Natural gas fell to 3.39 USD/MMBtu on July 4, 2025, down 1.74% from the previous day. Over the past month, Natural gas's price has fallen 7.91%, but it is still 46.02% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Natural gas - values, historical data, forecasts and news - updated on July of 2025.

This statistic shows the stock prices of selected oil and gas commodities from January 2, 2020 to February 4, 2025. After the Russian invasion of Ukraine in February 2022, energy prices climbed significantly. The highest increase can be observed for natural gas, whose price peaked in August and September 2022. By the beginning of 2023, natural gas price started to decline.

Northwest Natural Gas stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Interactive chart illustrating the history of Henry Hub natural gas prices. The prices shown are in U.S. dollars.

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 Natural Gas the Future?

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

TTF Gas fell to 33.36 EUR/MWh on July 4, 2025, down 1.04% from the previous day. Over the past month, TTF Gas's price has fallen 8.96%, but it is still 1.05% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. EU Natural Gas TTF - values, historical data, forecasts and news - updated on July of 2025.

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 Natural Gas Futures x3 Short Leveraged Index Ignite a Price Drop?

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 Natural Gas Stocks: Mountain data was reported at 174.000 Cub ft bn in 16 Nov 2018. This records a decrease from the previous number of 181.000 Cub ft bn for 09 Nov 2018. United States Natural Gas Stocks: Mountain data is updated weekly, averaging 166.000 Cub ft bn from Jan 2010 (Median) to 16 Nov 2018, with 464 observations. The data reached an all-time high of 259.000 Cub ft bn in 18 Nov 2016 and a record low of 80.000 Cub ft bn in 18 Apr 2014. United States Natural Gas Stocks: Mountain data remains active status in CEIC and is reported by Energy Information Administration. The data is categorized under Global Database’s United States – Table US.RB015: Natural Gas Stocks. The data for weeks January 1, 2010 through June 12, 2015 are estimates derived by reallocating previously submitted respondent-level data and previous estimates for nonsampled respondents.

Working gas held in storage facilities in the United States increased by 55 billion cubic feet in the week ending June 27 of 2025 . This dataset provides the latest reported value for - United States Natural Gas Stocks Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset contains information on Natural Gas Stocks in Spain. Follow datasource.kapsarc.org for timely data to advance energy economics research.

Natural Gas Stocks Inventory in Romania increased to 18.59 TWh on Sunday June 29 from 18.43 in the previous day. This dataset includes data for Romania on Natural Gas Stocks Inventory expressed on TWh as reported by the Gas Infrastructure Europe.

This data is made up of daily stock prices and commodities' futures of a range of variables including NASDAQ clean focused price index, ARCA technology price index, Brent oil futures, Henry hub natural gas futures, Newcastle coal futures, carbon emission futures and green information technology stock price. The dataset supports empirical analysis which examines the volatility of clean energy stock returns (CERs) given the aggregate influence of energy security elements (ESEs) internal to CERs and the individuals influences of a range of exogenous variables including oil futures, natural gas futures, coal futures, carbon emission futures and green information technology stock price.

The global natural gas price index stood at 182.56 index points in May 2025. Natural gas prices decreased that month as heating fuel demand continued to fall. The global price index takes into account indices from Europe, Japan, and the United States – some of the largest natural gas trading markets. The U.S. is the leading natural gas exporter in the world. Means of trading natural gas Liquefied natural gas (LNG) is the most common form of trading natural gas. Although piped gas is often the preferred choice for transportation between neighboring producing and consuming countries, seaborne trade as LNG has grown in market volume. This is in part thanks to high consumption in pipeline-inaccessible areas such Japan, Korea, and China, as well as the recent increase in LNG trade by European countries. Major natural gas price benchmarks The natural gas prices often used as global benchmarks are Europe’s Dutch TTF traded on the Intercontinental Exchange, Indonesian LNG in Japan, and the U.S. Henry Hub traded on the New York Mercantile Exchange. 2022 was an especially volatile year for natural gas prices, as supply was severely constrained following sanctions on Russian imports. Other reasons for recent spikes in gas prices are related to issues at refineries, changes in demand, and problems along seaborne supply routes.

United States Stocks: Petroleum: NL: Natural Gas Liquids (NGL): Pipeline data was reported at 34,956.000 Barrel th in Apr 2018. This records an increase from the previous number of 34,644.000 Barrel th for Mar 2018. United States Stocks: Petroleum: NL: Natural Gas Liquids (NGL): Pipeline data is updated monthly, averaging 28,144.000 Barrel th from Jan 2010 (Median) to Apr 2018, with 100 observations. The data reached an all-time high of 34,956.000 Barrel th in Apr 2018 and a record low of 16,314.000 Barrel th in Mar 2010. United States Stocks: Petroleum: NL: Natural Gas Liquids (NGL): Pipeline data remains active status in CEIC and is reported by Energy Information Administration. The data is categorized under Global Database’s USA – Table US.RB031: Petroleum Stocks: by Type of Storage.

Northwest Natural Gas market cap as of June 28, 2025 is $1.73B. Northwest Natural Gas market cap history and chart from 2010 to 2025. Market capitalization (or market value) is the most commonly used method of measuring the size of a publicly traded company and is calculated by multiplying the current stock price by the number of shares outstanding.

This dataset is about stocks. It has 1 row and is filtered where the company is Shaanxi Provincial Natural Gas. It features 8 columns including stock name, company, exchange, and exchange symbol.

Dutch TTF gas futures amounted to **** euros per megawatt hour on June 30, 2025 for contracts with delivery in August 2025. Figures decreased compared to the previous week as Europe's stockpiles were rising. Dutch TTF is seen as a Europe-wide natural gas price benchmark. Europe more reliant on imports The Groningen gas field is the largest gas field in Europe and the major natural gas source in the Netherlands. In 2014, the first earthquake related to drilling the field occurred, and other seismic activities were also observed. Therefore, the Groningen field has drastically reduced its production output. Since then, natural gas production in the Netherlands has been in a trend of continuous decline. To balance the diminished domestic production, the European market relies on liquefied natural gas imports and pipeline inflow. LNG pricing across European regions The European gas market exhibits regional variations, as evidenced by LNG prices in different parts of the continent. The Southwest Europe LNG price is generally slightly higher than LNG prices in Northwest Europe. The latter reached around ** U.S. dollars per million British thermal units in late June 2025.

Natural Gas Stocks Inventory in Netherlands increased to 70.29 TWh on Thursday July 3 from 69.87 in the previous day. This dataset includes data for Netherlands on Natural Gas Stocks Inventory expressed on TWh as reported by the Gas Infrastructure Europe.

As of December 31, 2024, Spain's natural gas stocks in regasification terminals reached 8.3 terawatt-hours, down from approximately 14.7 terawatt-hours in the previous year. Meanwhile, stocks in underground storage amounted to over 29 terawatt-hours at the end of 2024, a year-on-year decrease of some 5.1 percent. During the period in consideration, natural gas stocks in Spain peaked in 2022, at a total of 50.5 terawatt-hours.

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.

Natural Gas Futures Triple Short Index: Will the Heat Be On?

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