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The main stock market index of United States, the US500, rose to 6327 points on July 23, 2025, gaining 0.27% from the previous session. Over the past month, the index has climbed 3.85% and is up 16.57% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

Oil prices dropped today due to concerns over the economic impact of the COVID-19 pandemic and the increase in oil supply. However, the approval of vaccines and discussions of production cuts provide some hope for a potential recovery in the future.

According to Cognitive Market Research, the global stock market size will be USD 3645.2 million in 2024. It will expand at a compound annual growth rate (CAGR) of 13% 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 1458.1 million in 2024 and will grow at a compound annual growth rate (CAGR) of 11.2% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 1093.6 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 838.4 million in 2024 and will grow at a compound annual growth rate (CAGR) of 15% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 182.3 million in 2024 and will grow at a compound annual growth rate (CAGR) of 12.4% 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 72.9 million in 2024 and will grow at a compound annual growth rate (CAGR) of 12.7% from 2024 to 2031.
The broker end users held the highest stock market revenue share in 2024.

Market Dynamics of Stock Market

Key Drivers for the Stock Market

Rising Demand for Real-Time Data and Analytics to be an Emerging Market Trend

The increasing need for real-time data and advanced analytics is a significant driver in the stock trading and investing market growth. Investors and traders require up-to-the-minute information on stock prices, market trends, and financial news to make informed decisions quickly. As financial markets become more dynamic and competitive, the ability to access and analyze real-time data becomes crucial for success. Trading applications that offer real-time updates, advanced charting tools, and detailed analytics provide users with a competitive edge by enabling them to react swiftly to market movements. This heightened demand for real-time insights fuels the development and adoption of sophisticated trading platforms that cater to both professional traders and retail investors seeking to maximize their investment opportunities.

Increasing Adoption of Mobile Trading Platforms to Boost Market Growth

The rapid adoption of mobile trading platforms is another key driver for the stock market expansion. With the proliferation of smartphones and mobile internet access, investors are increasingly favoring mobile platforms for their trading activities due to their convenience and accessibility. Mobile trading apps offer users the ability to trade, monitor portfolios, and access financial information on the go, which appeals to both active traders and casual investors. This shift towards mobile platforms is supported by innovations in-app functionality, user experience, and security features. As more investors seek flexibility and real-time engagement with their investments, the demand for sophisticated and user-friendly mobile trading applications continues to rise, propelling market growth.

Restraint Factor for the Stock Market

Stringent Rules and Regulations to Impede the Adoption of Online Trading Platforms

Regulatory compliance and legal challenges are major restraints for the stock trading and investing market share. The financial industry is heavily regulated, with strict rules governing trading practices, data protection, and financial disclosures. Compliance with these regulations requires substantial investment in legal expertise, technology, and administrative processes. Changes in regulations can also introduce uncertainty and additional compliance costs for application providers. For example, regulations such as the Markets in Financial Instruments Directive II (MiFID II) in Europe and the Dodd-Frank Act in the U.S. impose stringent requirements on trading practices and transparency. Failure to adhere to these regulations can result in legal penalties and damage to a company’s reputation, which can inhibit market growth and innovation in trading applications.

Market Volatility and Investor Uncertainty

The stock market is highly sensitive to global economic conditions, geopolitical tensions, interest rate fluctuations, and unexpected events (such as pandemics or wars). This inherent volatility can lead to sharp declines in investor confidence and capital outflows, especially among retai...

Crude oil stock market news is crucial for investors, traders, and industries dependent on oil prices. Factors such as OPEC decisions, global economic trends, geopolitical events, and market speculation influence crude oil prices. Financial news outlets and specialized publications report regular updates on crude oil prices and other relevant factors affecting the market.

Japan's main stock market index, the JP225, rose to 40790 points on July 23, 2025, gaining 2.55% from the previous session. Over the past month, the index has climbed 5.15% and is up 4.18% compared to the same time last year, 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 July of 2025.

Prices for Global Equity Index including live quotes, historical charts and news. Global Equity Index was last updated by Trading Economics this July 23 of 2025.

Stock Analysis Software Market Outlook

The global stock analysis software market size was valued at approximately USD 1.2 billion in 2023 and is projected to reach around USD 3.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 12.5% during the forecast period. The growth of this market is driven by the increasing adoption of advanced analytics tools by individual investors and financial institutions to make informed investment decisions. The rising demand for automated trading systems and the integration of artificial intelligence (AI) and machine learning (ML) in stock analysis software are significant growth factors contributing to the market expansion.

One of the primary growth factors for the stock analysis software market is the increasing complexity and volume of financial data. With the exponential growth of data from various sources such as social media, news articles, and financial statements, investors and financial analysts require sophisticated tools to process and interpret this information accurately. Stock analysis software equipped with AI and ML algorithms can analyze vast datasets in real-time, providing valuable insights and predictive analytics that enhance investment strategies. Moreover, the growing trend of algorithmic trading, which relies heavily on high-speed data processing and automated decision-making, is further propelling the market growth.

Another crucial growth driver is the rising awareness and adoption of stock analysis software among individual investors. As more individuals seek to actively manage their investment portfolios, there is a growing demand for user-friendly and cost-effective stock analysis tools that offer comprehensive market analysis, technical indicators, and personalized investment recommendations. The proliferation of mobile applications and the increasing accessibility of cloud-based stock analysis solutions have made it easier for retail investors to access advanced analytical tools, thereby contributing to market expansion.

The integration of innovative technologies such as natural language processing (NLP) and sentiment analysis into stock analysis software is also a significant growth factor. These technologies enable the software to interpret and analyze unstructured data from news articles, social media, and other textual sources to gauge market sentiment and predict stock price movements. This capability is particularly valuable in today's fast-paced financial markets, where sentiment and news events can have a substantial impact on stock prices. The continuous advancements in AI and NLP technologies are expected to drive further innovations and improvements in stock analysis software, thereby boosting market growth.

In the evolving landscape of financial technology, Investor Relations Tools have become indispensable for companies seeking to maintain transparent and effective communication with their stakeholders. These tools facilitate seamless interaction between companies and their investors, providing real-time updates, financial reports, and strategic insights. By leveraging these tools, companies can enhance their investor engagement strategies, build trust, and foster long-term relationships with their shareholders. The integration of advanced analytics and AI-driven insights into Investor Relations Tools further empowers companies to tailor their communication strategies, ensuring that they meet the diverse needs of their investor base. As the demand for transparency and accountability in financial markets continues to grow, the adoption of sophisticated Investor Relations Tools is expected to rise, playing a crucial role in the broader ecosystem of stock analysis software.

From a regional perspective, North America is anticipated to hold the largest market share due to the high concentration of financial institutions, brokerage firms, and individual investors in the region. The presence of key market players and the early adoption of advanced technologies also contribute to the dominant position of North America in the global stock analysis software market. Additionally, the Asia Pacific region is expected to witness significant growth during the forecast period, driven by the increasing number of retail investors, rapid economic development, and the growing financial markets in countries such as China and India.

Component Analysis

Description

This dataset offers a comprehensive historical record of stock prices for the world's most famous brands, with daily updates. The data spans from January 1, 2000, to the present day , providing an extensive timeline of stock market information for various global brands.

Key Features

• Date: The date of the stock price data.
• Open: The opening price of the stock on that date.
• High: The highest price the stock reached during the trading day.
• Low: The lowest price the stock reached during the trading day.
• Close: The closing price of the stock on that date.
• Volume: The trading volume, i.e., the number of shares traded on that date.
• Dividends: Dividends paid on that date (if any).
• Stock Splits: Information about stock splits (if any).
• Brand_Name: The name of the brand or company.
• Ticker: Ticker symbol for the stock.
• Industry_Tag: The industry category or sector to which the brand belongs.
• Country: The country where the brand is headquartered or primarily operates.

Potential Use Cases

• Stock Market Analysis: Analyze historical stock prices to identify trends and patterns in the stock market.
• Brand Performance: Evaluate the performance of various brands in the stock market over time.
• Investment Strategies: Develop investment strategies based on historical stock data for specific brands.
• Sector Analysis: Explore how different industries or sectors are performing in the stock market.
• Country Comparison: Compare the stock performance of brands across different countries.
• Market Sentiment Analysis: Analyze stock price movements in relation to news or events affecting specific brands or industries.

If you find this dataset useful, please consider giving it a vote! 🙂❤️

China's main stock market index, the SHANGHAI, rose to 3582 points on July 22, 2025, gaining 0.62% from the previous session. Over the past month, the index has climbed 5.92% and is up 22.86% compared to the same time last year, 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 July of 2025.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

MSCI World: Reflecting Global Economic Trends or Inflated Valuations?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

This dataset provides comprehensive access to financial market data from Google Finance in real-time. Get detailed information on stocks, market quotes, trends, ETFs, international exchanges, forex, crypto, and related news. Perfect for financial applications, trading platforms, and market analysis tools. The dataset is delivered in a JSON format via REST API.

Israel's main stock market index, the TA-125, fell to 3116 points on July 22, 2025, losing 0.04% from the previous session. Over the past month, the index has climbed 8.16% and is up 50.58% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Israel. Israel Stock Market (TA-125) - values, historical data, forecasts and news - updated on July of 2025.

At Forestreet we want to democratise market and innovation discovery. Built and guided by industry experts over the last five years, our AI-powered market intelligence and vendor discovery software uses advanced analytics, NLP and machine learning to map, categorise and analyse any market in fine detail. The current expensive, time-consuming and biased research model has remained static for decades. We think things need shaking up.

Our market discovery and analytics platform is the only tool on the market that can make sense of noise and deliver data-led insights to support your business. Leveraging the latest in AI and automation, Forestreet can provide structured, real-time information to support your process.

Comprehensive market mapping in minutes

From a seed company or key words, users can fully map out highly complex markets in a matter of minutes. No more biased presentations, outdated listings or incomplete datasets. Gone are the days of waiting months for a generic analyst report. With all companies identified live through our internet scraping mechanics, our agile software is as dynamic as the industries you monitor and perfectly catered to your needs. So you can make confident decisions, knowing you’re acting on the most up to date research.

With our SaaS software, you can find companies you didn't know you were competing with and understand their services right down to a features level. Avoid that moment in meetings when a client says, "but what about company X?" Our Forestreet dashboard can have you responding in seconds with fact-based details showing how your product’s features compare to any competitor’s offerings.

Dive deep with our in-depth analysis tools

Beyond its extensive mapping and categorisation capabilities, the Forestreet platform has detailed enrichment options allowing you to deep dive into an individual company’s characteristics and performance. This includes data about size, funding and location, as well as public perceptions and interaction. Our company Momentum scores also combine a range of signals to give an insight into a company’s potential for growth and current market interest.

Other available tools include the Feature Architecture, which shows all the features offered by the whole market, and our Phrase Explorer, which allows you to search companies based on the specific language they use to describe themselves.

Stay at the forefront with up to date news and sentiment analysis

Make sure you know what’s been talked about in your market right now with our news and insights feature. Our AI crawls popular and hard-to-find news sites, providing you with unique comments and feedback about what's going on anywhere in the world. These news sources go well beyond what can be found on Google News, or even paid services like Factiva, so you’ll never get out of touch with the latest trends and developments.

And no need to worry about old data or your key findings getting out of date. In today’s world, we know that markets are constantly shifting and are changing faster and more unpredictably than ever before. But with the ability to refresh and update data on demand, you can embrace smart decision making at pace.

Our platform enables you to understand your market segment with the granularity required for highly informed sourcing, competitor analysis, investment and procurement decisions or de-risk regulation. Insightful data generated by you for any market or geography. All at your fingertips.

News and Magazines App Market size was valued at USD 1.20 billion in 2021 and is poised to grow from USD 2.15 billion in 2022 to USD 4.55 billion by 2030, growing at a CAGR of 11.2%

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.

Supplementary information files for the article Emerging stock market volatility and economic fundamentals: the importance of US uncertainty spillovers, financial and health crises

Abstract: This paper studies the US and global economic fundamentals that exacerbate emerging stock markets volatility and can be considered as systemic risk factors increasing financial stability vulnerabilities. We apply the bivariate HEAVY system of daily and intra-daily volatility equations enriched with powers, leverage, and macro-effects that improve its forecasting accuracy significantly. Our macro-augmented asymmetric power HEAVY model estimates the inflammatory effect of US uncertainty and infectious disease news impact on equities alongside global credit and commodity factors on emerging stock index realized volatility. Our study further demonstrates the power of the economic uncertainty channel, showing that higher US policy uncertainty levels increase the leverage effects and the impact from the common macro-financial proxies on emerging markets’ financial volatility. Lastly, we provide evidence on the crucial role of both financial and health crisis events (the 2008 global financial turmoil and the recent Covid-19 pandemic) in raising markets’ turbulence and amplifying the volatility macro-drivers impact, as well.

According to the most recently available data, the leading news company in the world was News Corp., with a market cap of 7.9 billion U.S. dollars. Some of News Corp.'s most famous brands include The Sun, HarperCollins Publishers, and Fox News. Ranked second was The New York Times Company with a market cap of 6.8 billion U.S. dollars.

Enhancing Financial Market Predictions: Causality-Driven Feature Selection This paper introduces FinSen dataset that revolutionizes financial market analysis by integrating economic and financial news articles from 197 countries with stock market data. The dataset’s extensive coverage spans 15 years from 2007 to 2023 with temporal information, offering a rich, global perspective 160,000 records on financial market news. Our study leverages causally validated sentiment scores and LSTM models to enhance market forecast accuracy and reliability.

Our FinSen Dataset

This repository contains the dataset for Enhancing Financial Market Predictions: Causality-Driven Feature Selection, which has been accepted in ADMA 2024.

If the dataset or the paper has been useful in your research, please add a citation to our work:

@article{liang2024enhancing, title={Enhancing Financial Market Predictions: Causality-Driven Feature Selection}, author={Liang, Wenhao and Li, Zhengyang and Chen, Weitong}, journal={arXiv e-prints}, pages={arXiv--2408}, year={2024} }

Datasets [FinSen] can be downloaded manually from the repository as csv file. Sentiment and its score are generated by FinBert model from the Hugging Face Transformers library under the identifier "ProsusAI/finbert". (Araci, Dogu. "Finbert: Financial sentiment analysis with pre-trained language models." arXiv preprint arXiv:1908.10063 (2019).)

We only provide US for research purpose usage, please contact w.liang@adelaide.edu.au for other countries (total 197 included) if necessary.

We also provide other NLP datasets for text classification tasks here, please cite them correspondingly once you used them in your research if any.

20Newsgroups. Joachims, T., et al.: A probabilistic analysis of the rocchio algorithm with tfidf for text categorization. In: ICML. vol. 97, pp. 143–151. Citeseer (1997) AG News. Zhang, X., Zhao, J., LeCun, Y.: Character-level convolutional networks for text classification. Advances in neural information processing systems 28 (2015) Financial PhraseBank. Malo, P., Sinha, A., Korhonen, P., Wallenius, J., Takala, P.: Good debt or bad debt: Detecting semantic orientations in economic texts. Journal of the Association for Information Science and Technology 65(4), 782–796 (2014)

Dataloader for FinSen We provide the preprocessing file finsen.py for our FinSen dataset under dataloaders directory for more convienient usage.

Models - Text Classification

DAN-3.

Gobal Pooling CNN.

Models - Regression Prediction

LSTM

Using Sentiment Score from FinSen Predict Result on S&P500 Dependencies The code is based on PyTorch under code frame of https://github.com/torrvision/focal_calibration, please cite their work if you found it is useful.

:smiley: ☺ Happy Research !

Market Overview

The global Predictive AI in Stock Market sector is projected to witness robust growth in the coming years. The market size is anticipated to reach approximately USD 4,100.6 million by 2034, rising from an estimated USD 831.5 million in 2024. This expansion reflects a strong compound annual growth rate (CAGR) of 17.3% during the forecast period spanning 2025 to 2034.

This growth can be attributed to the increasing reliance on artificial intelligence to enhance trading strategies, forecast market movements, and support data-driven investment decisions. As financial institutions and individual investors continue to seek better accuracy in forecasting and risk management, the adoption of predictive AI tools is expected to accelerate.

In 2024, North America emerged as the leading regional market, accounting for more than 34.1% of the global revenue share. This equated to a market value of USD 283.5 million. The region’s dominance is driven by early technology adoption, well-established financial infrastructure, and the presence of key AI solution providers.