In January 2025, the index for consumer confidence in China ranged at 87.5 points, up from 86.4 points in the previous month. The index dropped considerably in the first half of 2022 and performed a sideways movement during 2023 and 2024. Consumer confidence Index The consumer confidence index (CCI), also called Index of Consumer Sentiment (ICS) is a commonly used indicator to measure the degree of economic optimism among consumers. Based on information about saving and spending activities of consumers, changes in business climate and future spending behavior are being projected. The CCI plays an important role for investors, retailers, and manufacturers in their decision-making processes. However, measurement of consumer confidence varies strongly from country to country. As consumers need time to react to economic changes, the CCI tends to lag behind other indicators like the consumer price index (CPI) and the producer price index (PPI). Development in China As shown by the graph at hand, confidence among Chinese consumers picked up since mid of 2016. In October 2017, the CCI hit a record value of 127.6 index points and entered into a sideward movement. Owing to a relative stability in GDP growth, a low unemployment rate, and a steady development of disposable household income, Chinese consumers gained more confidence in the state of the national economy. Those factors also contribute to the consumers’ spending power, which was reflected by a larger share of consumption in China’s GDP. After the outbreak of the coronavirus pandemic, consumer confidence dropped quickly in the beginning of 2020, but started to recover in the second half of the year, leading to a v-shaped movement of the index in 2020.

Consumer Confidence in the United States decreased to 57.90 points in March from 64.70 points in February 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 Japan decreased to 35 points in February from 35.20 points in January of 2025. This dataset provides - Japan Consumer Confidence - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Germany GDP Nowcast: swda: YoY: Contribution: Consumer Survey: Consumer Confidence Indicator (CI): sa: Euro Area 20 data was reported at 4.293 % in 10 Mar 2025. This records an increase from the previous number of 4.164 % for 03 Mar 2025. Germany GDP Nowcast: swda: YoY: Contribution: Consumer Survey: Consumer Confidence Indicator (CI): sa: Euro Area 20 data is updated weekly, averaging 4.452 % from Jan 2019 (Median) to 10 Mar 2025, with 323 observations. The data reached an all-time high of 6.349 % in 28 Mar 2022 and a record low of 2.395 % in 28 Sep 2020. Germany GDP Nowcast: swda: YoY: Contribution: Consumer Survey: Consumer Confidence Indicator (CI): sa: Euro Area 20 data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s Germany – Table DE.CEIC.NC: CEIC Nowcast: Gross Domestic Product (GDP).

France GDP Nowcast: swda: YoY: Contribution: Consumer Survey: Consumer Confidence Indicator (CI): sa: Euro Area 20 data was reported at 1.223 % in 03 Mar 2025. This records a decrease from the previous number of 1.385 % for 24 Feb 2025. France GDP Nowcast: swda: YoY: Contribution: Consumer Survey: Consumer Confidence Indicator (CI): sa: Euro Area 20 data is updated weekly, averaging 0.000 % from Jan 2019 (Median) to 03 Mar 2025, with 322 observations. The data reached an all-time high of 2.215 % in 23 Dec 2024 and a record low of 0.000 % in 26 Dec 2022. France GDP Nowcast: swda: YoY: Contribution: Consumer Survey: Consumer Confidence Indicator (CI): sa: Euro Area 20 data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s France – Table FR.CEIC.NC: CEIC Nowcast: Gross Domestic Product (GDP).

Consumer Confidence in Luxembourg decreased to -11.40 points in February from -7.80 points in January of 2025. This dataset provides the latest reported value for - Luxembourg Consumer Confidence - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

United States GDP Nowcast: saar: YoY: Contribution: Consumer Survey: Consumer Sentiment Index (CSI) data was reported at 0.336 % in 10 Mar 2025. This records an increase from the previous number of 0.310 % for 03 Mar 2025. United States GDP Nowcast: saar: YoY: Contribution: Consumer Survey: Consumer Sentiment Index (CSI) data is updated weekly, averaging 0.207 % from Jan 2019 (Median) to 10 Mar 2025, with 323 observations. The data reached an all-time high of 0.640 % in 27 Nov 2023 and a record low of 0.000 % in 17 Aug 2020. United States GDP Nowcast: saar: YoY: Contribution: Consumer Survey: Consumer Sentiment Index (CSI) data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s United States – Table US.CEIC.NC: CEIC Nowcast: Gross Domestic Product (GDP).

United States CCI: New York data was reported at 90.800 1985=100 in Feb 2025. This records a decrease from the previous number of 96.900 1985=100 for Jan 2025. United States CCI: New York data is updated monthly, averaging 84.000 1985=100 from Feb 2007 (Median) to Feb 2025, with 217 observations. The data reached an all-time high of 132.800 1985=100 in Nov 2018 and a record low of 17.800 1985=100 in Feb 2009. United States CCI: New York data remains active status in CEIC and is reported by The Conference Board. The data is categorized under Global Database’s United States – Table US.H042: Consumer Confidence Index. [COVID-19-IMPACT]

The statistic shows the gross domestic product (GDP) per capita in Japan from 1987 to 2023, with projections up until 2029. In 2023, the estimated gross domestic product per capita in Japan was around 33,898.99 U.S. dollars. For further information, see Japan's GDP. Japan's economy Japan is the world’s second largest developed economy and a member of the Group of Eight, also known as G8, which is comprised of the eight leading industrialized countries. Due to a weak financial sector, overregulation and a lack of demand, Japan suffered substantially from the early 1990s until 2000, a time referred to as ‘’The Lost Decade’’. Japan’s economy is still slowly recovering from the country’s asset price bubble collapse; however it continues to struggle to retain economic milestones achieved in the 1980s. Japan’s response to the crash was to stimulate the economy, which in turn resulted in extensive amounts of debt that further increased into the 21st century, most notably after the 2008 financial crisis. Despite maintaining a surprisingly low unemployment rate, demand within the country remains inadequate, primarily because Japanese residents spend a rather small fraction of the money they earned from the workplace. Lower demand often has a direct effect on production, with companies seeing not enough profits to continue production at such a high rate. Based on the consumer confidence index, Japanese households found that their quality of life, income growth, employment and propensity to durable goods was below satisfactory standards, perhaps due to these households still experiencing the effects of the 1990s bubble crash.

The statistic shows the gross domestic product (GDP) per capita in Brazil from 1987 to 2022, with projections up until 2029. GDP is the total value of all goods and services produced in a country in a year. It is considered to be a very important indicator of the economic strength of a country and a positive change is an indicator of economic growth. In 2023, the estimated GDP per capita in Brazil amounted to around 10,642.44 U.S. dollars. For further information see GDP of Brazil.

Economical future of Brazil

GDP per capita is worked out by taking the country’s total gross domestic product and dividing it by the total population, which essentially helps determine growth of an economy as well as changes in productivity for every person living in the country. As a member of economic organizations such as the G20 as well as the BRIC countries, Brazil has certainly made its mark as one of the strongest economies in the world. Despite experiencing economic fluctuations often, the general direction of the Brazilian economy is mainly positive. With recent improvements within the government, bank and education systems, Brazil has become a slightly more significant option for international investments.

Additionally, a profusion of natural resources, a strong agricultural and industrial sector, and a growing service sector has made investors more intrigued in the future of the country. Additionally, at the end of 2014, consumer confidence saw a slight, however noticeable improvement, implying that individual financial situations and hope for the future of the country are very present within the country. Shortly after, consumer confidence plummeted, showing little faith in Brazil's economic future. However, the economic benchmarks point in a different direction.

The Consumer Sentiment Index in the United States stood at 71.8 in November 2024, an increase from the previous month. The index is normalized to a value of 100 in December 1964 and based on a monthly survey of consumers, conducted in the continental United States. It consists of about 50 core questions which cover consumers' assessments of their personal financial situation, their buying attitudes and overall economic conditions.

The statistic shows the growth rate of the real gross domestic product (GDP) in the United States from 2019 to 2023, with projections up until 2029. GDP refers to the total market value of all goods and services that are produced within a country per year. It is an important indicator of the economic strength of a country. Real GDP is adjusted for price changes and is therefore regarded as a key indicator for economic growth. In 2023, the growth of the real gross domestic product in the United States was around 2.53 percent compared to the previous year. See U.S. GDP per capita and the US GDP for more information.

Real gross domestic product (GDP) of the United States

The gross domestic product (GDP) of a country is a crucial economic indicator, representing the market value of the total goods and services produced and offered by a country within a year, thus serving as one of the indicators of a country’s economic state. The real GDP of a country is defined as its gross domestic product adjusted for inflation.

An international comparison of economic growth rates has ranked the United States alongside other major global economic players such as China and Russia in terms of real GDP growth. With further growth expected during the course of the coming years, as consumer confidence continues to improve, experts predict that the worst is over for the United States economy.

A glance at US real GDP figures reveals an overall increase in growth, with sporadic slips into decline; the last recorded decline took place in Q1 2011. All in all, the economy of the United States can be considered ‘well set’, with exports and imports showing positive results. Apart from this fact, the United States remains one of the world’s leading exporting countries, having been surpassed only by China and tailed by Germany. It is also ranked first among the top global importers. Despite this, recent surveys revealing Americans’ assessments of the U.S. economy have yielded less optimistic results. Interestingly enough, this consensus has been mutual across the social and environmental spectrum. On the other hand, GDP is often used as an indicator for the standard of living in a country – and most Americans seem quite happy with theirs.

Consumer spending across India amounted to 24.57 trillion rupees by the end of the second quarter of 2024. It reached an all-time high during the fourth quarter of 2023. What is consumer spending? Consumer spending refers to the total money spent on final goods and services by individuals and households in an economy. It is an important metric that directly impacts the GDP of a country. Items that qualify as consumer spending include durable and nondurable goods and services. Various factors such as debt held by consumers, wages, supply and demand, taxes, and government-based economic stimulus can impact consumer spending in a country. Positive consumer outlook in India India’s consumer spending reflects a positive outlook with renewed consumer confidence post-COVID. Its consumer market is set to become one of the largest in the world as the number of middle- to high-income households rises with increasing amounts of disposable incomes. The country’s young demographic is also considered a driving force for increased consumer spending. Consumer electronics such as smartphones, laptops, and gaming consoles were the preferred items among Indian holiday shoppers in 2023.

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.

Dollar index faces uncertain future amid economic headwinds

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

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.

Taiwan Weighted Index: A Reliable Indicator of 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

In the aftermath of the shock win for leave in the UK’s referendum on EU membership, there has been considerable uncertainty over the short- and long-term impacts on the UK economy. This report provides an overview of the impact Brexit has had on key economic indicators such as GDP, interest rates, unemployment and the housing market, and the subsequent impact on consumer confidence and retail growth and projections. Read More

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.

[Video] S&P 500: Bull or Bear?

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

GDP即时预测：季节性和工作日调整数据：同比：贡献：消费者调查：消费者信心指数（CI）：SA：欧元区20国在03-10-2025达4.293%，相较于03-03-2025的4.164%有所增长。GDP即时预测：季节性和工作日调整数据：同比：贡献：消费者调查：消费者信心指数（CI）：SA：欧元区20国数据按周更新，01-07-2019至03-10-2025期间平均值为4.452%，共323份观测结果。该数据的历史最高值出现于03-28-2022，达6.349%，而历史最低值则出现于09-28-2020，为2.395%。CEIC提供的GDP即时预测：季节性和工作日调整数据：同比：贡献：消费者调查：消费者信心指数（CI）：SA：欧元区20国数据处于定期更新的状态，数据来源于CEIC Data，数据归类于全球数据库的德国 – Table DE.CEIC.NC: CEIC Nowcast: Gross Domestic Product (GDP)。

Consumer Confidence in South Africa decreased to -20 points in the first quarter of 2025 from -6 points in the fourth quarter of 2024. This dataset provides the latest reported value for - South Africa Consumer Confidence - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus 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.

PRIF^J Priority Income Fund Inc. 6.000% Series J Term Preferred Stock due 2028

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