Natural gas increased 0.21 USD/MMBtu or 5.84% since the beginning of 2025, 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 March 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.

This data package contains all the information related to the economy of a country including price index, commodities values and info about NASDAQ members.

TTF Gas decreased 8.92 EUR/MWh or 17.69% since the beginning of 2025, 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 March of 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 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.

Gasoline increased 0.22 USD/GAL or 10.89% since the beginning of 2025, 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 March 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.

Global Gas (HGAS): On the Rise or Just Hot Air?

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 relationship between oil prices and the stock market is complex and influenced by various factors. Rising oil prices can lead to increased costs for businesses and decreased consumer spending, impacting stock prices. Oil and gas companies' earnings directly depend on oil prices, which in turn affect the overall stock market. Geopolitical events and supply-demand dynamics also influence oil prices. Conversely, stock market fluctuations can indirectly affect oil prices by impacting investor sentiment

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 TR/CC CRB Unleaded Gas Index a Reliable Fuel 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

Brent decreased 0.64 USD/BBL or 0.85% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Brent crude oil - values, historical data, forecasts and news - updated on March 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 the Dow Jones U.S. Oil & Gas Index Poised for 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

Crude Oil decreased 2.12 USD/BBL or 2.95% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Crude Oil - values, historical data, forecasts and news - updated on March of 2025.

SEACOR Marine Holdings Inc.'s stock has demonstrated a positive trend in recent years, signaling potential for continued growth. However, investors should also consider the risks associated with the company's dependence on the offshore oil and gas industry, which may experience volatility. Monitor industry trends and the company's financial performance for potential opportunities and risks.

This table contains 25 series, with data for years 1956 - present (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Toronto Stock Exchange Statistics (25 items: Standard and Poor's/Toronto Stock Exchange Composite Index; high; Standard and Poor's/Toronto Stock Exchange Composite Index; close; Toronto Stock Exchange; oil and gas; closing quotations; Standard and Poor's/Toronto Stock Exchange Composite Index; low ...).

Coal decreased 28.50 USD/MT or 22.75% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Coal - values, historical data, forecasts and news - updated on March of 2025.

Eggs US decreased 2.89 USD/DOZEN or 49.69% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Eggs US.

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

Propane increased 0.10 USD/GAL or 13.33% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Propane - values, historical data, forecasts and news - updated on March of 2025.