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.

Natural gas fell to 3.39 USD/MMBtu on July 1, 2025, down 2.01% from the previous day. Over the past month, Natural gas's price has fallen 8.32%, but it is still 39.08% 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.

TTF Gas rose to 33.89 EUR/MWh on July 2, 2025, up 2.52% from the previous day. Over the past month, TTF Gas's price has fallen 6.05%, but it is still 3.40% 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.

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

UK Gas rose to 78.55 GBp/thm on July 1, 2025, up 1.15% from the previous day. Over the past month, UK Gas's price has fallen 3.39%, but it is still 0.43% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. UK Natural Gas - 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

In 2024, the price of natural gas in Europe reached 11 constant U.S. dollars per million British thermal units, compared with 2.2 U.S. dollars in the U.S. This was a notable decrease compared to the previous year, which had seen a steep increase in prices due to an energy supply shortage exacerbated by the Russia-Ukraine war. Since 1980, natural gas prices have typically been higher in Europe than in the United States and are expected to remain so for the coming two years. This is due to the U.S. being a significantly larger natural gas producer than Europe. What is natural gas and why is it gaining ground in the energy market? Natural gas is commonly burned in power plants with combustion turbines that generate electricity or used as a heating fuel. Given the fact that the world’s energy demand continues to grow, natural gas was seen by some industry leaders as an acceptable "bridge-fuel" to overcome the use of more emission-intensive energy sources such as coal. Subsequently, natural gas has become the main fuel for electricity generation in the U.S., while the global gas power generation share has reached over 22 percent. How domestic production shapes U.S. natural gas prices The combination of hydraulic fracturing (“fracking”) and horizontal drilling can be regarded as one of the oil and gas industry’s biggest breakthroughs in decades, with the U.S. being the largest beneficiary. This technology has helped the industry release unprecedented quantities of gas from deposits, mainly shale and tar sands that were previously thought either inaccessible or uneconomic. It is forecast that U.S. shale gas production could reach 36 trillion cubic feet in 2050, up from 1.77 trillion cubic feet in 2000.

Gasoline rose to 2.10 USD/Gal on July 1, 2025, up 1.85% from the previous day. Over the past month, Gasoline's price has risen 1.77%, but it is still 18.30% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gasoline - 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.

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

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.

Summer Road Trips Feeling the Burn as Gas Prices Soar

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

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.

The US oil stock market is a key component of the global energy sector and offers individuals and institutions the opportunity to participate in the growth and profitability of the oil and gas industry. This article explores the composition of the market, the influence of factors such as oil prices and government policies, and the emergence of renewable energy companies. It also highlights the risks associated with investing in oil stocks and advises investors to carefully analyze market conditions before m

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

The size of the North America Natural Gas Market was valued at USD XX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 5.00% during the forecast period. The North American natural gas market is exhibiting dynamic growth, not only owing to high domestic production coupled with rising consumption but also a growing trend toward cleaner sources of energy. Today, the United States is the world's largest producer of natural gas, largely because of the breakthrough in shale extraction technologies that have opened up vast reserves. This has resulted in the United States becoming the world's largest liquefied natural gas exporter. Most particularly, it makes use of incredibly high demand in markets such as Asia and Europe. Canada has considerable natural gas reserves, pipelines, and other infrastructure, supporting both the export of gas to the U.S. and international markets, besides providing domestic energy supply. ALCANICA: Canada is also focusing on the development of LNG export facilities to meet growing demand worldwide. As environmental concerns go up, natural gas becomes a bridge fuel-a source to help in the process of moving away from coal and supporting renewable integration. The issues affecting the market here include price volatility, regulatory barriers, and increased competition due to renewable energy. This should continue to be accompanied by growth in North America's natural gas market, as production capacity is strong, and investments being made in infrastructure are supported within a shifting energy mix that increasingly is suited for cleaner fuels. Recent developments include: In July 2022, Sempra Infrastructure signed an agreement with Mexico's Federal Electricity Commission to advance the joint development of critical energy infrastructure projects in Mexico, including the rerouting of the Guaymas-El Oro pipeline in Sonora, the proposed Vista Pacífico LNG project in Topolobampo, Sinaloa, and the potential development of a liquefied natural gas (LNG) terminal in Salina Cruz, Oaxaca.. Key drivers for this market are: 4., Growing Demand for Renewable Energy4.; Upcoming Investments in the Energy Sector and Supportive Renewable Energy Policies. Potential restraints include: 4., High Initial Investment Cost and Long Investment Return Period on Projects. Notable trends are: Power generation to Dominate the Market.

Dow Jones North America Select Junior Gas index is predicted to experience moderate growth with a positive outlook. However, risks associated with geopolitical instability, supply chain disruptions, and fluctuating commodity prices should be considered, as they could potentially impact the index's performance and lead to short-term volatility.

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 Short Leveraged Index 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

Predictions expect Helix stock to trend upwards due to increased demand and market share in the energy service industry. However, risks associated with volatility in oil and gas prices, competition, and operational hazards may impact its performance.

The global liquefied petroleum gas (LPG) market rose significantly to $199.9B in 2024, with an increase of 6.5% against the previous year. Over the period under review, consumption showed a modest expansion. Over the period under review, the global market hit record highs at $201.9B in 2022; however, from 2023 to 2024, consumption remained at a lower figure.

This statistic shows the stock price development of selected petroleum companies from January 2, 2020 to April 15, 2024. After the Russian invasion of Ukraine in February 2022, oil prices increased sharply in the first quarter of 2022 since many countries depend on Russian oil. Petroleum companies highly benefited from inclined oil prices, and saw significant increases in their share prices.

In 2019, the U.S. industrial gas market decreased by X% to $X, falling for the third consecutive year after two years of growth. In general, consumption recorded a perceptible increase. The pace of growth appeared the most rapid in 2016 with an increase of X% y-o-y. Over the period under review, the market reached the peak level in 2019 and is likely to see steady growth in the near future.