Retail Sales Nowcast: sa: YoY: Contribution:(GDP) Gross Domestic ProductNowcast: Now-Casting Surprise Index: 3 Months: United States data was reported at 0.824 % in 12 May 2025. This stayed constant from the previous number of 0.824 % for 05 May 2025. Retail Sales Nowcast: sa: YoY: Contribution:(GDP) Gross Domestic ProductNowcast: Now-Casting Surprise Index: 3 Months: United States data is updated weekly, averaging 0.000 % from Feb 2020 (Median) to 12 May 2025, with 274 observations. The data reached an all-time high of 2.444 % in 28 Oct 2024 and a record low of 0.000 % in 14 Apr 2025. Retail Sales Nowcast: sa: YoY: Contribution:(GDP) Gross Domestic ProductNowcast: Now-Casting Surprise Index: 3 Months: United States 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: Retail Sales.

Industrial Production Nowcast: sa: YoY: Contribution: GDP Nowcast: Now-Casting Surprise Index: 2 Months: United States data was reported at 0.000 % in 12 May 2025. This stayed constant from the previous number of 0.000 % for 05 May 2025. Industrial Production Nowcast: sa: YoY: Contribution: GDP Nowcast: Now-Casting Surprise Index: 2 Months: United States data is updated weekly, averaging 0.000 % from Feb 2020 (Median) to 12 May 2025, with 273 observations. The data reached an all-time high of 22.016 % in 09 Nov 2020 and a record low of 0.000 % in 12 May 2025. Industrial Production Nowcast: sa: YoY: Contribution: GDP Nowcast: Now-Casting Surprise Index: 2 Months: United States 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: Industrial Production.

Economic Optimism Index In the Euro Area decreased to 94 points in June from 94.80 points in May of 2025. This dataset provides - Euro Area Economic Sentiment Indicator- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Economic Policy Uncertainty Index for United States (USEPUINDXD) from 1985-01-01 to 2025-07-10 about uncertainty, academic data, indexes, and USA.

Brazil IPCA: Inflation Surprise: Actual IPCA data was reported at 1.310 % in Feb 2025. This records an increase from the previous number of 0.160 % for Jan 2025. Brazil IPCA: Inflation Surprise: Actual IPCA data is updated monthly, averaging 0.360 % from Jun 2016 (Median) to Feb 2025, with 105 observations. The data reached an all-time high of 1.620 % in Mar 2022 and a record low of -0.680 % in Jul 2022. Brazil IPCA: Inflation Surprise: Actual IPCA data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Inflation – Table BR.IB010: Consumer Price Index: Broad Category - IPCA: Inflation Surprise.

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.

Shanghai Surprise: DJ Shanghai in Uncharted Waters?

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.

Nordstrom Defies Retail Headwinds with Surprise Profit

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

NY Empire State Manufacturing Index in the United States decreased to -16 points in June from -9.20 points in May of 2025. This dataset provides the latest reported value for - United States NY Empire State Manufacturing Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

IPCA: Inflation Surprise: Copom scenario data was reported at 1.170 % in Feb 2025. This records an increase from the previous number of -0.080 % for Jan 2025. IPCA: Inflation Surprise: Copom scenario data is updated monthly, averaging 0.360 % from Jun 2016 (Median) to Feb 2025, with 105 observations. The data reached an all-time high of 1.210 % in Apr 2022 and a record low of -0.210 % in Sep 2022. IPCA: Inflation Surprise: Copom scenario data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Inflation – Table BR.IB010: Consumer Price Index: Broad Category - IPCA: Inflation Surprise.

Brazil IPCA: Inflation Surprise: Surprise: Last 12 months data was reported at 0.330 % Point in Feb 2025. This records a decrease from the previous number of 0.440 % Point for Nov 2024. Brazil IPCA: Inflation Surprise: Surprise: Last 12 months data is updated quarterly, averaging -0.010 % Point from Aug 2016 (Median) to Feb 2025, with 35 observations. The data reached an all-time high of 1.520 % Point in Nov 2021 and a record low of -2.580 % Point in Aug 2022. Brazil IPCA: Inflation Surprise: Surprise: Last 12 months data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Inflation – Table BR.IB010: Consumer Price Index: Broad Category - IPCA: Inflation Surprise.

Leading Economic Index Brazil increased 0.20 percent in April of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Brazil Leading Economic Index - 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.

Sabine Royalty Trust: Dividend Surprise Awaits? (SBR)

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

Dow Jones Industrial Average: Prediction: Moderate growth, driven by strong corporate earnings and a positive economic outlook. Risk: A potential economic slowdown or geopolitical tensions could impact market performance. Shanghai Composite Index: Prediction: Continued volatility, with short-term fluctuations and potential for sustained upward momentum. Risk: Economic conditions in China, including policy changes and trade tensions, can influence market direction.

Brazil IPCA: Inflation Surprise: Surprise data was reported at 0.140 % Point in Feb 2025. This records a decrease from the previous number of 0.240 % Point for Jan 2025. Brazil IPCA: Inflation Surprise: Surprise data is updated monthly, averaging -0.030 % Point from Jun 2016 (Median) to Feb 2025, with 105 observations. The data reached an all-time high of 0.800 % Point in Oct 2021 and a record low of -1.520 % Point in Jul 2022. Brazil IPCA: Inflation Surprise: Surprise data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Inflation – Table BR.IB010: Consumer Price Index: Broad Category - IPCA: Inflation Surprise.

Philadelphia Fed Manufacturing Index in the United States remained unchanged at -4 points in June. This dataset provides the latest reported value for - United States Philadelphia Fed Manufacturing Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Brazil IPCA: Inflation Surprise: Copom Scenario: Last 12 months data was reported at 4.720 % in Feb 2025. This records an increase from the previous number of 4.430 % for Nov 2024. Brazil IPCA: Inflation Surprise: Copom Scenario: Last 12 months data is updated quarterly, averaging 4.230 % from Aug 2016 (Median) to Feb 2025, with 35 observations. The data reached an all-time high of 11.310 % in Aug 2022 and a record low of 2.450 % in Aug 2020. Brazil IPCA: Inflation Surprise: Copom Scenario: Last 12 months data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Inflation – Table BR.IB010: Consumer Price Index: Broad Category - IPCA: Inflation Surprise.

Brazil IPCA: Inflation Surprise: Actual IPCA: Last 12 months data was reported at 5.060 % in Feb 2025. This records an increase from the previous number of 4.870 % for Nov 2024. Brazil IPCA: Inflation Surprise: Actual IPCA: Last 12 months data is updated quarterly, averaging 4.500 % from Aug 2016 (Median) to Feb 2025, with 35 observations. The data reached an all-time high of 11.730 % in May 2022 and a record low of 1.880 % in May 2020. Brazil IPCA: Inflation Surprise: Actual IPCA: Last 12 months data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Inflation – Table BR.IB010: Consumer Price Index: Broad Category - IPCA: Inflation Surprise.

Highest magnitude correlations at top. Standard deviations and confidence intervals on are estimated by 10,000 bootstraps (random sampling with replacement). Not shown are the literary scores which did not yield statistically significant correlations with economic misery: WNA misery (Fiction books), WNA joy, WNA fear, WNA surprise, WNA anger, WNA sadness, LIWC anxiety, LIWC anger, LIWC affect, and LIWC positive emotions.

零售即时预测：SA：同比：贡献：GDP即时预测：即时预测惊喜指数：2个月：美国在05-12-2025达0.240%，相较于05-05-2025的0.240%保持不变。零售即时预测：SA：同比：贡献：GDP即时预测：即时预测惊喜指数：2个月：美国数据按周更新，02-17-2020至05-12-2025期间平均值为0.000%，共274份观测结果。该数据的历史最高值出现于02-15-2021，达17.116%，而历史最低值则出现于04-07-2025，为0.000%。CEIC提供的零售即时预测：SA：同比：贡献：GDP即时预测：即时预测惊喜指数：2个月：美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美国 – Table US.CEIC.NC: CEIC Nowcast: Retail Sales。

Inflation Surprise: IPCA: YoY: Copom Scenario在2025-02达4.720%，相较于2024-11的4.430%有所增长。Inflation Surprise: IPCA: YoY: Copom Scenario数据按季度更新，2016-08至2025-02期间平均值为4.230%，共35份观测结果。该数据的历史最高值出现于2022-08，达11.310%，而历史最低值则出现于2020-08，为2.450%。CEIC提供的Inflation Surprise: IPCA: YoY: Copom Scenario数据处于定期更新的状态，数据来源于Central Bank of Brazil，数据归类于Brazil Premium Database的Inflation – Table BR.IB010: Consumer Price Index: Broad Category - IPCA: Inflation Surprise。