Euro Area's main stock market index, the EU50, fell to 5385 points on July 11, 2025, losing 1.03% from the previous session. Over the past month, the index has climbed 0.45% and is up 6.78% 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 July 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

India's main stock market index, the SENSEX, fell to 82500 points on July 11, 2025, losing 0.83% from the previous session. Over the past month, the index has climbed 0.99% and is up 2.46% 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 July of 2025.

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SET: No of Listed Transferable Subscription Right data was reported at 0.000 Unit in 2017. This stayed constant from the previous number of 0.000 Unit for 2016. SET: No of Listed Transferable Subscription Right data is updated yearly, averaging 0.000 Unit from Dec 2004 (Median) to 2017, with 14 observations. SET: No of Listed Transferable Subscription Right data remains active status in CEIC and is reported by The Stock Exchange of Thailand. The data is categorized under Global Database’s Thailand – Table TH.Z010: The Stock Exchange of Thailand: Market Statistics: Annual.

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.

Browse LSEG's Money Market (MM) Pricing Data, and benefit from our comprehensive coverage real-time and historical pricing and indices data.

The global market size of Labor is $XX million in 2018 with XX CAGR from 2014 to 2018, and it is expected to reach $XX million by the end of 2024 with a CAGR of XX% from 2019 to 2024.
Global Labor Market Report 2019 - Market Size, Share, Price, Trend and Forecast is a professional and in-depth study on the current state of the global Labor industry. The key insights of the report:
1.The report provides key statistics on the market status of the Labor manufacturers and is a valuable source of guidance and direction for companies and individuals interested in the industry.
2.The report provides a basic overview of the industry including its definition, applications and manufacturing technology.
3.The report presents the company profile, product specifications, capacity, production value, and 2013-2018 market shares for key vendors.
4.The total market is further divided by company, by country, and by application/type for the competitive landscape analysis.
5.The report estimates 2019-2024 market development trends of Labor industry.
6.Analysis of upstream raw materials, downstream demand, and current market dynamics is also carried out
7.The report makes some important proposals for a new project of Labor Industry before evaluating its feasibility.
There are 4 key segments covered in this report: competitor segment, product type segment, end use/application segment and geography segment.
For competitor segment, the report includes global key players of Labor as well as some small players.
The information for each competitor includes:
* Company Profile
* Main Business Information
* SWOT Analysis
* Sales, Revenue, Price and Gross Margin
* Market Share

For product type segment, this report listed main product type of Labor market
* Product Type I
* Product Type II
* Product Type III

For end use/application segment, this report focuses on the status and outlook for key applications. End users sre also listed.
* Application I
* Application II
* Application III

For geography segment, regional supply, application-wise and type-wise demand, major players, price is presented from 2013 to 2023. This report covers following regions:
* North America
* South America
* Asia & Pacific
* Europe
* MEA (Middle East and Africa)
The key countries in each region are taken into consideration as well, such as United States, China, Japan, India, Korea, ASEAN, Germany, France, UK, Italy, Spain, CIS, and Brazil etc.

Reasons to Purchase this Report:
* Analyzing the outlook of the market with the recent trends and SWOT analysis
* Market dynamics scenario, along with growth opportunities of the market in the years to come
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* Regional and country level analysis integrating the demand and supply forces that are influencing the growth of the market.
* Market value (USD Million) and volume (Units Million) data for each segment and sub-segment
* Competitive landscape involving the market share of major players, along with the new projects and strategies adopted by players in the past five years
* Comprehensive company profiles covering the product offerings, key financial information, recent developments, SWOT analysis, and strategies employed by the major market players
* 1-year analyst support, along with the data support in excel format.
We also can offer customized report to fulfill special requirements of our clients. Regional and Countries report can be provided as well.

The Flexible Current Probes market is experiencing significant growth driven by the increasing demand for versatile and reliable measurement solutions across various industries, such as telecommunications, aerospace, automotive, and electronics manufacturing. These innovative probes are essential tools for electrica

Explore LSEG's Euronext Market Data, including full access to benchmarks and indices, and corporate action and dividend data.

Description

This dataset, titled "Cryptocurrency Market Sentiment & Prediction," is a synthetic collection of real-time crypto market data designed for advanced analysis and predictive modeling. It captures a comprehensive range of features including price movements, social sentiment, news impact, and trading patterns for 10 major cryptocurrencies. Tailored for data scientists and analysts, this dataset is ideal for exploring market volatility, sentiment analysis, and price prediction, particularly in the context of significant events like the Bitcoin halving in 2024 and increasing institutional adoption.

Key Features Overview: - Price Movements: Tracks current prices and 24-hour price change percentages to reflect market dynamics. - Social Sentiment: Measures sentiment scores from social media platforms, ranging from -1 (negative) to 1 (positive), to gauge public perception. - News Sentiment and Impact: Evaluates sentiment from news sources and quantifies their potential impact on market behavior. - Trading Patterns: Includes data on 24-hour trading volumes and market capitalization, crucial for understanding market activity. - Technical Indicators: Features metrics like the Relative Strength Index (RSI), volatility index, and fear/greed index for in-depth technical analysis. - Prediction Confidence: Provides a confidence score for predictive models, aiding in assessing forecast reliability.

Purpose and Applications: - Perfect for machine learning tasks such as price prediction, sentiment-price correlation studies, and volatility classification. - Supports time series analysis for forecasting price movements and identifying volatility clusters. - Valuable for research into the influence of social media and news on cryptocurrency markets, especially during high-impact events.

Dataset Scope: - Covers a simulated 30-day period, offering a snapshot of market behavior under varying conditions. - Focuses on major cryptocurrencies including Bitcoin, Ethereum, Cardano, Solana, and others, ensuring relevance to current market trends.

Dataset Structure Table:

Dataset Statistics Table:

This dataset is a powerful resource for machine learning projects, sentiment analysis, and crypto market research, providing a robust foundation for AI/ML model development and testing.

Stock market return (%, year-on-year) in Kenya was reported at 18.41 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Dive into Market Research Intellect's Streaming Current Detector Market Report, valued at USD 250 million in 2024, and forecast to reach USD 500 million by 2033, growing at a CAGR of 8.5% from 2026 to 2033.

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.

What happens to gold if CPI increases?

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 Inrush Current Limiters (ICL) market is experiencing significant evolution, driven by the growing demand for energy-efficient solutions in various industries. ICLs play a critical role in protecting electrical systems, preventing sudden surges in current that can damage components and disrupt operations. Commonl

United States Avg Weekly Earnings: sa: RT: Meat, Fish & Seafood Market data was reported at 488.560 USD in May 2018. This records an increase from the previous number of 484.900 USD for Apr 2018. United States Avg Weekly Earnings: sa: RT: Meat, Fish & Seafood Market data is updated monthly, averaging 423.130 USD from Mar 2006 (Median) to May 2018, with 147 observations. The data reached an all-time high of 518.680 USD in Mar 2015 and a record low of 394.940 USD in Jan 2014. United States Avg Weekly Earnings: sa: RT: Meat, Fish & Seafood Market data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G033: Current Employment Statistics Survey: Average Weekly and Hourly Earnings: Seasonally Adjusted.

Sweetener Market Data (SMD) report - beet and cane processors and cane refiners in the U.S. are required by the FAIR Act of 1996, as amended, to report data on physical quantities delivered by use for "Multiple and All Other Food Uses" on a monthly basis. Quantities are reported by region. Regions include: "New England", "Mid Atlantic", "North Central", "South", "West" and "Puerto Rico".

The High Current Shunt Resistor market plays a crucial role in various industries, including automotive, telecommunications, and renewable energy, by providing precise current measurement and monitoring solutions. These resistors are engineered to handle significant currents while maintaining accuracy and reliabilit

Russia Number of Trades: Money Market data was reported at 180.600 Unit th in Nov 2017. This records a decrease from the previous number of 188.800 Unit th for Oct 2017. Russia Number of Trades: Money Market data is updated monthly, averaging 156.600 Unit th from Jul 2012 (Median) to Nov 2017, with 65 observations. The data reached an all-time high of 310.500 Unit th in Dec 2014 and a record low of 97.200 Unit th in Jan 2016. Russia Number of Trades: Money Market data remains active status in CEIC and is reported by Moscow Exchange. The data is categorized under Global Database’s Russian Federation – Table RU.ZA010: Moscow Exchange: All Markets: Number of Trades.

The Outdoor Bushing Current Transformers (CBCTs) market is poised for significant growth as industries increasingly demand reliable and efficient power management solutions. These specialized devices are crucial in electrical substations and power distribution networks, where they function to measure current flowing