In 2025, stock markets in the United States accounted for roughly ** percent of world stocks. The next largest country by stock market share was China, followed by the European Union as a whole. 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.

This statistic shows the largest global stock exchanges globally as of March 2025, ranked by the value of electronic order book share trading. In that time, the NYSE Stock Market was the largest stock exchange worldwide, with the value of EOB shares traded amounting to *** trillion U.S. dollars. Stock exchanges — additional information Stock exchanges are an important part of the free market economic system and are the most important component of the stock market. A stock exchange provides the setting in which stockbrokers, sellers, buyers, and traders can be brought together to take part in the sale of shares, bonds, derivatives and other securities. The core function of a stock exchange is to enable the fair and orderly trading, as well as the provision of price information, of any securities being traded on that exchange. Originally the exchanges were physical places (in some world locations the goods are still traded over-the-counter) but with time, they took the shape of an electronic platform. In order that company shares may be bought, traded and sold on a stock exchange, the company is required to have undergone an initial public offering process (IPO) on that particular exchange. The initial public offering of Alibaba Group Holding, a Chinese company operating in the e-commerce sector, on the New York Stock Exchange in September 2014, was the largest listing in the United States since 1996. The IPO of Alibaba Group Holding raised approximately ***** billion U.S. dollars.

The New York Stock Exchange (NYSE) is the largest stock exchange in the world, with an equity market capitalization of almost ** trillion U.S. dollars as of November 2025. The following largest three exchanges were the NASDAQ, PINK Exchange, and the Frankfurt Exchange. What is a stock exchange? A stock exchange is a marketplace where stockbrokers, traders, buyers, and sellers can trade in equities products. The largest exchanges have thousands of listed companies. These companies sell shares of their business, giving the general public the opportunity to invest in them. The oldest stock exchange worldwide is the Frankfurt Stock Exchange, founded in the late sixteenth century. Other functions of a stock exchange Since these are publicly traded companies, every firm listed on a stock exchange has had an initial public offering (IPO). The largest IPOs can raise billions of dollars in equity for the firm involved. Related to stock exchanges are derivatives exchanges, where stock options, futures contracts, and other derivatives can be traded.

The average for 2022 based on 74 countries was 34.95 percent. The highest value was in Hong Kong: 794.22 percent and the lowest value was in Azerbaijan: 0 percent. The indicator is available from 1975 to 2022. Below is a chart for all countries where data are available.

The average for 2022 based on 75 countries was 1225.97 billion U.S. dollars. The highest value was in the USA: 40297.98 billion U.S. dollars and the lowest value was in Bermuda: 0.21 billion U.S. dollars. The indicator is available from 1975 to 2024. Below is a chart for all countries where data are available.

Stock Exchanges Market Outlook

The global stock exchanges market size is projected to grow from USD 85 billion in 2023 to USD 130 billion by 2032, reflecting a compound annual growth rate (CAGR) of 4.8%. This steady growth is underpinned by a multitude of factors, including advancements in trading technology, the increasing complexity of financial instruments, and the rising participation of retail and institutional investors in global financial markets. The proliferation of electronic trading platforms, alongside traditional stock exchanges, is also contributing significantly to the growth of this market, providing enhanced accessibility, transparency, and efficiency in trading operations worldwide.

A key growth factor driving the expansion of the stock exchanges market is the ongoing digital transformation across the financial sector. With the advent of sophisticated trading technologies such as algorithmic trading and high-frequency trading, stock exchanges are increasingly adopting cutting-edge IT infrastructures to handle large volumes of trade data with superior accuracy and speed. Furthermore, the development of blockchain technology is poised to revolutionize clearing and settlement processes, reducing costs and the time taken for transaction finalization. This technological evolution is not only enhancing the operational efficiency of stock exchanges but also broadening the scope for innovative financial products, thereby attracting a wider array of market participants.

Another significant driver is the globalization of financial markets, which has led to a convergence in trading practices and regulations. As cross-border investments surge, stock exchanges are compelled to offer diverse products and services to cater to a global clientele. This necessitates continuous improvements in trading platforms and regulatory frameworks to manage the complexities associated with international investments. Additionally, increasing wealth in emerging economies is spurring investment activities, thereby boosting the demand for reliable and efficient stock exchanges. These dynamics are fueling the growth of the market by fostering an environment conducive to investment and financial inclusivity.

The increasing interest from retail investors is also a major factor contributing to the growth of the stock exchanges market. The advent of user-friendly trading apps and platforms has democratized stock trading, enabling retail investors to participate actively in financial markets. Enhanced financial literacy and the widespread availability of information have empowered individual investors to make informed decisions, leading to an upsurge in market participation. This rise in retail trading volume is prompting stock exchanges to innovate and expand their offerings to accommodate this burgeoning segment, thus driving market growth.

Regionally, North America continues to dominate the stock exchanges market, driven by the presence of major exchanges such as the New York Stock Exchange (NYSE) and NASDAQ. However, the Asia Pacific region is emerging as a formidable player due to rapid economic growth, regulatory reforms, and technological advancements in countries like China, India, and Japan. The region is witnessing a significant influx of foreign capital, bolstering trading activities and propelling market expansion. Europe also holds a substantial share, supported by its mature financial markets and strong institutional investor base. Meanwhile, Latin America and the Middle East & Africa are exhibiting potential for growth, albeit at a relatively slower pace, as they develop their financial infrastructures and regulatory environments.

Type Analysis

The stock exchanges market is bifurcated into traditional stock exchanges and electronic trading platforms, each serving distinct roles in the financial ecosystem. Traditional stock exchanges have long been the cornerstone of financial markets, operating as centralized venues where securities are bought and sold. These exchanges, such as the NYSE and London Stock Exchange, are characterized by their stringent regulatory frameworks and structured trading environments, which instill confidence and trust among market participants. Despite the technological advancements, traditional exchanges continue to hold a significant share of the market due to their established reputations and the comprehensive services they offer, including listing, trading, and settlement.

On the other hand, electronic trading platforms have gained momentum in recent years, driven by the demand for greater efficiency and flexibility in trading. These platf

Global Stock Market Financial Dataset (from TradingView)

This collection provides a comprehensive snapshot of over 11,800 publicly traded companies worldwide. It combines multiple financial statements and performance indicators extracted from TradingView to support data analysis, stock screening, and financial modeling.

Files Overview

1.tradingview_all_stocks.csv Contains general stock information and market statistics.

Columns: ticker, name, close, change, change_abs, volume, market_cap_basic, price_earnings_ttm, sector, industry Size: 11,806 rows × 10 columns Description: Lists all active stocks with latest prices, PE ratios, and sector/industry classifications.

2.tradingview_performance.csv Tracks short- and long-term stock performance.

Columns (sample): ticker, name, close, Perf.W, Perf.1M, Perf.3M, Perf.6M, Perf.YTD, Perf.1Y, Perf.5Y, etc. Size: 11,814 rows × 17 columns Description: Shows relative percentage performance across multiple timeframes.

3.balance_sheet.csv Summarizes financial position and liquidity metrics.

Columns: total_assets_fq, cash_n_short_term_invest_fq, total_liabilities_fq, total_debt_fq, net_debt_fq, total_equity_fq, current_ratio_fq Size: 11,821 rows × 12 columns Description: Includes key balance sheet values, enabling leverage and liquidity analysis.

4.cashflow.csv Focuses on company cash generation and sustainability.

Columns: free_cash_flow_ttm Size: 11,821 rows × 4 columns Description: Provides trailing twelve-month free cash flow figures for profitability evaluation.

5.dividends.csv Details dividend-related statistics.

Columns: dividends_yield, dividend_payout_ratio_ttm Size: 11,823 rows × 5 columns Description: Useful for income-focused investors; includes dividend yields and payout ratios.

6.income_statement.csv Presents company earnings metrics.

Columns: total_revenue_ttm, gross_profit_ttm, net_income_ttm, ebitda_ttm Size: 11,821 rows × 7 columns Description: Captures profitability over the last 12 months for revenue and margin analysis.

7.profitability.csv Shows margin-based performance indicators.

Columns: gross_margin_ttm, operating_margin_ttm, net_margin_ttm, ebitda_margin_ttm Size: 11,823 rows × 7 columns Description: Enables efficiency and operational performance comparisons across companies.

Use Cases 1. Stock market and financial analysis 2. Portfolio optimization and factor modeling 3. Machine learning for price prediction 4. Company benchmarking and screening 5. Academic or educational use in finance courses

Data Source & Notes 1. All data was aggregated from TradingView using public financial data endpoints. 2. Missing values may occur for companies that do not report certain metrics. 3. All monetary figures are based on the latest available TTM (Trailing Twelve Months) or FQ (Fiscal Quarter) data at the time of extraction.

The "Stock Market Dataset for AI-Driven Prediction and Trading Strategy Optimization" is designed to simulate real-world stock market data for training and evaluating machine learning models. This dataset includes a combination of technical indicators, market metrics, sentiment scores, and macroeconomic factors, providing a comprehensive foundation for developing and testing AI models for stock price prediction and trading strategy optimization.

Key Features Market Metrics:

Open, High, Low, Close Prices: Daily stock price movement. Volume: Represents the trading activity during the day. Technical Indicators:

RSI (Relative Strength Index): A momentum oscillator to measure the speed and change of price movements. MACD (Moving Average Convergence Divergence): An indicator to reveal changes in strength, direction, momentum, and duration of a trend. Bollinger Bands: Upper and lower bands around a stock price to measure volatility. Sentiment Analysis:

Sentiment Score: Simulated sentiment derived from financial news and social media, ranging from -1 (negative) to 1 (positive). Macroeconomic Factors:

GDP Growth: Indicates the overall health and growth of the economy. Inflation Rate: Reflects changes in purchasing power and economic stability. Target Variable:

Buy/Sell Signal: Binary classification (1 = Buy, 0 = Sell) based on price movement thresholds, simulating actionable trading decisions. Use Cases AI Model Training: Ideal for building stock prediction models using LSTM, Gradient Boosting, Random Forest, etc. Trading Strategy Optimization: Enables testing of trading algorithms and strategies in a simulated environment. Sentiment Analysis Research: Useful for understanding how sentiment influences stock movements. Feature Engineering and Selection: Provides a diverse set of features for experimentation with advanced techniques like PCA and LDA. Dataset Highlights Synthetic Yet Realistic: Carefully designed to mimic real-world financial data trends and relationships. Comprehensive Coverage: Includes key indicators and metrics used by traders and analysts. Scalable: Suitable for use in both small-scale academic projects and larger AI-driven trading platforms. Accessible for All Levels: The intuitive structure ensures that even beginners can utilize this dataset for financial machine learning applications. File Format The dataset is provided in CSV format, where:

Rows represent individual trading days. Columns represent features (technical indicators, market metrics, etc.) and the target variable. Acknowledgments This dataset is synthetically generated and is intended for research and educational purposes. It is not based on real market data and should not be used for actual trading.

About:

This dataset encompasses the historical data of major stock indices from around the world, sourced directly from Yahoo Finance. With data reaching back to the early 1920s (where available), it serves as an invaluable repository for academic researchers, financial analysts, and market enthusiasts. Users can delve into trends across decades, evaluate historical market behaviors, or even design and validate predictive financial models.

Photo by Tötös Ádám on Unsplash

Info on CSVs:

1. all_indices_data.csv:

   • Description: A consolidated dataset merging all the stock indices from Yahoo Finance.
   • Columns:
     • date: The date of the data point (formatted as YYYY-MM-DD).
     • open: The opening value of the index on that date.
     • high: The highest value of the index during the trading session.
     • low: The lowest value of the index during the trading session.
     • close: The closing value of the index.
     • volume: The trading volume of the index on that date.
     • ticker: The ticker symbol of the stock index.

2. individual_indices_data/[SYMBOL]_data.csv:

   • Description: Individual datasets for each stock index, where [SYMBOL] denotes the ticker symbol of the respective stock index. Each dataset is curated from Yahoo Finance's historical data archives.
   • Columns:
     • date: The date of the data point (formatted as YYYY-MM-DD).
     • open: The opening value of the index on that date.
     • high: The highest value of the index during the trading session.
     • low: The lowest value of the index during the trading session.
     • close: The closing value of the index.
     • volume: The trading volume of the index on that date.

Graph and download economic data for Stock Market Total Value Traded to GDP for United States (DDDM02USA156NWDB) from 1975 to 2019 about market cap, stock market, trade, GDP, and USA.

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.
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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 clearing minimize r

Context:

The provided dataset is extracted from yahoo finance using pandas and yahoo finance library in python. This deals with stock market index of the world best economies. The code generated data from Jan 01, 2003 to Jun 30, 2023 that’s more than 20 years. There are 18 CSV files, dataset is generated for 16 different stock market indices comprising of 7 different countries. Below is the list of countries along with number of indices extracted through yahoo finance library, while two CSV files deals with annualized return and compound annual growth rate (CAGR) has been computed from the extracted data.

Number of Countries & Index:

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F90ce8a986761636e3edbb49464b304d8%2FNumber%20of%20Index.JPG?generation=1688490342207096&alt=media" alt="">

Content:

Unit of analysis: Stock Market Index Analysis

This dataset is useful for research purposes, particularly for conducting comparative analyses involving capital market performance and could be used along with other economic indicators.

There are 18 distinct CSV files associated with this dataset. First 16 CSV files deals with number of indices and last two CSV file deals with annualized return of each year and CAGR of each index. If data in any column is blank, it portrays that index was launch in later years, for instance: Bse500 (India), this index launch in 2007, so earlier values are blank, similarly China_Top300 index launch in year 2021 so early fields are blank too.

The extraction process involves applying different criteria, like in 16 CSV files all columns are included, Adj Close is used to calculate annualized return. The algorithm extracts data based on index name (code given by the yahoo finance) according start and end date.

Annualized return and CAGR has been calculated and illustrated in below image along with machine readable file (CSV) attached to that.

To extract the data provided in the attachment, various criteria were applied:

1. Content Filtering: The data was filtered based on several attributes, including the index name, start and end date. This filtering process ensured that only relevant data meeting the specified criteria.

2. Collaborative Filtering: Another filtering technique used was collaborative filtering using yahoo finance, which relies on index similarity. This approach involves finding indices that are similar to other index or extended dataset scope to other countries or economies. By leveraging this method, the algorithm identifies and extracts data based on similarities between indices.

In the last two CSV files, one belongs to annualized return, that was calculated based on the Adj close column and new DataFrame created to store its outcome. Below is the image of annualized returns of all index (if unreadable, machine-readable or CSV format is attached with the dataset).

Annualized Return:

As far as annualised rate of return is concerned, most of the time India stock market indices leading, followed by USA, Canada and Japan stock market indices.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F37645bd90623ea79f3708a958013c098%2FAnnualized%20Return.JPG?generation=1688525901452892&alt=media" alt="">

Compound Annual Growth Rate (CAGR):

The best performing index based on compound growth is Sensex (India) that comprises of top 30 companies is 15.60%, followed by Nifty500 (India) that is 11.34% and Nasdaq (USA) all is 10.60%.

The worst performing index is China top300, however this is launch in 2021 (post pandemic), so would not possible to examine at that stage (due to less data availability). Furthermore, UK and Russia indices are also top 5 in the worst order.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F58ae33f60a8800749f802b46ec1e07e7%2FCAGR.JPG?generation=1688490409606631&alt=media" alt="">

Geography: Stock Market Index of the World Top Economies

Time period: Jan 01, 2003 – June 30, 2023

Variables: Stock Market Index Title, Open, High, Low, Close, Adj Close, Volume, Year, Month, Day, Yearly_Return and CAGR

File Type: CSV file

Inspiration:

• Time series prediction model
• Investment opportunities in world best economies
• Comparative Analysis of past data with other stock market indices or other indices

Disclaimer:

This is not a financial advice; due diligence is required in each investment decision.

The average for 2021 based on 87 countries was 32.21 percent. The highest value was in Venezuela: 991.39 percent and the lowest value was in Botswana: -6.38 percent. The indicator is available from 1984 to 2021. Below is a chart for all countries where data are available.

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.

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

United States US: Stocks Traded: Total Value data was reported at 39,785.881 USD bn in 2017. This records a decrease from the previous number of 42,071.330 USD bn for 2016. United States US: Stocks Traded: Total Value data is updated yearly, averaging 17,934.293 USD bn from Dec 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 47,245.496 USD bn in 2008 and a record low of 1,108.421 USD bn in 1984. United States US: Stocks Traded: Total Value data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

The value of global domestic equity market increased from ***** trillion U.S. dollars in 2013 to ****** trillion U.S. dollars in 2024. The United States was by far the leading country with the largest share of total world stocks as of 2024. Global market capitalization in different regions The market capitalization of domestic companies listed varied across different regions of the world. As of Decmber 2024, the Americas region had the largest domestic equity market, totaling ** trillion U.S. dollars. This region is home to the NYSE and Nasdaq, which are the two largest stock exchange operators in the world. The market capitalization of these two exchanges alone exceeded ** billion U.S. dollars as of January 2025, larger than the total market capitalization in the Asia-Pacific, and in the EMEA regions in the same period. Largest Stock Exchanges in Latin America As of December 2024, the B3 (Brasil Bolsa Balcao) was the biggest stock exchange in Latin America in terms of market capitalization and the second-largest in terms of number of listed companies. Following the B3 were the Mexican Stock Exchange and the Santiago Stock Exchange in Chile. The most valuable company in Latin America is listed on the Mexican Stock Exchange: Fomento Económico Mexicano, a multinational beverage and retail company headquartered in Monterrey, had a market cap of *** billion U.S. dollars as of March 2025.

Graph and download economic data for Rest of the World; Trade Receivables; Asset, Market Value Levels (BOGZ1LM263070005Q) from Q4 1945 to Q2 2025 about receivables, market value, trade, and assets.

Graph and download economic data for Number of Listed Companies for United States (DDOM01USA644NWDB) from 1975 to 2019 about companies, stock market, and USA.

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.