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.

Euro Area's main stock market index, the EU50, rose to 5684 points on December 2, 2025, gaining 0.27% from the previous session. Over the past month, the index has climbed 0.09% and is up 16.52% 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 December of 2025.

The average for 2021 based on 36 countries was 20.67 percent. The highest value was in Greece: 31.83 percent and the lowest value was in Russia: 12.32 percent. The indicator is available from 1984 to 2021. Below is a chart for all countries where data are available.

Prices for Euro Area Stock Market Index (EU600) including live quotes, historical charts and news. Euro Area Stock Market Index (EU600) was last updated by Trading Economics this December 2 of 2025.

Graph and download economic data for Volatility of Stock Price Index for Euro Area (DISCONTINUED) (DDSM01EZA066NWDB) from 1984 to 2015 about volatility, stocks, Euro Area, Europe, price index, indexes, and price.

Stock prices of the largest European banks fell sharply in March 2023, as the collapse of Silicon Valley Bank and First Republic in the U.S. crumbled confidence in the sector. Shortly after the second and third largest U.S. bank failures, Credit Suisse went under, which pushed the stock prices of leading European banks down further. Towards the end of the month, stock prices increased notably, but remained well below prices at the start of March.

Graph and download economic data for Financial Market: Share Prices for Euro Area (19 Countries) (SPASTT01EZM661N) from Dec 1986 to Oct 2025 about stock market, Euro Area, and Europe.

Graph and download economic data for Financial Market: Share Prices for Euro Area (19 Countries) (SPASTT01EZQ661N) from Q1 1987 to Q3 2025 about stock market, Euro Area, and Europe.

Graph and download economic data for Share Prices: All Shares/Broad: Total for Euro Area (19 Countries) (SPASTT01EZM657N) from Jan 1987 to Oct 2025 about stock market, Euro Area, and Europe.

B&M European Value stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Context

Real and up to date stock market exchange of cryptocurrencies can be quite expensive and are hard to get. However, historical financial data are the starting point to develop algorithm(s) to analyze market trend and why not beat the market by predicting market movement.

Content

Data provided in this dataset are historical data from the beginning of EUR-USD pair market on Kraken exchange up to the present (2021 December). This data comes frome real trades on one of the most popular cryptocurrencies exchange.

Trading history

Historical market data, also known as trading history, time and sales or tick data, provides a detailed record of every trade that happens on Kraken exchange, and includes the following information: - Timestamp - The exact date and time of each trade. - Price - The price at which each trade occurred. - Volume - The amount of volume that was traded.

OHLCVT

In addition, OHLCVT data are provided for the most common period interval: 1 min, 5 min, 15 min, 1 hour, 12 hours and 1 day. OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information for each time period: - Open - The first traded price - High - The highest traded price - Low - The lowest traded price - Close - The final traded price - Volume - The total volume traded by all trades - Trades - The number of individual trades

Don't hesitate to tell me if you need other period interval 😉 ...

Update

This dataset will be updated every quarter to add new and up to date market trend. Let me know if you need an update more frequently.

Inspiration

Can you beat the market? Let see what you can do with these data!

This dataset provides values for STOCK PRICE VOLATILITY WB DATA.HTML reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Prices for Euro Area Stock Market Index (Euronext 100) including live quotes, historical charts and news. Euro Area Stock Market Index (Euronext 100) was last updated by Trading Economics this December 3 of 2025.

Context

Real and up to date stock market exchange of cryptocurrencies can be quite expensive and are hard to get. However, historical financial data are the starting point to develop algorithm(s) to analyze market trend and why not beat the market by predicting market movement.

Content

Data provided in this dataset are historical data from the beginning of EUR-CHF pair market on Kraken exchange up to the present (2021 December). This data comes frome real trades on one of the most popular cryptocurrencies exchange.

Trading history

Historical market data, also known as trading history, time and sales or tick data, provides a detailed record of every trade that happens on Kraken exchange, and includes the following information: - Timestamp - The exact date and time of each trade. - Price - The price at which each trade occurred. - Volume - The amount of volume that was traded.

OHLCVT

In addition, OHLCVT data are provided for the most common period interval: 1 min, 5 min, 15 min, 1 hour, 12 hours and 1 day. OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information for each time period: - Open - The first traded price - High - The highest traded price - Low - The lowest traded price - Close - The final traded price - Volume - The total volume traded by all trades - Trades - The number of individual trades

Don't hesitate to tell me if you need other period interval 😉 ...

Update

This dataset will be updated every quarter to add new and up to date market trend. Let me know if you need an update more frequently.

Inspiration

Can you beat the market? Let see what you can do with these data!

Graph and download economic data for Share Prices: All Shares/Broad: Total for Euro Area (19 Countries) (SPASTT01EZQ657N) from Q2 1987 to Q3 2025 about stock market, Euro Area, and Europe.

Stock Price Time Series for Edisun Power Europe AG. Edisun Power Europe AG, together with its subsidiaries, finances and operates photovoltaic systems in Europe. The company owned and operated 34 photovoltaic plants with an installed capacity of 106 megawatts in Switzerland, Germany, France, Italy, Portugal, and Spain. It sells solar energy to local power suppliers. Edisun Power Europe AG was founded in 1997 and is headquartered in Zurich, Switzerland.

European Seeds and Planting Stock Price Index for Agriculture by Country, 2022 Discover more data with ReportLinker!

Context

Real and up to date stock market exchange of cryptocurrencies can be quite expensive and are hard to get. However, historical financial data are the starting point to develop algorithm(s) to analyze market trend and why not beat the market by predicting market movement.

Content

Data provided in this dataset are historical data from the beginning of BNT-EUR pair market on Kraken exchange up to the present (2021 December). This data comes frome real trades on one of the most popular cryptocurrencies exchange.

Trading history

Historical market data, also known as trading history, time and sales or tick data, provides a detailed record of every trade that happens on Kraken exchange, and includes the following information: - Timestamp - The exact date and time of each trade. - Price - The price at which each trade occurred. - Volume - The amount of volume that was traded.

OHLCVT

In addition, OHLCVT data are provided for the most common period interval: 1 min, 5 min, 15 min, 1 hour, 12 hours and 1 day. OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information for each time period: - Open - The first traded price - High - The highest traded price - Low - The lowest traded price - Close - The final traded price - Volume - The total volume traded by all trades - Trades - The number of individual trades

Don't hesitate to tell me if you need other period interval 😉 ...

Update

This dataset will be updated every quarter to add new and up to date market trend. Let me know if you need an update more frequently.

Inspiration

Can you beat the market? Let see what you can do with these data!

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 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 Index: A Barometer of European Economic Health?

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