Euro Area's main stock market index, the EU50, rose to 5391 points on September 12, 2025, gaining 0.08% from the previous session. Over the past month, the index has climbed 0.05% and is up 11.29% 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 September of 2025.

End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.

Prices for Euro Area Stock Market Index (EU350) including live quotes, historical charts and news. Euro Area Stock Market Index (EU350) was last updated by Trading Economics this September 14 of 2025.

France's main stock market index, the FR40, rose to 7825 points on September 12, 2025, gaining 0.02% from the previous session. Over the past month, the index has climbed 0.26% and is up 4.82% 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 September of 2025.

P-values of two samples Kolmogorov-Smirnov test comparing real data distribution with q normal distribution for individual stocks and the whole WIG 30 index (independent fit of left and right tail is performed).

In 2022, the leading stock exchange in Europe in terms of IPOs size was the Frankfurt Stock Exchange (Deutsche Börse), with a value of 9.4 billion euros. The following two largest exchanges were the Borsa Italiana in Milan (part of Euronext Group), and the London Stock Exchange, with around 1.4 billion and 1.1 billion euros respectively.

The data come from best fit results shown in Table 1. The top part of the table is related to intraday data while bottom part contains interday data. The averaged relative asymmetry ratio and is taken respectively over all intraday time-lags (from 1 min to 60 min) and interday time-lags (from 1 day to 4 days) for individual stocks and the whole WIG 30 index.

Germany's main stock market index, the DE40, fell to 23698 points on September 12, 2025, losing 0.02% from the previous session. Over the past month, the index has declined 2.02%, though it remains 26.73% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Germany. Germany Stock Market Index (DE40) - values, historical data, forecasts and news - updated on September 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 ** percent of their value compared to January *, 2020. However, Asian markets and the NASDAQ Composite Index only shed around ** to ** 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 ** percent higher than in January 2020, while most other markets were only between ** and ** 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.

Skewness of price returns for chosen stokcs from WIG 30 stock index.

The data set contains material to replicate: Beck K, Stanek P (2019) Globalization or regionalization of stock markets? The case of Central and Eastern European Countries. Eastern European Economics, 57(4), 317-330. doi: https://doi.org/10.1080/00128775.2019.1610895 The data comprises stock market returns time series at weekly frequency between January 2000 and December 2018 on 44 stock price indices grouped into 11 sets corresponding to (1) East Asian and Australian developed markets, (2) “Chinese” markets (including Taiwan and Hong Kong), (3) “core” euro area, (4) “peripheral” euro area, (5) developed European markets outside the euro area, (6) V-4 countries, (7) “frontier” European markets (Russia, Turkey, Ukraine), (8) Baltic countries, (9) Latin American markets, (10) North American markets and (11) emerging South-East Asian countries. Data were retrieved from stooq.com and in case of some missing points, for example, due to Chinese New Year celebrations, log-linear interpolation was applied.

Polish currency (PLN—złoty) has been added for comparison. Shown are also results of independent fit of Tsallis parameter q± to the right (positive returns) and left (negative returns) tail of probability distribution for diversified time-lags.

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.

Euro Stoxx 50: Back on Track?

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

Smart Insider’s Global Share Buyback Database offers invaluable insights to investors on stock market data. We provide detailed, up-to-date share buyback data covering over 55,000 companies globally and over 8,000+ in Europe & UK, that’s every company that reports Buybacks through regulatory processes.

Our Share buyback data includes detailed information on all major buyback transactions including source announcements and derived analysis fields. Our platform adds a visual representation of the data, allowing investors to quickly identify patterns and make decisions based on their findings.

Get detailed share buyback insights with Smart Insider and stay ahead of the curve with accurate, historical buyback insight that helps you make better investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as CSV, XML or XLSX via SFTP, API or Snowflake.

Sample dataset for Desktop Service has been provided with limited fields. Upon request, we can provide a detailed Quant sample.

Tags: Equity Market Data, Stock Market Data, Corporate Actions Data, Corporate Buyback Data, Company Financial Data, Insider Trading Data

Comprehensive dataset of 23 companies listed on Berlin Stock Exchange, including detailed financial information, market data, and corporate filings. This dataset provides real-time updates on trading metrics, company profiles, financial statements, regulatory filings, and market performance indicators. Updated every 30 minutes, it covers key data points such as market capitalization, trading volume, stock prices, company fundamentals, and regulatory compliance information for all listed securities on Berlin Stock Exchange.

Comprehensive dataset of 1543 companies listed on London Stock Exchange, including detailed financial information, market data, and corporate filings. This dataset provides real-time updates on trading metrics, company profiles, financial statements, regulatory filings, and market performance indicators. Updated every 30 minutes, it covers key data points such as market capitalization, trading volume, stock prices, company fundamentals, and regulatory compliance information for all listed securities on London Stock Exchange.

This paper studies the heterogeneous effects of exchange rate and stock market on carbon emission allowance price in four emissions trading scheme pilots in China. We employ a panel quantile regression model, which can describe both individual and distributional heterogeneity. The empirical results illustrate that the effects of explanatory variables on carbon emission allowance price is heterogeneous along the whole quantiles. Specifically, exchange rate has a negative effect on carbon emission allowance price at lower quantiles, while becomes a positive effect at higher quantiles. In addition, a negative effect exists between domestic stock market and carbon emission allowance price, and the intensity decreasing along with the increase of quantile. By contrast, an increasing positive effect is discovered between European stock market and domestic carbon emission allowance prices. Finally, heterogeneous effects on carbon emission allowance price can also be proved in European Union Emission Trading Scheme (EU-ETS).

The dataset used in this paper is a collection of stock prices of eleven companies of different stock exchanges of frontier markets.

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Foreign Exchange Market Size 2025-2029

The foreign exchange market size is forecast to increase by USD 582 billion, at a CAGR of 10.6% between 2024 and 2029.

Major Market Trends & Insights

Europe dominated the market and accounted for a 47% growth during the forecast period.
By the Type - Reporting dealers segment was valued at USD 278.60 billion in 2023
By the Trade Finance Instruments - Currency swaps segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 118.14 billion
Market Future Opportunities: USD 582.00 billion 
CAGR : 10.6%
Europe: Largest market in 2023

Market Summary

The Foreign Exchange (Forex) market, a global financial platform for exchanging one currency for another, is a dynamic and continuously evolving ecosystem. According to the Bank for International Settlements, daily trading volumes reached approximately USD6 trillion in April 2020, representing a significant portion of the world's financial transactions. This market's importance is underscored by its role in facilitating international trade, investment, and tourism. The Forex market's decentralized nature allows for 24/7 trading opportunities, making it an attractive proposition for businesses and investors seeking to manage currency risk or capitalize on price fluctuations. Despite the market's complexity, advanced technologies, such as machine learning and artificial intelligence, are increasingly being adopted to enhance trading strategies and improve risk management.
One significant trend is the increasing use of money transfer agencies, venture capital investments, and mutual funds in foreign exchange transactions. These tools enable real-time analysis of market trends and help forecast exchange rates, providing valuable insights for businesses operating in multiple currencies. The Forex market's influence extends beyond traditional financial sectors, with applications in various industries, including tourism, import/export, and international business. As businesses expand their global footprint and economies continue to interconnect, the role and significance of the Forex market are set to grow further.

What will be the Size of the Foreign Exchange Market during the forecast period?

Explore market size, adoption trends, and growth potential for foreign exchange market Request Free Sample

The market, a vital component of the global financial system, operates without fail, facilitating the conversion of one currency into another. According to recent data, approximately 6% of daily global trading volume is attributed to this market. Looking ahead, growth is projected to reach over 5% annually. Consider the following comparison: the average daily trading volume in the forex market exceeds that of the New York Stock Exchange by a significant margin. In 2020, the former recorded around USD 6 trillion, while the latter saw approximately USD 136 billion. This disparity underscores the market's immense scale and influence.
Moreover, the forex market's liquidity depth enables efficient price discovery, minimizing transaction security concerns and market impact costs. Automated trading bots and order book depth analysis are essential tools for market participants, allowing for effective backtesting strategies and fraud detection systems. Leverage ratios, transaction fees, and margin requirements are essential factors influencing market accessibility and profitability. High-frequency trading and the presence of liquidity providers contribute to market efficiency and statistical arbitrage opportunities. Regulatory compliance and brokerage services further ensure a secure trading environment. Despite payment processing fees and order flow imbalance, risk tolerance levels remain a crucial consideration for participants.

How is this Foreign Exchange Industry segmented?

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

Type

  Reporting dealers
  Financial institutions
  Non-financial customers


Trade Finance Instruments

  Currency swaps
  Outright forward and FX swaps
  FX options


Trading Platforms

  Electronic Trading
  Over-the-Counter (OTC)
  Mobile Trading


Geography

  North America

    US
    Canada


  Europe

    Germany
    Switzerland
    UK


  Middle East and Africa

    UAE


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Type Insights

The reporting dealers segment is estimated to witness significant growth during the forecast period.

The market is a dynamic and intricate financial ecosystem where businesses and investors transact in various currencies to manage internationa

The data series sample cover 2,101 European equity funds, with monthly data for the period January 2001 to October 2016, as provided by Morningstar. We use all funds sorted as Euro/Eurozone equity funds in Morningstar, traded in euros. Specifically, we include the following categories: Europe ex-UK Large-Cap Equity; Europe Equity-Currency Hedged; Europe ex-UK Small/Mid-Cap Equity; Europe Flex-Cap Equity; Europe Large-Cap Blend Equity; Europe Large-Cap Growth Equity; Europe Large-Cap Value Equity; Europe Mid-Cap Equity; Europe Small-Cap Equity; Eurozone Flex-Cap Equity; Eurozone Large-Cap Equity; Eurozone Mid-Cap Equity and Eurozone Small-Cap Equity. We omit those funds that hold exclusively domestic stocks, in order to avoid distorting our results on grounds of risk exposures that involve specific areas. The dataset comprises the following series:

1. Summary statistics for 2,101 Euro/Eurozone equity funds.
2. Summary statistics for 20 size portfolios, formed by 2,101 Euro/Eurozone equity funds.
3. DEA estimates for 20 size portfolios, formed by 2,101 Euro/Eurozone equity funds.
4. Monthly returns for the three classic factors of Fama and French and for the DEA factor.
5. Monthly returns for 20 size portfolios, formed by 2,101 Euro/Eurozone equity funds.