FRBOP Forecast: Core CPI Inflation: sa: Mean: Plus 1 Qtr data was reported at 2.226 % in Mar 2019. This records a decrease from the previous number of 2.327 % for Dec 2018. FRBOP Forecast: Core CPI Inflation: sa: Mean: Plus 1 Qtr data is updated quarterly, averaging 1.951 % from Mar 2007 (Median) to Mar 2019, with 49 observations. The data reached an all-time high of 2.365 % in Jun 2018 and a record low of 1.127 % in Mar 2009. FRBOP Forecast: Core CPI Inflation: sa: Mean: Plus 1 Qtr data remains active status in CEIC and is reported by Federal Reserve Bank of Philadelphia. The data is categorized under Global Database’s United States – Table US.I008: Consumer Price Index: Urban: sa: Forecast: Federal Reserve Bank of Philadelphia.

Euro Area's main stock market index, the EU50, rose to 5703 points on October 27, 2025, gaining 0.49% from the previous session. Over the past month, the index has climbed 3.55% and is up 14.74% 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 October of 2025.

Consumer Price Index data was reported at 1.340 Index, 2017 in 2026. This records an increase from the previous number of 1.310 Index, 2017 for 2025. Consumer Price Index data is updated yearly, averaging 0.589 Index, 2017 from Dec 1960 (Median) to 2026, with 67 observations. The data reached an all-time high of 1.340 Index, 2017 in 2026 and a record low of 0.121 Index, 2017 in 1960. Consumer Price Index data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.EO: Consumer and Wholesale Price Index: Forecast: OECD Member: Annual. CPI-Consumer price indexIndex, national reference year

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.

Will the AEX Index Soar to New Heights?

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

Based on professional technical analysis and AI models, deliver precise price‑prediction data for Solana Stock Index on 2025-10-28. Includes multi‑scenario analysis (bullish, baseline, bearish), risk assessment, technical‑indicator insights and market‑trend forecasts to help investors make informed trading decisions and craft sound investment strategies.

OMXS30 index may experience moderate volatility in the near term. Bullish momentum could push the index higher, driven by positive economic data and favorable market sentiment. However, potential headwinds, such as geopolitical uncertainties or macroeconomic risks, could limit gains and lead to periods of consolidation. Overall, the risk remains moderate due to the potential for both upside and downside movements.

CZ: Consumer Price Index: Double Hit Scenario data was reported at 1.215 Index, 2010 in 2021. This records an increase from the previous number of 1.199 Index, 2010 for 2020. CZ: Consumer Price Index: Double Hit Scenario data is updated yearly, averaging 0.917 Index, 2010 from Dec 1993 (Median) to 2021, with 29 observations. The data reached an all-time high of 1.215 Index, 2010 in 2021 and a record low of 0.468 Index, 2010 in 1993. CZ: Consumer Price Index: Double Hit Scenario data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Czech Republic – Table CZ.OECD.EO: Consumer and Wholesale Price Index: Forecast: OECD Member: Annual. CPI-Consumer price indexIndex, national reference year

The Global Forecast System (GFS) CPEX dataset includes model data simulated by the Global Forecast System (GFS) model for the Convective Process Experiment (CPEX) field campaign. The NASA Convective Processes Experiment (CPEX) aircraft field campaign took place in the North Atlantic-Gulf of America-Caribbean Sea region from 25 May-25 June 2017. CPEX conducted a total of sixteen DC-8 missions from 27 May-24 June. The CPEX campaign collected data to help explain convective storm initiation, organization, growth, and dissipation in the North Atlantic-Gulf of America-Caribbean Oceanic region during the early summer of 2017. These data are available from May 24, 2017 through July 20, 2017 and are available in netCDF-3 format.

Terrorism Index in Cuba remained unchanged at 0 Points in 2023 from 0 Points in 2022. Cuba Terrorism Index - values, historical data, forecasts and news - updated on October of 2025.

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

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.

Is the Dow Jones North America Select Junior Gas Index a Reliable Gauge of Energy Growth?

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 global Melt Flow Index Tester market is projected to reach a valuation of USD 1.2 billion by 2033, growing at a compound annual growth rate (CAGR) of 5.8% from 2025 to 2033.

India's main stock market index, the SENSEX, rose to 84779 points on October 27, 2025, gaining 0.67% from the previous session. Over the past month, the index has climbed 5.49% and is up 5.97% 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 October of 2025.

This dataset contains the predicted prices of Metaverse Index for the upcoming years based on user-defined projections.

Terrorism Index in Moldova remained unchanged at 0 Points in 2024 from 0 Points in 2023. Moldova Terrorism Index - values, historical data, forecasts and news - updated on October of 2025.

Structural steel (FOB India) prices fell YoY in late 2023. From Oct ($598) to Dec ($515), consistent ~11-12% monthly drops were observed.

Economic Optimism Index in South Korea increased to 92.30 points in September from 91.70 points in August of 2025. This dataset provides - South Korea Economic Optimism Index- actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset contains the predicted prices of CT100 INDEX for the upcoming years based on user-defined projections.

Based on professional technical analysis and AI models, deliver precise price‑prediction data for Index Cooperative on 2025-11-13. Includes multi‑scenario analysis (bullish, baseline, bearish), risk assessment, technical‑indicator insights and market‑trend forecasts to help investors make informed trading decisions and craft sound investment strategies.

This dataset contains the predicted prices of the asset The Clanker Index over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.