Graph and download economic data for Unemployment Rate in New Orleans-Metairie, LA (MSA) (NEWO322UR) from Jan 1990 to Dec 2024 about New Orleans, LA, unemployment, rate, and USA.

Graph and download economic data for Unemployment Rate in Orleans Parish, LA (LAORLE0URN) from Jan 1990 to Apr 2025 about Orleans Parish, LA; New Orleans; LA; unemployment; rate; and USA.

Unemployment Rate in New Orleans-Metairie, LA (MSA) was 4.40% in December of 2024, according to the United States Federal Reserve. Historically, Unemployment Rate in New Orleans-Metairie, LA (MSA) reached a record high of 17.60 in April of 2020 and a record low of 3.50 in August of 2022. Trading Economics provides the current actual value, an historical data chart and related indicators for Unemployment Rate in New Orleans-Metairie, LA (MSA) - last updated from the United States Federal Reserve on July of 2025.

Graph and download economic data for Unemployment Rate in Jefferson Parish, LA (LAJEFF5URN) from Jan 1990 to Apr 2025 about Jefferson Parish, LA; New Orleans; LA; unemployment; rate; and USA.

Graph and download economic data for Unemployment Rate in St. Bernard Parish, LA (LASTBE5URN) from Jan 1990 to May 2025 about St. Bernard Parish, LA; New Orleans; LA; unemployment; rate; 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.

ENJ Entergy New Orleans LLC First Mortgage Bonds 5.0% Series due December 1 2052

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.

Entergy New Orleans 5.0% Bonds (ENJ) - A Stable Bet for Long-Term Investors?

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

Graph and download economic data for Unemployment Rate in St. Charles Parish, LA (LASTCH9URN) from Jan 1990 to May 2025 about St. Charles Parish, LA; New Orleans; LA; unemployment; rate; 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.

Entergy New Orleans (ENOstock) Bonds: A Steady Stream of Income

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

Graph and download economic data for Unemployment Rate in St. Bernard Parish, LA (LAUCN220870000000003A) from 1990 to 2024 about St. Bernard Parish, LA; New Orleans; LA; unemployment; rate; and USA.

Graph and download economic data for Unemployment Rate in Plaquemines Parish, LA (LAPLAQ5URN) from Jan 1990 to May 2025 about Plaquemines Parish, LA; New Orleans; LA; unemployment; rate; 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.

(ENOstock) Entergy New Orleans: A Reliable Powerhouse for Your Portfolio

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

Graph and download economic data for Unemployment Rate in St. John the Baptist Parish, LA (LASTJO5URN) from Jan 1990 to May 2025 about St. John The Baptist Parish, LA; New Orleans; LA; unemployment; rate; and USA.

Graph and download economic data for Unemployment Rate in St. Tammany Parish, LA (LASTTA0URN) from Jan 1990 to May 2025 about St. Tammany Parish, LA; New Orleans; LA; unemployment; rate; and USA.

Graph and download economic data for Unemployed Persons in New Orleans-Metairie, LA (MSA) (LAUMT223538000000004) from Jan 1990 to May 2025 about New Orleans, LA, household survey, unemployment, persons, and USA.

Graph and download economic data for Unemployed Persons in Orleans Parish, LA (LAUCN220710000000004) from Jan 1990 to May 2025 about Orleans Parish, LA; New Orleans; LA; household survey; unemployment; persons; and USA.

Graph and download economic data for Unemployment Rate in Orleans County, NY (NYORLE3URN) from Jan 1990 to Apr 2025 about Orleans County, NY; Rochester; NY; unemployment; rate; and USA.

Graph and download economic data for Unemployed Persons in Jefferson Parish, LA (LAUCN220510000000004) from Jan 1990 to May 2025 about Jefferson Parish, LA; New Orleans; LA; household survey; unemployment; persons; and USA.

Graph and download economic data for Unemployed Persons in St. Charles Parish, LA (LAUCN220890000000004) from Jan 1990 to May 2025 about St. Charles Parish, LA; New Orleans; LA; household survey; unemployment; persons; and USA.

Graph and download economic data for Unemployed Persons in St. Bernard Parish, LA (LAUCN220870000000004) from Jan 1990 to Apr 2025 about St. Bernard Parish, LA; New Orleans; LA; household survey; unemployment; persons; and USA.