Consumer Confidence in the United States increased to 60.50 points in June from 52.20 points in May of 2025. This dataset provides the latest reported value for - United States Consumer Sentiment - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Consumer Confidence in China decreased to 87.50 points in March from 88.40 points in February of 2025. This dataset provides - China Consumer Confidence - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset provides values for CONSUMER CONFIDENCE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Ipsos Global @dvisor wave 18 was conducted on February 2 and February 14, 2011. It included the following question sections: A: Demographic Profile, B: Consumer Confidence, R: Reuters Battery, CB: Environmental Concern.

Ipsos Global @dvisor wave 35 was conducted on July 3 and July 17, 2012. It included the following question sections: A: Demographic Profile, B: Consumer Confidence, R: Reuters Battery, FD: Country Image Rating - France, H: Economy / Spending / Purchasing, BA: Intentions to Purchase Gold, CB: Environmental Concern, DV: Workplace.

Consumer Confidence in Canada increased to 48.20 points in May from 45.40 points in April of 2025. This dataset provides - Canada Consumer Confidence - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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.

CB Chubb Limited Common Stock

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

Specialised design activities are in demand from companies across a plethora of industries, with advertising agencies, manufacturers, corporate clients and hospitality businesses being key downstream markets. Consumer spending on goods and fashion items and the number of property transactions also impact demand for specialised designers. A growing number of enterprises operating in France has expanded the potential client pool for designers, as these businesses require interior design services and creative solutions for their products. Revenue is expected to climb at a compound annual rate of 8.7% over the five years through 2025, including a 1.4% hike in 2025 to €3.8 billion. Demand resurged from pandemic lows in 2021 and 2022, driven by rebounding business and consumer spending. Strong consumer consumption elevated demand for product and fashion design services. A recovery in the housing market and investment in renovations by corporate and hospitality clients bolstered interior design growth. However, high inflation and interest rates have restricted capital expenditure and R&D investment, hindering demand for design services since late 2022. Squeezed consumer finances have weakened retail spending, reducing product and fashion design clients. The real estate market has also faltered, with a significant reduction in housing transactions impacting interior design demand. Falling inflation and interest rates by late 2024 have opened up opportunities. However, ongoing geopolitical tensions and political instability have weighed on consumer and business sentiment and expenditure. Revenue is expected to climb at a compound annual rate of 3.6% over the five years through 2030 to €4.6 billion. Anticipated improvement in economic conditions, thanks to lower inflation and interest rates, will drive business and consumer spending. Businesses will invest in design solutions to innovate and meet evolving client preferences. Enhanced consumer sentiment and disposable income will drive fashion and interior design demand. The industry will also focus on personalisation and sustainability to meet consumer expectations and the drive towards green industrial and fashion designs. Adoption of technology like AI will also speed up, with these tools enhancing design agencies’ efficiency and creativity. Companies embracing these trends will gain a competitive edge and attract more clients.