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.

United States Diffusion Index: Philadelphia Fed: sa: Inventories data was reported at 14.400 NA in Jul 2018. This records an increase from the previous number of 10.200 NA for Jun 2018. United States Diffusion Index: Philadelphia Fed: sa: Inventories data is updated monthly, averaging -5.300 NA from May 1968 (Median) to Jul 2018, with 603 observations. The data reached an all-time high of 27.900 NA in Mar 1973 and a record low of -51.000 NA in Mar 2009. United States Diffusion Index: Philadelphia Fed: sa: Inventories data remains active status in CEIC and is reported by Federal Reserve Bank of Philadelphia. The data is categorized under Global Database’s USA – Table US.S010: Third District Manufacturing Business Outlook Survey.

United States Diffusion Index: Philadelphia Fed: Prices Paid data was reported at 59.700 NA in Jul 2018. This records an increase from the previous number of 56.900 NA for Jun 2018. United States Diffusion Index: Philadelphia Fed: Prices Paid data is updated monthly, averaging 25.400 NA from May 1968 (Median) to Jul 2018, with 603 observations. The data reached an all-time high of 91.000 NA in Mar 1974 and a record low of -39.500 NA in Dec 2008. United States Diffusion Index: Philadelphia Fed: Prices Paid data remains active status in CEIC and is reported by Federal Reserve Bank of Philadelphia. The data is categorized under Global Database’s USA – Table US.S010: Third District Manufacturing Business Outlook Survey.

United States Diffusion Index: Philadelphia Fed: Number of Employees data was reported at 15.900 NA in Nov 2018. This records an increase from the previous number of 15.100 NA for Oct 2018. United States Diffusion Index: Philadelphia Fed: Number of Employees data is updated monthly, averaging 2.200 NA from May 1968 (Median) to Nov 2018, with 607 observations. The data reached an all-time high of 36.100 NA in May 2018 and a record low of -48.800 NA in Mar 2009. United States Diffusion Index: Philadelphia Fed: Number of Employees 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.S010: Third District Manufacturing Business Outlook Survey.

United States Diffusion Index: Philadelphia Fed: sa: General Business Conditions data was reported at 25.700 NA in Jul 2018. This records an increase from the previous number of 19.900 NA for Jun 2018. United States Diffusion Index: Philadelphia Fed: sa: General Business Conditions data is updated monthly, averaging 10.800 NA from May 1968 (Median) to Jul 2018, with 603 observations. The data reached an all-time high of 58.500 NA in Mar 1973 and a record low of -57.900 NA in Dec 1974. United States Diffusion Index: Philadelphia Fed: sa: General Business Conditions data remains active status in CEIC and is reported by Federal Reserve Bank of Philadelphia. The data is categorized under Global Database’s USA – Table US.S010: Third District Manufacturing Business Outlook Survey.

Graph and download economic data for Future Capital Expenditures; Diffusion Index for Federal Reserve District 3: Philadelphia (CEFDFSA066MSFRBPHI) from May 1968 to Jun 2025 about FRB PHI District, diffusion, capital, expenditures, indexes, and USA.

Graph and download economic data for Current General Activity, Perceptions of Respondents for the Region; Diffusion Index for Federal Reserve District 3: Philadelphia (GARBNDIF066MSFRBPHI) from Mar 2011 to Jun 2025 about FRB PHI District, diffusion, services, indexes, and USA.

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.

Philadelphia Gold and Silver Index: What's the Forecast?

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

United States Diffusion Index: Philadelphia Fed: sa: Prices Received data was reported at 36.300 NA in Jul 2018. This records an increase from the previous number of 33.200 NA for Jun 2018. United States Diffusion Index: Philadelphia Fed: sa: Prices Received data is updated monthly, averaging 8.400 NA from May 1968 (Median) to Jul 2018, with 603 observations. The data reached an all-time high of 63.800 NA in Feb 1974 and a record low of -40.900 NA in Apr 2009. United States Diffusion Index: Philadelphia Fed: sa: Prices Received data remains active status in CEIC and is reported by Federal Reserve Bank of Philadelphia. The data is categorized under Global Database’s USA – Table US.S010: Third District Manufacturing Business Outlook Survey.

Philly Fed CAPEX Index in the United States decreased to 14.50 points in June from 27 points in May of 2025. This dataset includes a chart with historical data for the United States Philly Fed CAPEX Index.

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.

Philadelphia Gold and Silver Index: What's Driving the Trends?

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.

Philadelphia Gold and Silver index: Analysts Bullish on Future Gains.

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

United States Diffusion Index: Philadelphia Fed: sa: Average Employee Workweek data was reported at 20.800 NA in Oct 2018. This records an increase from the previous number of 14.600 NA for Sep 2018. United States Diffusion Index: Philadelphia Fed: sa: Average Employee Workweek data is updated monthly, averaging 0.200 NA from May 1968 (Median) to Oct 2018, with 606 observations. The data reached an all-time high of 34.400 NA in May 2018 and a record low of -45.600 NA in Jun 1980. United States Diffusion Index: Philadelphia Fed: sa: Average Employee Workweek data remains active status in CEIC and is reported by Federal Reserve Bank of Philadelphia. The data is categorized under Global Database’s USA – Table US.S010: Third District Manufacturing Business Outlook Survey.

Philly Fed Business Conditions in the United States decreased to 18.30 points in June from 47.20 points in May of 2025. This dataset includes a chart with historical data for the United States Philly Fed Business Conditions.

United States Diffusion Index: Philadelphia Fed: sa: Delivery Times data was reported at 11.000 NA in Jul 2018. This records an increase from the previous number of 9.600 NA for Jun 2018. United States Diffusion Index: Philadelphia Fed: sa: Delivery Times data is updated monthly, averaging -2.500 NA from May 1968 (Median) to Jul 2018, with 603 observations. The data reached an all-time high of 20.700 NA in Apr 2018 and a record low of -33.800 NA in Jun 1980. United States Diffusion Index: Philadelphia Fed: sa: Delivery Times data remains active status in CEIC and is reported by Federal Reserve Bank of Philadelphia. The data is categorized under Global Database’s USA – Table US.S010: Third District Manufacturing Business Outlook Survey.

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.

Philadelphia Gold and Silver Index: The Future of Precious Metals?

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

Diffusion Index: Philadelphia Fed: sa: Next 6 Mth: Prices Paid data was reported at 59.700 NA in Jul 2018. This records a decrease from the previous number of 62.600 NA for Jun 2018. Diffusion Index: Philadelphia Fed: sa: Next 6 Mth: Prices Paid data is updated monthly, averaging 47.700 NA from May 1968 (Median) to Jul 2018, with 603 observations. The data reached an all-time high of 97.800 NA in May 1977 and a record low of -20.500 NA in Dec 2008. Diffusion Index: Philadelphia Fed: sa: Next 6 Mth: Prices Paid data remains active status in CEIC and is reported by Federal Reserve Bank of Philadelphia. The data is categorized under Global Database’s USA – Table US.S010: Third District Manufacturing Business Outlook Survey.

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.

Philadelphia Gold and Silver Index to See Bullish Momentum, Analysts Predict

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

Diffusion Index: Philadelphia Fed: sa: New Orders data was reported at 31.400 NA in Jul 2018. This records an increase from the previous number of 17.900 NA for Jun 2018. Diffusion Index: Philadelphia Fed: sa: New Orders data is updated monthly, averaging 11.900 NA from May 1968 (Median) to Jul 2018, with 603 observations. The data reached an all-time high of 56.200 NA in Mar 1973 and a record low of -53.600 NA in May 1980. Diffusion Index: Philadelphia Fed: sa: New Orders data remains active status in CEIC and is reported by Federal Reserve Bank of Philadelphia. The data is categorized under Global Database’s USA – Table US.S010: Third District Manufacturing Business Outlook Survey.

Philly Fed New Orders in the United States decreased to 2.30 points in June from 7.50 points in May of 2025. This dataset includes a chart with historical data for the United States Philly Fed New Orders.