Crude Oil fell to 65.98 USD/Bbl on June 24, 2025, down 3.70% from the previous day. Over the past month, Crude Oil's price has risen 8.36%, but it is still 18.37% lower than a year ago, 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 June of 2025.

Graph and download economic data for Producer Price Index by Commodity: Fuels and Related Products and Power: Lubricating Oil Base Stocks (WPU0578) from Jun 2009 to May 2025 about lubricants, stocks, fuels, oil, commodities, PPI, inflation, price index, indexes, price, and USA.

Brent fell to 68.02 USD/Bbl on June 24, 2025, down 4.84% from the previous day. Over the past month, Brent's price has risen 5.42%, but it is still 19.23% lower than a year ago, 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 June 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.

Heating Oil fell to 2.27 USD/Gal on June 24, 2025, down 0.28% from the previous day. Over the past month, Heating Oil's price has risen 8.56%, but it is still 9.44% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Heating oil - values, historical data, forecasts and news - updated on June of 2025.

Palm Oil fell to 4,120 MYR/T on June 24, 2025, down 0.12% from the previous day. Over the past month, Palm Oil's price has risen 7.60%, and is up 6.85% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Palm Oil - values, historical data, forecasts and news - updated on June of 2025.

Graph and download economic data for Refined Cottonseed Oil Stocks Owned by the Commodity Credit Corporation for United States (M0544BUSM438NNBR) from Jan 1952 to Nov 1955 about refined, cotton, fat, owned, inventories, credits, oil, corporate, commodities, 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.

S&P GSCI Crude Oil Index: A Reliable Gauge of Global Oil Prices?

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

On June 23, 2025, the Brent crude oil price stood at 70.98 U.S. dollars per barrel, compared to 68.51 U.S. dollars for WTI oil and 76.19 U.S. dollars for the OPEC basket. OPEC prices rose that week following expected supply constraints related to the Israel-Iran conflict.Europe's Brent crude oil, the U.S. WTI crude oil, and OPEC's basket are three of the most important benchmarks used by traders as reference for oil and gasoline prices. Lowest ever oil prices during coronavirus pandemic In 2020, the coronavirus pandemic resulted in crude oil prices hitting a major slump as oil demand drastically declined following lockdowns and travel restrictions. Initial outlooks and uncertainty surrounding the course of the pandemic brought about a disagreement between two of the largest oil producers, Russia and Saudi Arabia, in early March. Bilateral talks between global oil producers ended in agreement on April 13th, with promises to cut petroleum output and hopes rising that these might help stabilize the oil price in the coming weeks. However, with storage facilities and oil tankers quickly filling up, fears grew over where to store excess oil, leading to benchmark prices seeing record negative prices between April 20 and April 22, 2020. How crude oil prices are determined As with most commodities, crude oil prices are impacted by supply and demand, as well as inventories and market sentiment. However, as oil is most often traded in future contracts (whereby a contract is agreed upon, while the product delivery will follow in the next two to three months), market speculation is one of the principal determinants for oil prices. Traders make conclusions on how production output and consumer demand will likely develop over the coming months, leaving room for uncertainty. Spot prices differ from futures in so far as they reflect the current market price of a commodity.

Urals Oil fell to 72.18 USD/Bbl on June 23, 2025, down 0.08% from the previous day. Over the past month, Urals Oil's price has risen 25.20%, but it is still 9.56% lower than a year ago, 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 Urals Crude.

Interactive daily chart of Brent (Europe) crude oil prices over the last ten years. Values shown are daily closing prices.

Rapeseed fell to 487.27 EUR/T on June 24, 2025, down 2.51% from the previous day. Over the past month, Rapeseed's price has fallen 0.25%, but it is still 5.98% higher than a year ago, 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 Rapeseed Oil.

Oil futures stock price refers to the current or future price of oil contracts traded in the commodities market. Learn about the factors that influence oil prices and how investors and traders can make informed decisions in this volatile market.

China Stock: Deliverable: Shanghai Futures Exchange: Fuel Oil data was reported at 157,335.000 Ton in 09 May 2025. This stayed constant from the previous number of 157,335.000 Ton for 30 Apr 2025. China Stock: Deliverable: Shanghai Futures Exchange: Fuel Oil data is updated daily, averaging 157,335.000 Ton from Dec 2014 (Median) to 09 May 2025, with 516 observations. The data reached an all-time high of 519,490.000 Ton in 03 Jul 2020 and a record low of 0.000 Ton in 12 Oct 2018. China Stock: Deliverable: Shanghai Futures Exchange: Fuel Oil data remains active status in CEIC and is reported by Shanghai Futures Exchange. The data is categorized under China Premium Database’s Financial Market – Table CN.ZB: Shanghai Futures Exchange: Commodity Futures: Stock.

Sunflower Oil fell to 1,252.10 INR/10 kg on June 24, 2025, down 0.82% from the previous day. Over the past month, Sunflower Oil's price has fallen 4.21%, but it is still 34.46% higher than a year ago, 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 Sunflower Oil.

Learn about the stock ticker symbol for crude oil (CL) and how it is used to identify specific futures contracts for trading. Discover the origin of ticker symbols and the role they play in tracking and trading commodities like crude oil. Understand how investors and traders can profit from changes in oil prices by buying or selling crude oil futures contracts, but also be aware of the high level of risk involved in trading futures.

WTI (West Texas Intermediate) is a major benchmark for pricing crude oil globally, known for its high quality and low sulfur content. This article discusses the production, trading, and factors influencing the price of WTI oil, as well as the various financial instruments available for investing in this commodity. It emphasizes the need for careful monitoring, risk management, and diversification when considering investments in WTI oil.

Historical dataset of daily Brent (Europe) crude oil prices over the last ten years. Values shown are daily closing prices.

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.

DJ Commodity Heating Oil index Faces Uncertain Outlook

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.

DJ Commodity Heating Oil index: Analysts Predict Moderate Price Fluctuations

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