The main stock market index in the United States (US500) decreased 176 points or 2.99% since the beginning of 2025, 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 March 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 Report Covers Rolling Stock Manufacturers and is Segmented by Type (Locomotives, Metros, Passenger Coaches, Other Types), by Propulsion Type (Diesel, Electric, Electro-diesel), and by Geography (North America, Europe, Asia-Pacific, and Rest of the World). The report offers market size and forecasts for rolling stock market in value (USD Billion) for above all segments

The main stock market index in China (SHANGHAI) increased 22 points or 0.66% since the beginning of 2025, 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 March of 2025.

This statistic presents the outlook that registered investment advisors (RIAs) have for the stock market in the first half of 2020. At the time of the survey, 51% of RIAs thought the stock market would increase in value overall.

No description was included in this Dataset collected from the OSF

The main stock market index in Argentina (Merval) decreased 93669 points or 3.70% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks this benchmark index from Argentina. Argentina Stock Market (MERVAL) - values, historical data, forecasts and news - updated on March 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.

How accurate is machine learning in stock market? (NSE TATASTLBSL 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 size of the Middle East And Africa ETF Market was valued at USD XX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 9.00">> 9.00% during the forecast period. The ETF (Exchange-Traded Fund) market refers to the financial industry focused on creating, managing, and trading ETFs, which are investment funds that track the performance of a specific index, sector, commodity, or asset class. ETFs combine the diversification of mutual funds with the liquidity and convenience of stocks, allowing investors to buy or sell shares throughout the trading day at market prices. This industry is a key segment of the broader financial markets and has grown rapidly due to its accessibility, cost efficiency, and flexibility for both retail and institutional investors. ETFs are often classified based on the assets they track, such as equities, bonds, commodities, or currencies. The ETF market offers a wide variety of products, including index-based ETFs, which mirror well-known indices like the S&P 500, sector-specific ETFs that focus on industries like technology or healthcare, and thematic ETFs, which center around global trends like clean energy or artificial intelligence. These products are usually managed by large financial institutions like BlackRock, Vanguard, and State Street Global Advisors. Recent developments include: In March 2024, Abu Dhabi Securities Exchange and HSBC Bank have entered into a partnership to expand the availability of digital fixed-income securities in the capital markets of the region. In collaboration with HSBC, ADX will investigate a framework that would allow digital assets, such digital bonds, to be listed on ADX and accessible via HSBC Orion, the bank's digital assets platform., In September 2023, the Ministry of Investment signed agreements with Al-Rajhi Bank, Alinma Bank, and Banque Saudi Fransi to strengthen the position of the digital banking industry and aid these institutions provide investors with better service.. Key drivers for this market are: Decline in Cost of Service Providers, Availiblity of New distribution platform in the region. Potential restraints include: Market Saturation (lack of Availiblity of new asset class), Extreme market events increasing risk associate with ETF, dampening their demand.. Notable trends are: Equity ETFs a Gateway to Diversified Exposure in the Region's Stock Markets.

Stock market forecasting is one of the most challenging problems in today’s financial markets. According to the efficient market hypothesis, it is almost impossible to predict the stock market with 100% accuracy. However, Machine Learning (ML) methods can improve stock market predictions to some extent. In this paper, a novel strategy is proposed to improve the prediction efficiency of ML models for financial markets. Nine ML models are used to predict the direction of the stock market. First, these models are trained and validated using the traditional methodology on a historic data captured over a 1-day time frame. Then, the models are trained using the proposed methodology. Following the traditional methodology, Logistic Regression achieved the highest accuracy of 85.51% followed by XG Boost and Random Forest. With the proposed strategy, the Random Forest model achieved the highest accuracy of 91.27% followed by XG Boost, ADA Boost and ANN. In the later part of the paper, it is shown that only classification report is not sufficient to validate the performance of ML model for stock market prediction. A simulation model of the financial market is used in order to evaluate the risk, maximum draw down and returns associate with each ML model. The overall results demonstrated that the proposed strategy not only improves the stock market returns but also reduces the risks associated with each ML model.

The main stock market index in Israel (TA-125) increased 34 points or 1.41% since the beginning of 2025, 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 March of 2025.

Stock Market Expectation: Germany: Increase data was reported at 27.500 % in Feb 2025. This records a decrease from the previous number of 30.500 % for Jan 2025. Stock Market Expectation: Germany: Increase data is updated monthly, averaging 57.100 % from Dec 1991 (Median) to Feb 2025, with 399 observations. The data reached an all-time high of 85.000 % in Aug 2000 and a record low of 21.700 % in Mar 2024. Stock Market Expectation: Germany: Increase data remains active status in CEIC and is reported by Leibniz Centre for European Economic Research. The data is categorized under Global Database’s Germany – Table DE.S001: Indicator of Economic Sentiment: ZEW.

The main stock market index in Spain (ES35) increased 1801 points or 15.53% since the beginning of 2025, 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 March of 2025.

The main stock market index in Kenya (Nairobi 20) increased 244 points or 12.12% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks this benchmark index from Kenya. Kenya Stock Market (NSE20) - values, historical data, forecasts and news - updated on March of 2025.

The main stock market index In the Euro Area (EU50) increased 521 points or 10.65% since the beginning of 2025, 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 March 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.

PFXNL Stock: The Stock Market Bubble Is About to Burst

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 Metro Rolling Stock market plays a crucial role in urban transportation systems, offering vehicles that operate on dedicated railway tracks to facilitate efficient, high-capacity transit in metropolitan areas. These rolling stocks, which include metro trains, light rails, and system components, are integral in m

The main stock market index in South Korea (KOSPI) increased 238 points or 9.90% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks this benchmark index from South Korea. South Korea Stock Market - values, historical data, forecasts and news - updated on March of 2025.

The Rolling Stock Market is segmented into various product categories, including locomotives, rapid transit, and wagons. Locomotives account for the largest market share due to their central role in providing motive power to trains. Rapid transit systems, such as metros and light rail vehicles, are also gaining popularity in urban areas, driven by the need for efficient and environmentally friendly transportation options. Wagons, which serve as the primary means of transporting freight, are expected to witness steady growth due to the increasing demand for efficient cargo transportation. Recent developments include: In February 2023, Stadler Rail AG joined forces with ASPIRE Engineering Research Centre and Utah State University in order to build a battery-driven passenger train around the concept of FLIRT Akku. The project encompasses the development, manufacture, and testing of a two-car multi-unit that runs on batteries under the brand name FLIRT Akku., Stadler Rail AG announced it had acquired BBR Verkehrstechnik GmbH (BBR), a rail company, and its group businesses in February 2023 to strengthen its internal know-how in the fields of digitization and signaling technology., Alstom SA is setting up a new factory for railway electrification in Valmadrera (Lecco, Italy) by March 2023. It will produce power transmission components for rail, metro, or tram lines., Siemens Mobility has entered into an agreement with Indian Railways under which Siemens India received an order for 9,000-hp locomotives from Indian Railways totaling 1,200 units – the largest ever single order placed with Siemens Mobility and Siemens India in their history. Siemens Mobility will design, develop, assemble, and test these trains for over a period of thirty-five years from delivery, and they shall also render full-service maintenance., In November 2022, Siemens Mobility unveiled plans to build a train bogies factory in Aurangabad, India, capable of delivering more than one export consignment exceeding two hundred bogies at once. These rail bogies were made by Siemens using the SF30 Combino Plus global design idea., In December 2022, HS2 awarded contracts to a joint venture comprising Hitachi Rail and Alstom (HAH-S) for the development, manufacture, and maintenance of high-speed rolling stock for Phase 1.. Notable trends are: Data analytics and advanced maintenance usage are fueling market growth.

The global preserved sweet corn market reached $X in 2022, growing by X% against the previous year. The market value increased at an average annual rate of X% from 2012 to 2022; the trend pattern remained relatively stable, with somewhat noticeable fluctuations being recorded throughout the analyzed period. The most prominent rate of growth was recorded in 2019 with an increase of X% against the previous year. Over the period under review, the global market reached the peak level in 2022 and is expected to retain growth in years to come.