-day global markets commentary and breaking news on a wide range of economic, equity, fixed income, energy commodity and FX markets, covering the US, Canada, Europe, and Asia with a focus on the most widely followed securities and events in developed markets and economies. Reports are designed to give the reader a quick and precise picture of the data, while analysts highlight both the immediate impact on the markets as well as the longer run implications for the economy and central bank policy. The Live Briefs Global Markets service is designed to keep a broad range of market participants and wealth managers alerted to market moving events around the globe. o 160 categories of original, real time multi-asset class coverage of equities, treasuries, commodities, options, ETFs and economies throughout the trading and business day; o Global Equities -Significant events affecting individual public companies in Europe, North America and Asia; o Global Economic news and market summaries; o Sector summaries (pre-market, mid-day and closing); o Forex commentary covering the major global currencies; o Energy and precious metal news and daily summaries; o Top News updates throughout each business day; o Earnings estimate changes; o Analyst rating changes; o After Hours and Pre-Market news, trading activity and technical price levels indications; o Market Chatter & Street Color– real time market moving insights from traders and investment professionals globally; o ETF Power Play- Daily trends in ETF trading activity; o Insider Trends – Notable individual and sector related insider trading activity; o Zero noise: Only premium, original news and event analysis. Never any fillers (press releases, non-market related news, etc.)

Financial News Events Dataset - Comprehensive Description

Overview

This synthetic dataset contains 3,024 records of financial news headlines centered around major market events from February 2025 to August 2025. The dataset captures real-time market dynamics, sentiment analysis, and trading patterns across global financial markets, making it ideal for financial analysis, sentiment modeling, and market prediction tasks.

Dataset Specifications

• Total Records: 3,024 rows
• Total Features: 12 columns
• Date Range: February 1, 2025 - August 14, 2025
• File Formats: CSV, JSON, XLSX
• Data Quality: ~5% null values strategically distributed for realistic data cleaning scenarios

Column Descriptions

Key Features & Statistics

Market Events Coverage (20 Categories)

• Stock Market Crashes & Rallies
• Interest Rate Changes & Central Bank Meetings
• Corporate Earnings Reports & IPO Launches
• Government Policy Announcements
• Trade Tariffs & Geopolitical Events
• Cryptocurrency Regulations
• Supply Chain Disruptions
• Economic Data Releases

Global Market Indices (18 Major Indices)

• US Markets: S&P 500, Dow Jones, Nasdaq Composite, Russell 2000
• Indian Markets: NSE Nifty, BSE Sensex
• European Markets: FTSE 100, DAX, Euro Stoxx 50, CAC 40
• Asian Markets: Nikkei 225, Hang Seng, Shanghai Composite, KOSPI
• Others: TSX, ASX 200, IBOVESPA, S&P/TSX Composite

News Sources (18 Reputable Publications)

Major financial news outlets including Reuters, Bloomberg, CNBC, Financial Times, Wall Street Journal, Economic Times, Forbes, and specialized financial publications.

Sector Distribution (18 Business Sectors)

Technology, Finance, Healthcare, Energy, Consumer Goods, Utilities, Industrials, Materials, Real Estate, Telecommunications, Automotive, Retail, Pharmaceuticals, Aerospace & Defense, Agriculture, Transportation, Media & Entertainment, Construction.

Data Quality & Preprocessing Notes

• Realistic Null Distribution: Approximately 5% null values in key columns (Headline, Sentiment, Index_Change_Percent, News_Url) to simulate real-world data collection challenges
• Balanced Sentiment Distribution: Mix of positive, neutral, and negative sentiment classifications
• Diverse Market Conditions: Index changes ranging from -5% to +5% reflecting various market scenarios
• Volume Variability: Trading volumes span 1M to 500M to represent different market liquidity conditions

Potential Use Cases

📈 Financial Analysis

• Market sentiment analysis and trend prediction
• Correlation studies between news events and market movements
• Trading volume pattern analysis

🤖 Machine Learning Applications

• Sentiment classification model training
• Market movement prediction algorithms
• News headline generation models
• Event-driven trading strategy development

📊 Data Visualization Projects

• Interactive market sentiment dashboards
• Time-series analysis of market events
• Geographic distribution of financial news impact
• Sector-wise performance visualization

🔍 Research Applications

• Academic research on market efficiency
• News impact analysis on different sectors
• Cross-market correlation studies
• Event study methodologies

Technical Specifications

• Memory Usage: Approximately 1.5MB across all formats
• **Proces...

Explore the "Bloomberg Quint News Dataset," a comprehensive collection of news articles from Bloomberg Quint, a leading source of financial, business, and economic news in India and around the world.

This dataset includes thousands of articles covering a wide range of topics, such as financial markets, economic policies, corporate news, technology, politics, and more. Each article in the dataset comes with detailed information, including headlines, publication dates, authors, article content, and categories, offering valuable insights for researchers, data analysts, and media professionals.

Key Features:

• Extensive Coverage: Thousands of news articles from Bloomberg Quint, covering diverse topics including business, finance, economics, technology, and global news.
• Detailed Metadata: Each article includes key details such as headline, publication date, author, content, and category, making it ideal for in-depth research and analysis.
• Ideal for Analysis: Perfect for researchers, data scientists, and content strategists looking to analyze trends in news reporting, study media coverage, or develop content strategies.
• Rich Source of Information: Provides up-to-date information on financial markets, economic policies, and global events, helping professionals stay informed and make data-driven decisions.

Whether you're researching financial trends, analyzing media coverage, or developing new content, the "Bloomberg Quint News Dataset" is an invaluable resource that offers detailed insights and extensive coverage of the latest news.

Explore the largest pre-crawled news articles dataset from CNBC, a leading global news source for business, finance and current affairs. This comprehensive news dataset includes thousands of articles covering a wide range of topics: financial markets, economic trends, technology, politics, health, and more. Each entry in this dataset provides detailed information, including headlines, publish dates, authors, article content and categories — offering valuable insights for researchers, data analysts and media professionals.

Key Features

• Extensive Coverage: Thousands of news articles from CNBC, spanning business, finance, technology and global news.
  
  
• Detailed Metadata: Each news record includes headline, publication date, author, content and category — enabling in-depth research.
  
  
• Ready for Analysis: Ideal for data scientists, content strategists and media researchers building trend-analysis, media-monitoring or news-analytics models.
  
  
• Immediate Use: Data is delivered in CSV format, instantly downloadable, ready for machine-learning, AI modelling or reporting pipelines.
  

Who benefits?

• Academic researchers analysing media coverage or news sentiment.
  
  
• Data scientists building news analytics dashboards or training NLP models.
  
  
• Content teams / SEO specialists sourcing datasets to support articles about media trends or data-driven stories.
  
  
• Global marketers investigating business & financial news trends across the US/UK/EU markets.
  

Why choose this dataset?

• Ready to use: no manual scraping required.
  
  
• High-quality metadata allowing filtered exports by topic, date or author.
  
  
• Broad topic coverage: business, finance, technology, politics, health, and global news.
  

Ideal for building derivatives: summarisation, classification, clustering.

CNBC Economy Articles Dataset is an invaluable collection of data extracted from CNBC’s economy section, offering deep insights into global and U.S. economic trends, market dynamics, financial policies, and industry developments.

This dataset encompasses a diverse array of economic articles on critical topics like GDP growth, inflation rates, employment statistics, central bank policies, and major global events influencing the market. Designed for researchers, analysts, and businesses, it serves as an essential resource for understanding economic patterns, conducting sentiment analysis, and developing financial forecasting models.

Dataset Highlights

Each record in the dataset is meticulously structured and includes:

• Article Titles
• Publication Dates
• Author Names
• Content Summaries
• URLs to Original Articles

This rich combination of fields ensures seamless integration into data science projects, research papers, and market analyses.

Key Features

• Number of Articles: Hundreds of articles sourced directly from CNBC.
• Data Fields: Includes title, publication date, author, article content, summary, URL, and relevant keywords.
• Topics Covered: U.S. and global economy, GDP trends, inflation, employment, financial markets, and monetary policies.
• Format: Delivered in CSV format for easy integration with research tools and analytical platforms.
• Source: Extracted directly from CNBC’s economy news section, ensuring accuracy and relevance.

Use Cases

• Economic Research: Gain insights into U.S. and global economic policies, market trends, and industry developments.
• Sentiment Analysis: Assess the sentiment of economic articles to gauge market perspectives and investor confidence.
• Financial Modeling: Build forecasting models leveraging key economic indicators discussed in the dataset.
• Content Creation: Develop research-backed reports, articles, and presentations on economic topics.

Who Benefits?

• Researchers & Academics studying macro-economics or financial policy.
  
• Data Scientists building AI models, trend analyzers, or economic forecasting tools.
  
• Economists & Analysts need real-world news data for policy analysis.
  
• Content Strategists who write data-backed articles about economic trends.

Why Choose This Dataset?

• No need to manually scrape CNBC — data is pre-extracted and clean.
  
• High-quality economy news metadata enables detailed filtering (by date, author, topic).
  
• Ready for machine learning, sentiment analysis, or building news-based economic models.
  
• Well-suited for trend tracking, policy analysis, and economic forecasting.

Explore More News Datasets

Interested in additional structured news datasets for your research or analytics needs? Check out our news dataset collection to find datasets tailored for diverse analytical applications.

Stay informed with our comprehensive Financial News Dataset, designed for investors, analysts, and businesses to track market trends, monitor financial events, and make data-driven decisions.

Dataset Features

Financial News Articles: Access structured financial news data, including headlines, summaries, full articles, publication dates, and source details. Market & Economic Indicators: Track financial reports, stock market updates, economic forecasts, and corporate earnings announcements. Sentiment & Trend Analysis: Analyze news sentiment, categorize articles by financial topics, and monitor emerging trends in global markets. Historical & Real-Time Data: Retrieve historical financial news archives or access continuously updated feeds for real-time insights.

Customizable Subsets for Specific Needs Our Financial News Dataset is fully customizable, allowing you to filter data based on publication date, region, financial topics, sentiment, or specific news sources. Whether you need broad coverage for market research or focused data for investment analysis, we tailor the dataset to your needs.

Popular Use Cases

Investment Strategy & Risk Management: Monitor financial news to assess market risks, identify investment opportunities, and optimize trading strategies. Market & Competitive Intelligence: Track industry trends, competitor financial performance, and economic developments. AI & Machine Learning Training: Use structured financial news data to train AI models for sentiment analysis, stock prediction, and automated trading. Regulatory & Compliance Monitoring: Stay updated on financial regulations, policy changes, and corporate governance news. Economic Research & Forecasting: Analyze financial news trends to predict economic shifts and market movements.

Whether you're tracking stock market trends, analyzing financial sentiment, or training AI models, our Financial News Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.

Japan's main stock market index, the JP225, rose to 49553 points on December 2, 2025, gaining 0.51% from the previous session. Over the past month, the index has declined 3.78%, though it remains 26.25% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Japan. Japan Stock Market Index (JP225) - values, historical data, forecasts and news - updated on December of 2025.

Stay ahead with our comprehensive News Dataset, designed for businesses, analysts, and researchers to track global events, monitor media trends, and extract valuable insights from news sources worldwide.

Dataset Features

News Articles: Access structured news data, including headlines, summaries, full articles, publication dates, and source details. Ideal for media monitoring and sentiment analysis. Publisher & Source Information: Extract details about news publishers, including domain, region, and credibility indicators. Sentiment & Topic Classification: Analyze news sentiment, categorize articles by topic, and track emerging trends in real time. Historical & Real-Time Data: Retrieve historical archives or access continuously updated news feeds for up-to-date insights.

Customizable Subsets for Specific Needs Our News Dataset is fully customizable, allowing you to filter data based on publication date, region, topic, sentiment, or specific news sources. Whether you need broad coverage for trend analysis or focused data for competitive intelligence, we tailor the dataset to your needs.

Popular Use Cases

Media Monitoring & Reputation Management: Track brand mentions, analyze media coverage, and assess public sentiment. Market & Competitive Intelligence: Monitor industry trends, competitor activity, and emerging market opportunities. AI & Machine Learning Training: Use structured news data to train AI models for sentiment analysis, topic classification, and predictive analytics. Financial & Investment Research: Analyze news impact on stock markets, commodities, and economic indicators. Policy & Risk Analysis: Track regulatory changes, geopolitical events, and crisis developments in real time.

Whether you're analyzing market trends, monitoring brand reputation, or training AI models, our News Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.

It is forecast that the global online trading market will increase at a global compound annual growth rate of *** percent per year, increasing to an estimated **** billion U.S. dollars in 2026. This is from a base of around ***** billion U.S. dollars in 2022. Following the coronavirus pandemic beginning in 2020, online trading activity increased among millennial investors. Many online brokers, including Robinhood, experienced notable growth in the number of platform users from the second quarter of 2020 through to 2021. A low-cost business model, paired with technological integration and social media promotion were contributing factors to the popularity of online trading. What is an online trading platform? The online trading market is typically accessed through an online market broker, providing a platform for users to track market prices and execute buy and sell orders on financial securities. The user typically holds their portfolio through an online broker. The number of monthly downloads for leading online trading apps spiked in early 2021. While this was influenced by media attention to popular news stories such as the increase in the price of GameStop shares, online trading is expected to continue as an alternative to traditional investment methods. Factors driving online trading The integration of technology has improved investing activities. From a global survey, most respondents stated technology made investing easier, cheaper, and more efficient. The use of technology allowed information such as real-time data, industry and firm reports, and trading notifications to be more accessible directly to the investor. Online platforms had experienced an increase in the number of trades placed per day, in 2019, interactive brokers had an average of 1,380 trades placed per day. This number steadily increased to 3,905 trades per day in 2021. Technological integration allowed trading via online platforms to be an alternative to traditional methods of relying on an in-person full-service broker.

United Kingdom's main stock market index, the GB100, fell to 9690 points on December 2, 2025, losing 0.13% from the previous session. Over the past month, the index has declined 0.12%, though it remains 15.91% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from United Kingdom. United Kingdom Stock Market Index (GB100) - values, historical data, forecasts and news - updated on December of 2025.

The crude oil market is experiencing volatility due to geopolitical tensions, the coronavirus outbreak, production cuts, increasing US oil production, and the shift towards cleaner energy sources.

Global newspaper publishers are highly susceptible to macroeconomic trends, as consumers tend to reduce subscriptions during volatile periods and advertisers tend to withdraw or limit spending when times are uncertain. Still, regardless of economic performance, global newspaper publishers have experienced a decades-long, steady downward spiral as consumers increasingly obtain news from other media outlets. Traditional newspapers, facing significant declines in readership, have watched as consumers pivot to digital platforms for their news consumption. The rise of social media, streaming and other online formats increasingly relegates print newspapers to the sidelines. Despite some publishers enhancing their online presence, monetizing digital readers still lags behind the revenue generated by print circulation. As a result, over the past five years, revenue has been declining at a CAGR of 3.1% and is expected to reach $80.5 billion in 2025, when revenue is estimated to drop 1.5%. Digital adoption has been a lifeline for those who have quickly adopted it, though it has done little to fully compensate for the losses in print subscriptions. Subscription-based models and the introduction of e-papers have become widespread, yet they haven't been the panacea many hoped for. As more consumers flock to free news sources, publishers have sought various means to attract subscribers. Most often, publishers offer limited discounted rates for online platforms as more consumers are interested in digital subscriptions. However, retaining subscribers past the date of the discounted rate is complex and many newspapers lose customers during this period. Furthermore, the climb in discounted rates and lower advertising fees due to lower readership puts greater pressure on profit. With few cost-cutting measures left, some newspaper publishers are forgoing print circulation altogether and transitioning into online-only publications. Overall industry profit has eroded as waning demand, combined with low-cost alternatives, has driven down prices. Over the next five years, global newspaper publishing will continue to deteriorate as online options proliferate and more of the public reduces reading habits, weakening circulation. With many consumers already accustomed to obtaining news for free through various outlets, few will find a reason to begin paying for subscriptions. As readership continues to drop, publishers will face increasing difficulty in attracting advertisers and will be compelled to lower rates further. Ultimately, revenue will fall at a CAGR of 1.7% over the next five years, reaching an estimated $73.9 billion in 2030.

China's main stock market index, the SHANGHAI, fell to 3898 points on December 2, 2025, losing 0.42% from the previous session. Over the past month, the index has declined 1.98%, though it remains 15.36% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from China. China Shanghai Composite Stock Market Index - values, historical data, forecasts and news - updated on December of 2025.

Negative News Entity Disambiguation Market Outlook

According to our latest research, the Global Negative News Entity Disambiguation market size was valued at $1.5 billion in 2024 and is projected to reach $5.2 billion by 2033, expanding at a CAGR of 14.8% during 2024–2033. One major factor fueling the rapid growth of this market globally is the increasing demand for advanced risk and compliance management solutions across highly regulated sectors such as BFSI and healthcare. As organizations face mounting pressure to monitor, analyze, and act upon negative news mentions related to entities they engage with, the need for sophisticated entity disambiguation tools—capable of accurately distinguishing between similarly named individuals or organizations in vast news datasets—has become critical. This is further driven by the proliferation of digital media and the growing importance of brand reputation management in a hyper-connected world, making robust negative news monitoring and analysis a top priority for enterprises worldwide.

Regional Outlook

North America holds the largest share of the Negative News Entity Disambiguation market, accounting for over 38% of global revenue in 2024. This dominance is primarily attributed to the region’s mature technological landscape, widespread adoption of AI-driven analytics, and the presence of major financial institutions and multinational corporations that require robust risk mitigation tools. Regulatory frameworks, such as anti-money laundering (AML) and know-your-customer (KYC) guidelines, have further compelled organizations to invest in advanced entity disambiguation solutions. Additionally, North America’s vibrant ecosystem of technology vendors and service providers, coupled with high digital literacy and early adoption of cloud-based deployment models, continues to drive market expansion. The region’s focus on innovation and compliance, supported by significant R&D investments, ensures that North American enterprises remain at the forefront of leveraging negative news analytics for both operational efficiency and reputational safeguarding.

The Asia Pacific region is projected to be the fastest-growing market, with a remarkable CAGR of over 17% during the forecast period. This accelerated growth is driven by the rapid digital transformation across emerging economies such as China, India, and Southeast Asian nations, where enterprises are increasingly recognizing the value of proactive risk and reputation management. The surge in cross-border business activities, heightened regulatory scrutiny, and the growing volume of digital news content are compelling organizations in the region to adopt advanced negative news entity disambiguation solutions. Furthermore, governments are investing in digital infrastructure and encouraging the adoption of AI-based compliance technologies, which is attracting significant investments from both local and international vendors. Strategic partnerships, joint ventures, and the establishment of regional data centers are also facilitating the deployment of scalable, cloud-based solutions tailored to the unique regulatory and linguistic landscapes of Asia Pacific.

Emerging economies in Latin America and the Middle East & Africa are gradually increasing their adoption of negative news entity disambiguation technologies, albeit at a slower pace compared to developed regions. In these markets, organizations face challenges such as limited digital infrastructure, budget constraints, and varying degrees of regulatory enforcement. However, the growing incidence of financial crime, fraud, and reputational risks is prompting banks, government agencies, and large enterprises to invest in entity disambiguation solutions for enhanced due diligence and risk monitoring. Localization requirements, such as support for regional languages and context-specific entity resolution, are influencing product development and deployment strategies. While adoption remains nascent, ongoing policy reforms aimed at strengthening financial transparency and combating illicit activities are expected to gradually boost demand for these technologies in the coming years.

Report Scope

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WiseTech Global reported AUD23.16B in Market Capitalization this December of 2025, considering the latest stock price and the number of outstanding shares.Data for WiseTech Global | WTC - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last December in 2025.

According to Cognitive Market Research, the global Online News Platform market size was USD 61325.2 million in 2024. It will expand at a compound annual growth rate (CAGR) of 5.20% 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 24530.08 million in 2024 and will grow at a compound annual growth rate (CAGR) of 3.4% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 18397.56 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 14104.80 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.2% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 3066.26 million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.6% 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 1226.50 million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.9% from 2024 to 2031.
The Localized Editions is the fastest growing segment of the Online News Platform industry

Market Dynamics of Online News Platform Market

Key Drivers for Online News Platform Market

Increased Internet Penetration to Boost Market Growth

Increased net penetration has transformed how human beings devour news, presenting unprecedented get entry to facts. As broadband and cellular connectivity extend globally, individuals can easily access a lot of online information platforms, from set-up media retailers to unbiased bloggers. This shift has democratized news consumption, taking into account various perspectives and real-time updates. Furthermore, the benefit of cell devices allows users to stay knowledgeable on the move, main to a surge in digital readership. As a result, traditional print media is dealing with demanding situations while online news assets continue to grow in popularity, reshaping the panorama of journalism and data dissemination.

Demand for Real-time Information to Drive Market Growth

The call for real-time facts is growing as consumers are seeking on-the-spot access to information updates. With the quick-paced nature of nowadays's global, human beings want to live knowledgeable approximately activities as they unfold. Online information structures are properly geared up to meet this need, presenting on-the-spot updates through websites, social media, and cellular apps. This capability permits customers to acquire breaking news indicators and live coverage of huge occasions, enhancing their universal information consumption experience. As a result, conventional media outlets are adapting to provide timely information, even as online structures thrive with the aid of catering to the growing expectation for immediacy in information delivery.

Restraint Factor for the Online News Platform Market

Competition will Limit Market Growth

The online news panorama is characterized by means of severe opposition, with numerous systems striving to capture target market interest. Established media outlets, digital-local news corporations, and independent bloggers all compete for readership, making it hard for brand-spanking new entrants to take advantage of traction. In these crowded surroundings, differentiating content material and building a loyal audience is important for fulfillment. New platforms frequently face limitations, which include restrained sources, brand popularity, and the need to set up credibility. To thrive, they should leverage modern techniques, engage users via compelling storytelling, and utilize social media correctly to stand out and attract a devoted following within the saturated marketplace.

Impact of Covid-19 on the Online News Platform Market

The COVID-19 pandemic substantially impacted the net information platform marketplace, accelerating shifts in consumer conduct and content material intake. With lockdowns and social distancing measures in the vicinity, more humans turned to digital resources for news updates, resulting in a surge in traffic for online structures. This improved call for statistics approximately the pandemic caused better engagement and subscriptions for plenty of information websites. However, advertising revenues faced demanding situa...

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