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.

Israel's main stock market index, the TA-125, fell to 3098 points on September 1, 2025, losing 0.54% from the previous session. Over the past month, the index has climbed 0.59% and is up 48.68% 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 September of 2025.

France's main stock market index, the FR40, fell to 7655 points on September 2, 2025, losing 0.69% from the previous session. Over the past month, the index has climbed 0.30% and is up 1.05% 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.

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

Spain's main stock market index, the ES35, fell to 14918 points on September 2, 2025, losing 0.15% from the previous session. Over the past month, the index has climbed 3.69% and is up 30.91% 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 September of 2025.

Iran Market Capitalization: Tehran Stock Exchange (TSE) data was reported at 1,743.023 USD bn in Sep 2023. This records a decrease from the previous number of 1,761.129 USD bn for Aug 2023. Iran Market Capitalization: Tehran Stock Exchange (TSE) data is updated monthly, averaging 105.978 USD bn from Dec 2005 (Median) to Sep 2023, with 199 observations. The data reached an all-time high of 1,991.152 USD bn in May 2023 and a record low of 33.814 USD bn in Jun 2007. Iran Market Capitalization: Tehran Stock Exchange (TSE) data remains active status in CEIC and is reported by Tehran Stock Exchange. The data is categorized under Global Database’s Iran – Table IR.Z002: Tehran Stock Exchange: Market Capitalization. [COVID-19-IMPACT]

Euro Area's main stock market index, the EU50, rose to 5377 points on September 2, 2025, gaining 0.16% from the previous session. Over the past month, the index has climbed 2.57% and is up 9.46% 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.

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

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.

China's main stock market index, the SHANGHAI, rose to 3876 points on September 1, 2025, gaining 0.46% from the previous session. Over the past month, the index has climbed 8.16% and is up 37.87% 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 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.

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.

FTSE 100: Where to Next?

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

United States New York Stock Exchange: Index: US 100 Index data was reported at 16,491.357 NA in Apr 2025. This records a decrease from the previous number of 16,852.600 NA for Mar 2025. United States New York Stock Exchange: Index: US 100 Index data is updated monthly, averaging 10,169.600 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 17,440.815 NA in Feb 2025 and a record low of 5,695.000 NA in May 2012. United States New York Stock Exchange: Index: US 100 Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: New York Stock Exchange: Monthly.

This statistic shows Euronext Lisbon's ** strongest market capitalization for companies incorporated in Portugal. As of the end of June 2025, the highest market capitalization recorded was for EDP, which reached **** billion euros. Jerónimo Martins, SGPS came second with approximately **** billion euros, followed by Galp Energia, with a market capitalization of **** billion euros.

Jamaica Stock Exchange: Index: JSE Junior Market Index data was reported at 3,517.840 NA in Apr 2025. This records a decrease from the previous number of 3,673.940 NA for Mar 2025. Jamaica Stock Exchange: Index: JSE Junior Market Index data is updated monthly, averaging 2,949.870 NA from Jan 2012 (Median) to Apr 2025, with 159 observations. The data reached an all-time high of 4,451.620 NA in Apr 2022 and a record low of 592.480 NA in Feb 2013. Jamaica Stock Exchange: Index: JSE Junior Market Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s Jamaica – Table JM.EDI.SE: Jamaica Stock Exchange: Monthly.

Graph and download economic data for Financial Market: Share Prices for Luxembourg (SPASTT01LUM661N) from Jan 1999 to Jun 2025 about Luxembourg and stock market.

Today's oil prices on the stock market have been quite volatile. Factors such as supply and demand dynamics, geopolitical events, economic indicators, and market speculation influence the price of oil. This article explores the impact of the ongoing conflict in the Middle East, global demand trends, supply levels, and market speculation on oil prices. It also highlights the potential for rapid changes in oil prices due to various geopolitical, economic, and market factors.

India's main stock market index, the SENSEX, rose to 80364 points on September 1, 2025, gaining 0.70% from the previous session. Over the past month, the index has declined 0.81% and is down 2.66% 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 September of 2025.

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

The dataset contains historical technical data of Dhaka Stock Exchange (DSE). The data was collected from different sources found in the internet where the data was publicly available. The data available here are used for information and research purposes and though to the best of our knowledge, it does not contain any mistakes, there might still be some mistakes. It is not encourages to use this dataset for portfolio management purposes and use this dataset out of your own interest. The contributors do not hold any liability if it is used for any purposes.