Business Confidence in Germany increased to 88.40 points in June from 87.50 points in May of 2025. This dataset provides the latest reported value for - Germany Business Confidence - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

ZEW Economic Sentiment Index in Germany increased to 52.70 points in July from 47.50 points in June of 2025. This dataset provides the latest reported value for - Germany Zew Economic Sentiment Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This statistic shows the business confidence index for the industrial sector in Germany from 2008 to 2017, with projections up until 2022. In 2017, the confidence index for the German industry had ranged at approximately 8.13 index points, indicating an increase in business confidence.

Inflation Expectation: Euro Area: Decrease data was reported at 28.700 % in Apr 2025. This records an increase from the previous number of 22.500 % for Mar 2025. Inflation Expectation: Euro Area: Decrease data is updated monthly, averaging 14.700 % from Feb 1999 (Median) to Apr 2025, with 315 observations. The data reached an all-time high of 87.600 % in Feb 2023 and a record low of 0.000 % in Feb 2018. Inflation Expectation: Euro Area: Decrease 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 Consumer Confidence Index (CCI) of Germany was ***** in September 2024, compared with ***** a year earlier. Consumer confidence in Germany had been falling from Summer 2021 until November 2022, with fears that the German economy's reopening after the COVID-19 pandemic would not be as positive as was initially imagined due to inflationary pressures, while the Russian invasion of Ukraine in February 2022, causing energy prices in Germany to spike, further dampened business confidence. In spite of relatively slow growth between 2023 and 2024, business confidence has somewhat returned to Germany, likely due to falling energy prices and decreases in inflation.

Germany SE: Services: Improve data was reported at 30.200 % in Apr 2025. This records a decrease from the previous number of 42.700 % for Mar 2025. Germany SE: Services: Improve data is updated monthly, averaging 35.900 % from Apr 1999 (Median) to Apr 2025, with 313 observations. The data reached an all-time high of 77.100 % in Apr 2000 and a record low of 5.900 % in Oct 2008. Germany SE: Services: Improve 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.

This statistic shows the business confidence index for the retail sector in Germany from 2008 to 2017, with projections up until 2022. In 2017, the confidence index for the German retail sector ranged at approximately **** index points, indicating a slight increase in business confidence.

This statistic shows the business confidence index for the service sector in Germany from 2008 to 2017, with projections up until 2022. In 2017, the confidence index for the German service industry ranged at approximately ***** index points, indicating a major increase in business confidence.

Long Term Interest Expectation: Germany: Increase data was reported at 40.500 % in Apr 2025. This records a decrease from the previous number of 48.300 % for Mar 2025. Long Term Interest Expectation: Germany: Increase data is updated monthly, averaging 46.500 % from Dec 1991 (Median) to Apr 2025, with 401 observations. The data reached an all-time high of 81.300 % in Mar 2011 and a record low of 2.400 % in Sep 1992. Long Term Interest 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.

Over the past five years, players in the advertising time and space marketing industry have faced difficult market conditions. The advertising industry as a whole is highly susceptible to economic fluctuations, as companies often reduce their advertising expenditure in times of economic uncertainty, which leads to a drop in sales in the industry. The low demand for advertising hit marketers particularly hard at the beginning of the five-year period during the pandemic. Manufacturers and retailers in particular were reluctant to advertise. In 2023 and 2024, subdued consumer sentiment and increased savings behaviour also led to lower demand for advertising space and prevented sales growth. Within the markets, there has been a loss of reach for traditional advertising channels such as TV advertising over the past five years, which has also led to a decline in demand for them. Digital advertising markets and streaming platforms, on the other hand, have seen an increase in reach. The rise of digital platforms and the shift in media consumption to the internet have also led to a massive shift in advertising expenditure towards online advertising. This requires marketers to increasingly focus their strategies on online content in order to remain successful. Industry players that have successfully established themselves on the digital market have been able to benefit from the growth of this market segment. Strategies such as cross-media marketing offers and more intensive cooperation with advertising agencies in order to offer customers a comprehensive range of services were also convincing. On average over the past five years, industry turnover has nevertheless fallen by 1.7% per year to 9.7 billion euros. A slight decline in turnover of 0.3% is expected in the current year.The business expectations of German companies will remain somewhat subdued in 2025. Even if the German population can expect higher purchasing power in 2025, savings behaviour is likely to continue to have a dampening effect on consumer spending. Large marketing groups will be able to achieve higher profit margins, while smaller players will be exposed to stronger price competition.In the next five years, the increasing level of digitalisation should have a positive impact on industry sales. New offerings and improved consumer accessibility via online channels are a growth driver for the industry. It will be important to recruit qualified specialists at an early stage, particularly in the areas of digital marketing and technology. Thanks to new digital opportunities, industry turnover is expected to grow by an average of 0.5% annually to €10 billion over the next five years.

ZEW Economic Sentiment Index In the Euro Area increased to 36.10 points in July from 35.30 points in June of 2025. This dataset provides the latest reported value for - Euro Area Zew Economic Sentiment Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Inflation Expectation: Germany: Increase data was reported at 25.700 % in Apr 2025. This records a decrease from the previous number of 29.800 % for Mar 2025. Inflation Expectation: Germany: Increase data is updated monthly, averaging 28.700 % from Dec 1991 (Median) to Apr 2025, with 401 observations. The data reached an all-time high of 84.900 % in Jun 2021 and a record low of 0.600 % in Jun 2023. Inflation 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.

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.

DAX Index: Germany's Economic Pulse?

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

Germany SE: Construction: Improve data was reported at 39.100 % in Apr 2025. This records a decrease from the previous number of 51.500 % for Mar 2025. Germany SE: Construction: Improve data is updated monthly, averaging 21.400 % from Dec 1991 (Median) to Apr 2025, with 401 observations. The data reached an all-time high of 69.400 % in Mar 2016 and a record low of 0.000 % in Oct 2022. Germany SE: Construction: Improve 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.

Stock Market Expectation: Germany: Increase data was reported at 36.800 % in Apr 2025. This records an increase from the previous number of 33.800 % for Mar 2025. Stock Market Expectation: Germany: Increase data is updated monthly, averaging 57.000 % from Dec 1991 (Median) to Apr 2025, with 401 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.

Building contractors and developers depend on various socio-economic factors, including property values, underlying sentiment in the housing market, the degree of optimism among downstream businesses and credit conditions. All of these drivers typically track in line with economic sentiment, with recent economic shocks spurring a difficult period for building contractors and developers. Nonetheless, the enduring need for building services, particularly to tackle housing shortages across the continent, ensures a strong foundation of work. Revenue is forecast to grow at a compound annual rate of 2.3% to reach €1.3 trillion over the five years through 2025. Operational and supply chain disruption caused by the pandemic reversed the fortunes of building contractors and developers in 2020, as on-site activity tumbled and downstream clients either cancelled, froze or scaled back investment plans. Aided by the release of pent-up demand and supportive government policy, building construction output rebounded in 2021. Excess demand for key raw materials led to extended lead times during this period, while input costs recorded a further surge as a result of the effects of rapidly climbing energy prices following Russia’s invasion of Ukraine. Soaring construction costs and the impact of interest rate hikes on both the housing market and investor sentiment led to a renewed slowdown in building construction activity across the continent. However, falling inflation and the start of an interest rate cutting cycle have spurred signs of a recovery in new work volumes, supporting anticipated revenue growth of 2.3% in 2025. Revenue is forecast to increase at a compound annual rate of 6.7% to €1.7 trillion over the five years through 2030. Activity is set to remain sluggish in the medium term, as weak economic growth and uncertainty surrounding the impact of the volatile global tariff environment on inflation and borrowing costs continue to weigh on investor sentiment. Contractors and developers will increasingly rely on public sector support, including measures to boost the supply of new housing, as countries seek to tackle severe housing shortages. Meanwhile, the introduction of more stringent sustainability requirements will drive demand for energy retrofits.

Food-service contractors thrive on the need for convenient, efficient dining options driven by corporate clients, educational institutions and healthcare facilities. Businesses outsource these services to focus on core activities while ensuring quality food provision for employees, creating sustained demand and lucrative long-term contracts for specialist contract caterers. Industry revenue is expected to climb at a compound annual rate of 2.8% over the five years through 2025 to reach €66.8 billion, including a 0.9% hike in 2025. With expanding health and environmental consciousness across Europe, contract caterers are expanding their menus to offer healthier, organic meals. Moreover, as vegetarianism and veganism become more popular lifestyle choices, contract caterers are introducing a wider range of meat-free meals. Changing work arrangements have also impacted food-service contractors’ service offices. Hybrid working models have become popular, though more and more companies are asking employees to return to the office, driving attendance at canteens. The return of sports and leisure events alongside rebounding tourism following the lifting of COVID-19 restrictions also spurred revenue growth in 2022. However, prolonged economic uncertainty amid inflationary pressures, geopolitical tensions and recent trade war fears have subdued business sentiment and budgets, restricting spending on food caterers and profitability in the three years through 2025. Industry revenue is forecast to swell at a compound annual rate of 5% to €85.3 billion over the five years through 2030. Anticipated economic improvements will support business spending on contract caterers. As more companies outsource catering services, long-term contract opportunities will likely rise. Continually evolving consumer tastes will drive differentiation in the industry. The priority to provide healthy, sustainable and meat-free options is expanding, with consumers becoming more health-conscious and environmentally aware. Major caterers are adapting, offering innovative meals and investing in sustainability initiatives to attract clients.

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.

DAX Index: German Economic Barometer?

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.

DAX Index: A Mirror to German 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

Germany Short Term Interest Expectation: China: Increase data was reported at 7.800 % in Apr 2025. This records an increase from the previous number of 4.100 % for Mar 2025. Germany Short Term Interest Expectation: China: Increase data is updated monthly, averaging 12.400 % from Apr 2021 (Median) to Apr 2025, with 49 observations. The data reached an all-time high of 31.500 % in May 2022 and a record low of 0.000 % in Dec 2024. Germany Short Term Interest Expectation: China: 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.