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.

The main stock market index of United States, the US500, rose to 6818 points on December 2, 2025, gaining 0.08% from the previous session. Over the past month, the index has declined 0.50%, though it remains 12.70% higher than a year ago, 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 December of 2025.

Graph and download economic data for Index of Common Stock Prices, New York Stock Exchange for United States (M11007USM322NNBR) from Jan 1902 to May 1923 about New York, stock market, indexes, and USA.

Between March 4 and March 11, 2020, the S&P 500 index declined by ** percent, descending into a bear market. On March 12, 2020, the S&P 500 plunged *** percent, its steepest one-day fall since 1987. The index began to recover at the start of April and reached a peak in December 2021. As of December 29, 2024, the value of the S&P 500 stood at ******** points. Coronavirus sparks stock market chaos Stock markets plunged in the wake of the COVID-19 pandemic, with investors fearing its spread would destroy economic growth. Buoyed by figures that suggested cases were leveling off in China, investors were initially optimistic about the virus being contained. However, confidence in the market started to subside as the number of cases increased worldwide. Investors were deterred from buying stocks, and this was reflected in the markets – the values of the Dow Jones Industrial Average and the Nasdaq Composite also dived during the height of the crisis. What is a bear market? A bear market occurs when the value of a stock market suffers a prolonged decline of more than 20 percent over a period of at least 2 months. The COVID-19 pandemic caused severe concern and sent stock markets on a steep downward spiral. The S&P 500 achieved a record closing high of ***** on February 19, 2020. However, just over 3 weeks later, the market closed on *****, which represented a decline of around ** percent in only 16 sessions.

Israel's main stock market index, the TA-125, rose to 3538 points on December 2, 2025, gaining 1.75% from the previous session. Over the past month, the index has climbed 4.40% and is up 50.06% 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 December of 2025.

France's main stock market index, the FR40, rose to 8121 points on December 2, 2025, gaining 0.29% from the previous session. Over the past month, the index has climbed 0.13% and is up 11.93% 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 December of 2025.

Graph and download economic data for Stock Market Capitalization to GDP for United States (DDDM01USA156NWDB) from 1975 to 2020 about market cap, stock market, capital, GDP, and USA.

Stock market index in Mexico, September, 2025 The most recent value is 139.61 points as of September 2025, an increase compared to the previous value of 132.58 points. Historically, the average for Mexico from January 1970 to September 2025 is 36.41 points. The minimum of 0 points was recorded in January 1970, while the maximum of 139.61 points was reached in September 2025. | TheGlobalEconomy.com

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

Spain's main stock market index, the ES35, rose to 16493 points on December 2, 2025, gaining 0.63% from the previous session. Over the past month, the index has climbed 2.84% and is up 38.90% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Spain. Spain Stock Market Index (ES35) - values, historical data, forecasts and news - updated on December of 2025.

The US_Stock_Data.csv dataset offers a comprehensive view of the US stock market and related financial instruments, spanning from January 2, 2020, to February 2, 2024. This dataset includes 39 columns, covering a broad spectrum of financial data points such as prices and volumes of major stocks, indices, commodities, and cryptocurrencies. The data is presented in a structured CSV file format, making it easily accessible and usable for various financial analyses, market research, and predictive modeling. This dataset is ideal for anyone looking to gain insights into the trends and movements within the US financial markets during this period, including the impact of major global events.

Key Features and Data Structure

The dataset captures daily financial data across multiple assets, providing a well-rounded perspective of market dynamics. Key features include:

• Commodities: Prices and trading volumes for natural gas, crude oil, copper, platinum, silver, and gold.
• Cryptocurrencies: Prices and volumes for Bitcoin and Ethereum, including detailed 5-minute interval data for Bitcoin.
• Stock Market Indices: Data for major indices such as the S&P 500 and Nasdaq 100.
• Individual Stocks: Prices and volumes for major companies including Apple, Tesla, Microsoft, Google, Nvidia, Berkshire Hathaway, Netflix, Amazon, and Meta.

The dataset’s structure is designed for straightforward integration into various analytical tools and platforms. Each column is dedicated to a specific asset's daily price or volume, enabling users to perform a wide range of analyses, from simple trend observations to complex predictive models. The inclusion of intraday data for Bitcoin provides a detailed view of market movements.

Applications and Usability

This dataset is highly versatile and can be utilized for various financial research purposes:

• Market Analysis: Track the performance of key assets, compare volatility, and study correlations between different financial instruments.
• Risk Assessment: Analyze the impact of commodity price movements on related stock prices and evaluate market risks.
• Educational Use: Serve as a resource for teaching market trends, asset correlation, and the effects of global events on financial markets.

The dataset’s daily updates ensure that users have access to the most current data, which is crucial for real-time analysis and decision-making. Whether for academic research, market analysis, or financial modeling, the US_Stock_Data.csv dataset provides a valuable foundation for exploring the complexities of financial markets over the specified period.

Acknowledgements:

This dataset would not be possible without the contributions of Dhaval Patel, who initially curated the US stock market data spanning from 2020 to 2024. Full credit goes to Dhaval Patel for creating and maintaining the dataset. You can find the original dataset here: US Stock Market 2020 to 2024.

The "yahoo_finance_dataset(2018-2023)" dataset is a financial dataset containing daily stock market data for multiple assets such as equities, ETFs, and indexes. It spans from April 1, 2018 to March 31, 2023, and contains 1257 rows and 7 columns. The data was sourced from Yahoo Finance, and the purpose of the dataset is to provide researchers, analysts, and investors with a comprehensive dataset that they can use to analyze stock market trends, identify patterns, and develop investment strategies. The dataset can be used for various tasks, including stock price prediction, trend analysis, portfolio optimization, and risk management. The dataset is provided in XLSX format, which makes it easy to import into various data analysis tools, including Python, R, and Excel.

The dataset includes the following columns:

Date: The date on which the stock market data was recorded. Open: The opening price of the asset on the given date. High: The highest price of the asset on the given date. Low: The lowest price of the asset on the given date. Close*: The closing price of the asset on the given date. Note that this price does not take into account any after-hours trading that may have occurred after the market officially closed. Adj Close**: The adjusted closing price of the asset on the given date. This price takes into account any dividends, stock splits, or other corporate actions that may have occurred, which can affect the stock price. Volume: The total number of shares of the asset that were traded on the given date.

This table contains 25 series, with data for years 1956 - present (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Toronto Stock Exchange Statistics (25 items: Standard and Poor's/Toronto Stock Exchange Composite Index; high; Standard and Poor's/Toronto Stock Exchange Composite Index; close; Toronto Stock Exchange; oil and gas; closing quotations; Standard and Poor's/Toronto Stock Exchange Composite Index; low ...).

1) Data Introduction • The Twitter Stock Prices Dataset contains stock price data for Twitter from November 2013 to October 2022. This dataset is a time series dataset that provides daily stock trading information. • The key attributes include the stock's opening price (Open), highest price (High), lowest price (Low), closing price (Close), adjusted closing price (Adj Close), and volume (Volume).

2) Data Utilization (1) Characteristics of the Twitter Stock Prices Data • This dataset is a time series, offering daily stock price fluctuations and allows tracking of price changes over time. • It includes 7 main attributes related to stock trading, allowing for analysis of price movements (open, high, low, close) and volume, to better understand Twitter’s stock price dynamics. • This data helps analyze market trends, price volatility patterns, and price fluctuation analysis, providing insights into the dynamics of the stock market.

(2) Applications of the Twitter Stock Prices Data • Predictive Modeling: This dataset can be used to develop stock price prediction models, including predicting price increases/decreases or forecasting future stock prices using machine learning models. • Business Insights: Investment experts can use this dataset to evaluate Twitter’s stock performance, and it provides useful information for optimizing investment strategies in response to market changes. This dataset can be used for trend forecasting and investor analysis. • Trend Analysis: By analyzing stock upward/downward trends, this dataset can help evaluate the company's market performance and develop trend-based investment strategies.

India's main stock market index, the SENSEX, fell to 85138 points on December 2, 2025, losing 0.59% from the previous session. Over the past month, the index has climbed 1.38% and is up 5.31% 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 December of 2025.

Graph and download economic data for Financial Market: Share Prices for Italy (SPASTT01ITQ661N) from Q1 1957 to Q3 2025 about Italy and stock market.

📊 Adobe Stock Dataset (1986-2024)

This dataset contains historical stock data for Adobe Inc. (ticker symbol: ADBE) obtained from Yahoo Finance. The dataset spans from 1986 to 2024, offering a rich insight into Adobe’s stock performance over nearly four decades. The data provides essential information about Adobe's market behavior, which can be used for various analyses, such as trend analysis, forecasting, and financial modeling.

🧑‍💻 How the Data is Made

The data is sourced from Yahoo Finance, where stock prices are recorded for every trading day. It includes key market information like opening, closing, highest, and lowest prices of the stock on any given day, along with the trading volume and adjusted close prices.

• Opening Price: The first price of the stock traded during market hours.
• Closing Price: The last price at which the stock was traded during market hours.
• Adjusted Close: The closing price adjusted for dividends and stock splits to reflect a true value over time.
• High/Low Prices: The highest and lowest prices at which the stock traded throughout the day.
• Volume: The number of shares traded during the day.

The data is processed daily, and over the years, it has been aggregated to offer a long-term view of Adobe's stock performance.

📋 Column Descriptions

📅 Time Span of Data

• Start Date: 1986 (The year Adobe was first publicly listed on the stock market)
• End Date: 2024 (Latest available data)

💡 Key Insights from the Dataset

• Market Trends: Track the upward and downward trends in Adobe's stock value, identifying key periods of growth or decline.
• Volatility: Analyze the fluctuations in stock prices using the high and low values to understand Adobe’s stock market volatility.
• Volume Activity: Understand market sentiment and investor interest by examining trading volumes.
• Stock Performance: Assess Adobe’s performance over time using adjusted closing prices, which account for stock splits and dividends.

This dataset offers a detailed, long-term view of Adobe's stock and is a valuable resource for anyone interested in financial analysis, stock price prediction, or market behavior study.

📈 Whether you are a data scientist, financial analyst, or simply someone interested in stock market trends, this dataset will provide the necessary foundation for conducting deep and insightful analyses.

Monthly and long-term Ukraine Stock Market data: historical series and analyst forecasts curated by FocusEconomics.

The global capital exchange ecosystem market, valued at $1.06 trillion in 2025, is projected to experience robust growth, driven by increasing global trade, the rise of fintech innovations, and a growing preference for digital trading platforms. The market's Compound Annual Growth Rate (CAGR) of 5.80% from 2025 to 2033 signifies a consistently expanding market opportunity. Key segments, including the primary and secondary markets, contribute significantly to this growth, with the primary market fueled by Initial Public Offerings (IPOs) and other new listings, while the secondary market thrives on the continuous trading of existing securities. The diverse range of stock and bond types (common, preferred, growth, value, defensive stocks; government, corporate, municipal, mortgage bonds) caters to a broad spectrum of investor profiles and risk appetites. Technological advancements, including high-frequency trading algorithms and improved data analytics, are further enhancing market efficiency and liquidity. However, regulatory hurdles, geopolitical uncertainties, and cybersecurity threats remain as potential restraints on market growth. The strong presence of established exchanges like the New York Stock Exchange (NYSE), NASDAQ, and the London Stock Exchange, alongside emerging players in Asia and other regions, contributes to the market's competitive landscape. Regional growth will likely be influenced by economic development, regulatory frameworks, and investor confidence, with North America and Asia Pacific anticipated to maintain leading positions. The future of the capital exchange ecosystem hinges on adaptation and innovation. The increasing integration of blockchain technology and decentralized finance (DeFi) is expected to reshape trading infrastructure and potentially challenge traditional exchange models. Increased regulatory scrutiny globally will likely necessitate further transparency and improved risk management practices by exchanges. Furthermore, the growing prominence of Environmental, Social, and Governance (ESG) investing will influence investment strategies and, consequently, trading activity across various asset classes. The market's future success will depend on its ability to effectively manage risks, embrace technological innovation, and meet the evolving needs of a diverse and increasingly sophisticated investor base. Continued growth is anticipated, driven by both established and emerging markets. Recent developments include: In December 2023, Defiance ETFs, introduced the Defiance Israel Bond ETF (NYSE Arca: CHAI) to facilitate investors' access to the Israeli bond market. CHAI commenced trading on the New York Stock Exchange. The ETF, CHAI, mirrors the MCM (Migdal Capital Markets) BlueStar Israel Bond Index, enabling investors to tap into both Israel government and corporate bonds. This index specifically monitors the performance of bonds, denominated in USD and shekels, issued by either the Israeli government or Israeli corporations., In January 2024, the National Stock Exchange (NSE) saw a 22% rise in its investor base, increasing from 70 million to 85.4 million during the calendar year 2023. This growth highlights the increasing participation of retail investors in the stock market.. Key drivers for this market are: Automating all processes, Regulatory Landscape. Potential restraints include: Automating all processes, Regulatory Landscape. Notable trends are: Increasing Stock Exchanges Index affecting Capital Market Exchange Ecosystem.

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 clearing minimize r