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.

Euro Area's main stock market index, the EU50, rose to 5381 points on July 24, 2025, gaining 0.70% from the previous session. Over the past month, the index has climbed 2.45% and is up 11.84% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Euro Area. Euro Area Stock Market Index (EU50) - values, historical data, forecasts and news - updated on July of 2025.

Use our Stock prices dataset to access comprehensive financial and corporate data, including company profiles, stock prices, market capitalization, revenue, and key performance metrics. This dataset is tailored for financial analysts, investors, and researchers to analyze market trends and evaluate company performance.

Popular use cases include investment research, competitor benchmarking, and trend forecasting. Leverage this dataset to make informed financial decisions, identify growth opportunities, and gain a deeper understanding of the business landscape. The dataset includes all major data points: company name, company ID, summary, stock ticker, earnings date, closing price, previous close, opening price, and much more.

China's main stock market index, the SHANGHAI, rose to 3606 points on July 24, 2025, gaining 0.65% from the previous session. Over the past month, the index has climbed 4.33% and is up 24.91% 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.

France's main stock market index, the FR40, fell to 7744 points on July 22, 2025, losing 0.69% from the previous session. Over the past month, the index has climbed 2.74% and is up 1.92% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from France. France Stock Market Index (FR40) - values, historical data, forecasts and news - updated on July of 2025.

While the global coronavirus (COVID-19) pandemic caused all major stock market indices to fall sharply in March 2020, both the extent of the decline at this time, and the shape of the subsequent recovery, have varied greatly. For example, on March 15, 2020, major European markets and traditional stocks in the United States had shed around 40 percent of their value compared to January 5, 2020. However, Asian markets and the NASDAQ Composite Index only shed around 20 to 25 percent of their value. A similar story can be seen with the post-coronavirus recovery. As of November 14, 2021 the NASDAQ composite index value was around 65 percent higher than in January 2020, while most other markets were only between 20 and 40 percent higher.

Why did the NASDAQ recover the quickest?

Based in New York City, the NASDAQ is famously considered a proxy for the technology industry as many of the world’s largest technology industries choose to list there. And it just so happens that technology was the sector to perform the best during the coronavirus pandemic. Accordingly, many of the largest companies who benefitted the most from the pandemic such as Amazon, PayPal and Netflix, are listed on the NADSAQ, helping it to recover the fastest of the major stock exchanges worldwide.

Which markets suffered the most?

The energy sector was the worst hit by the global COVID-19 pandemic. In particular, oil companies share prices suffered large declines over 2020 as demand for oil plummeted while workers found themselves no longer needing to commute, and the tourism industry ground to a halt. In addition, overall share prices in two major stock exchanges – the London Stock Exchange (as represented by the FTSE 100 index) and Hong Kong (as represented by the Hang Seng index) – have notably recovered slower than other major exchanges. However, in both these, the underlying issue behind the slower recovery likely has more to do with political events unrelated to the coronavirus than it does with the pandemic – namely Brexit and general political unrest, respectively.

Snapshot img

Securities Exchanges Market Size 2025-2029

The securities exchanges market size is forecast to increase by USD 56.67 billion at a CAGR of 12.5% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing demand for investment opportunities. This trend is fueled by a global economic recovery and a rising interest in various asset classes, particularly in emerging markets. Another key driver is the increasing focus on sustainable and environmental, social, and governance (ESG) investing. This shift reflects a growing awareness of the importance of long-term value creation and the role of exchanges in facilitating socially responsible investments. This trend is driven by the expanding securities business units, including stocks, bonds, mutual funds, and other securities, which cater to the needs of investment firms and individual investors. However, the market is not without challenges. Increasing market volatility poses a significant risk for exchanges and their clients.
Furthermore, the rapid digitization of trading and the emergence of alternative trading platforms are disrupting traditional exchange business models. To navigate these challenges, exchanges must adapt by investing in technology, expanding their product offerings, and building strong regulatory frameworks. Data analytics and big data are also crucial tools for e-brokerage firms to gain insights and make informed decisions. By doing so, they can capitalize on the market's growth potential and maintain their competitive edge. Geopolitical tensions, economic instability, and regulatory changes can all contribute to market fluctuations and uncertainty.

What will be the Size of the Securities Exchanges Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

In the dynamic market, financial instrument classification plays a crucial role in facilitating efficient trade matching through advanced execution quality metrics and order book liquidity. Quantitative trading models leverage options clearing corporation data to optimize portfolio holdings, while trade matching engines utilize high-speed data storage solutions and portfolio optimization algorithms to minimize latency and enhance market depth indicators. Data center infrastructure and network bandwidth capacity are essential components for supporting complex algorithmic trading strategies, including latency reduction and price volatility forecasting. Market impact measurement and risk assessment methodologies are integral to managing market impact and mitigating fraud, ensuring regulatory compliance through transaction reporting standards and regulatory compliance software.

Exchange traded funds (ETFs) have gained popularity, necessitating robust quote dissemination systems and trade surveillance analytics. Server virtualization and cybersecurity threat mitigation strategies further strengthen the market's resilience, enabling seamless integration of data-driven quantitative models and sophisticated fraud detection algorithms. Additionally, users of online trading platforms can easily monitor the performance of their assets thanks to real-time stock data.

How is this Securities Exchanges Industry segmented?

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

Service

  Market platforms
  Capital access platforms
  Others


Trade Finance Instruments

  Equities
  Derivatives
  Bonds
  Exchange-traded funds
  Others


Type

  Large-cap exchanges
  Mid-cap exchanges
  Small-cap exchanges


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Switzerland
    UK


  APAC

    China
    Hong Kong
    India
    Japan


  Rest of World (ROW)

By Service Insights

The Market platforms segment is estimated to witness significant growth during the forecast period. The market is characterized by advanced technologies and systems that enable efficient price discovery, manage settlement risk, and ensure regulatory compliance. Market platforms, which include trading platforms, order-matching systems, and market data dissemination, hold the largest share of the market. These platforms facilitate the buying and selling of securities, providing market liquidity and transparency. Real-time market surveillance and high-frequency trading infrastructure are crucial components, ensuring fair and orderly markets and enabling efficient trade execution. Financial modeling techniques and algorithmic trading platforms optimize trading strategies, while electronic communication networks and central counterparty cleari

US retail investors had a relatively strong opinion on whether the stock market was more profitable than investments in cryptocurrencies. Nearly 32 percent of the respondents to a survey listed crypto as potentially having the most risk, against almost 38 percent preferring the stock market over virtual currencies in terms of profitability. One potential reason why this could be found at the US opinion on risk: slightly more respondents felt that the stock market was a more risky to invest in. This is quite different from answers given to these same questions but by consumers from the United Kingdom.

SET: No of Listed Transferable Subscription Right data was reported at 0.000 Unit in 2017. This stayed constant from the previous number of 0.000 Unit for 2016. SET: No of Listed Transferable Subscription Right data is updated yearly, averaging 0.000 Unit from Dec 2004 (Median) to 2017, with 14 observations. SET: No of Listed Transferable Subscription Right data remains active status in CEIC and is reported by The Stock Exchange of Thailand. The data is categorized under Global Database’s Thailand – Table TH.Z010: The Stock Exchange of Thailand: Market Statistics: Annual.

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.

India's main stock market index, the SENSEX, rose to 82727 points on July 23, 2025, gaining 0.66% from the previous session. Over the past month, the index has climbed 0.82% and is up 3.22% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from India. BSE SENSEX Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

Gain access to LSEG's National Stock Exchange of India data, India's largest stock exchange with more than 180,000 terminals across 600 districts.

Stock market index in Mexico, June, 2025 The most recent value is 130.44 points as of June 2025, a decline compared to the previous value of 131.33 points. Historically, the average for Mexico from January 1970 to June 2025 is 35.98 points. The minimum of 0 points was recorded in January 1970, while the maximum of 131.33 points was reached in May 2025. | TheGlobalEconomy.com

Graph and download economic data for Financial Market: Share Prices for Italy (SPASTT01ITQ661N) from Q1 1957 to Q2 2025 about Italy and stock market.

The Value Line Investment Survey is one of the oldest, continuously running investment advisory publications. Since 1955, the Survey has been published in multiple formats including print, loose-leaf, microfilm and microfiche. Data from 1997 to present is now available online. The Survey tracks 1700 stocks across 92 industry groups. It provides reported and projected measures of firm performance, proprietary rankings and analysis for each stock on a quarterly basis. DATA AVAILABLE FOR YEARS: 1980-1989 This dataset, a subset of the Survey covering the years 1980-1989 has been digitized from the microfiche collection available at the Dewey Library (FICHE HG 4501.V26). It is only available to MIT students and faculty for academic research. Published weekly, each edition of the Survey has the following three parts: Summary & Index: includes an alphabetical listing of all industries with their relative ranking and the page number for detailed industry analysis. It also includes an alphabetical listing of all stocks in the publication with references to their location in Part 3, Ratings & Reports. Selection & Opinion: contains the latest economic and stock market commentary and advice along with one or more pages of research on interesting stocks or industries, and a variety of pertinent economic and stock market statistics. It also includes three model stock portfolios. Ratings & Reports: This is the core of the Value Line Investment Survey. Preceded by an industry report, each one-page stock report within that industry includes Timeliness, Safety and Technical rankings, 3-to 5-year analyst forecasts for stock prices, income and balance sheet items, up to 17 years of historical data, and Value Line analysts’ commentaries. The report also contains stock price charts, quarterly sales, earnings, and dividend information. Publication Schedule: Each edition of the Survey covers around 130 stocks in seven to eight industries on a preset sequential schedule so that all 1700 stocks are analyzed once every 13 weeks or each quarter. All editions are numbered 1-13 within each quarter. For example, in 1980, reports for Chrysler appear in edition 1 of each quarter on the following dates: January 4, 1980 – page 132 April 4, 1980 – page 133 July 4, 1980 – page 133 October 1, 1980 – page 133 Reports for Coca-Cola were published in edition 10 of each quarter on: March 7, 1980 – page 1514 June 6, 1980 – page 1518 Sept. 5, 1980 – page 1517 Dec. 5, 1980 – page 1548 Any significant news affecting a stock between quarters is covered in the supplementary reports that appear at the end of part 3, Ratings & Reports. File format: Digitized files within this dataset are in PDF format and are arranged by publication date within each compressed annual folder. How to Consult the Value Line Investment Survey: To find reports on a particular stock, consult the alphabetical listing of stocks in the Summary & Index part of the relevant weekly edition. Look for the page number just to the left of the company name and then use the table below to identify the edition where that page number appears. All editions within a given quarter are numbered 1-13 and follow equally sized page ranges for stock reports. The table provides page ranges for stock reports within editions 1-13 of 1980 Q1. It can be used to identify edition and page numbers for any quarter within a given year. Ratings & Reports Edition Pub. Date Pages 1 04-Jan-80 100-242 2 11-Jan-80 250-392 3 18-Jan-80 400-542 4 25-Jan-80 550-692 5 01-Feb-80 700-842 6 08-Feb-80 850-992 7 15-Feb-80 1000-1142 8 22-Feb-80 1150-1292 9 29-Feb-80 1300-1442 10 07-Mar-80 1450-1592 11 14-Mar-80 1600-1742 12 21-Mar-80 1750-1908 13 28-Mar-80 2000-2142 Another way to navigate to the Ratings & Reports part of an edition would be to look around page 50 within the PDF document. Note that the page numbers of the PDF will not match those within the publication.

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.

Can we predict stock market using machine learning? (WY Stock Forecast)

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

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.

Data Analytics in Financial Market Outlook

The global data analytics in financial market size was valued at approximately USD 10.5 billion in 2023 and is projected to reach around USD 34.8 billion by 2032, growing at a robust CAGR of 14.4% during the forecast period. This remarkable growth is driven by the increasing adoption of advanced analytics technologies, the need for real-time data-driven decision-making, and the rising incidence of financial fraud.

One of the primary growth factors for the data analytics in the financial market is the burgeoning volume of data generated from diverse sources such as transactions, social media, and online banking. Financial institutions are increasingly leveraging data analytics to process and analyze this vast amount of data to gain actionable insights. Additionally, technological advancements in artificial intelligence (AI) and machine learning (ML) are significantly enhancing the capabilities of data analytics tools, enabling more accurate predictions and efficient risk management.

Another driving factor is the heightened focus on regulatory compliance and security management. In the wake of stringent regulations imposed by financial authorities globally, organizations are compelled to adopt robust analytics solutions to ensure compliance and mitigate risks. Moreover, with the growing threat of cyber-attacks and financial fraud, there is a heightened demand for sophisticated analytics tools capable of detecting and preventing fraudulent activities in real-time.

Furthermore, the increasing emphasis on customer-centric strategies in the financial sector is fueling the adoption of data analytics. Financial institutions are utilizing analytics to understand customer behavior, preferences, and needs more accurately. This enables them to offer personalized services, improve customer satisfaction, and drive revenue growth. The integration of advanced analytics in customer management processes helps in enhancing customer engagement and loyalty, which is crucial in the competitive financial landscape.

Regionally, North America has been the dominant player in the data analytics in financial market, owing to the presence of major market players, technological advancements, and a high adoption rate of analytics solutions. However, the Asia Pacific region is anticipated to witness the highest growth during the forecast period, driven by the rapid digitalization of financial services, increasing investments in analytics technologies, and the growing focus on enhancing customer experience in emerging economies like China and India.

Component Analysis

In the data analytics in financial market, the components segment is divided into software and services. The software segment encompasses various analytics tools and platforms designed to process and analyze financial data. This segment holds a significant share in the market owing to the continuous advancements in software capabilities and the growing need for real-time analytics. Financial institutions are increasingly investing in sophisticated software solutions to enhance their data processing and analytical capabilities. The software segment is also being propelled by the integration of AI and ML technologies, which offer enhanced predictive analytics and automation features.

On the other hand, the services segment includes consulting, implementation, and maintenance services provided by vendors to help financial institutions effectively deploy and manage analytics solutions. With the rising complexity of financial data and analytics tools, the demand for professional services is on the rise. Organizations are seeking expert guidance to seamlessly integrate analytics solutions into their existing systems and optimize their use. The services segment is expected to grow significantly as more institutions recognize the value of professional support in maximizing the benefits of their analytics investments.

The software segment is further categorized into various types of analytics tools such as descriptive analytics, predictive analytics, and prescriptive analytics. Descriptive analytics tools are used to summarize historical data to identify patterns and trends. Predictive analytics tools leverage historical data to forecast future outcomes, which is crucial for risk management and fraud detection. Prescriptive analytics tools provide actionable recommendations based on predictive analysis, aiding in decision-making processes. The growing need for advanced predictive and prescriptive analytics is driving the demand for specialized software solut

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 214 companies listed on the Panama Stock Exchange (XPTY) in Panama. 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 Panama:

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.

‍

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

Panamanian Stock Exchange Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Panamanian Stock Exchange (Bolsa de Valores de Panamá). This index provides an overview of the overall market performance in Panama.

Panamanian Stock Exchange Foreign Company Index: The index that tracks the performance of foreign companies listed on the Panamanian Stock Exchange. This index reflects the performance of international companies operating in Panama.

Company A: A prominent Panamanian company with diversified operations across various sectors, such as shipping, logistics, or finance. This company's stock is widely traded on the Panamanian Stock Exchange.

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

Company C: A major player in the Panamanian energy or real estate sector, involved in the production and distribution of related products. This company's stock is listed and actively traded on the Panamanian Stock Exchange.

‍

If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Panama, 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.

‍

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 Panama ?

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 Panama?

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 Panama 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, direc...

Estonia: Stock market return, percent: The latest value from 2021 is 43.16 percent, an increase from -3.07 percent in 2020. In comparison, the world average is 32.21 percent, based on data from 87 countries. Historically, the average for Estonia from 1997 to 2021 is 18.77 percent. The minimum value, -41.38 percent, was reached in 1998 while the maximum of 173.71 percent was recorded in 1997.