Crude Oil fell to 65.07 USD/Bbl on June 27, 2025, down 0.26% from the previous day. Over the past month, Crude Oil's price has risen 5.22%, but it is still 20.20% 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.

Find out the latest prices of oil stocks, including Brent Crude Oil, WTI Crude Oil, ExxonMobil Corporation (XOM), Chevron Corporation (CVX), and British Petroleum (BP). Learn about the factors influencing oil stock prices such as global oil demand, OPEC production decisions, geopolitical events, and economic indicators. Understand the risks involved in investing in oil stocks and the importance of staying updated on market trends.

The CL symbol represents the US Crude Oil futures contract, which is traded on NYMEX and ICE. Learn about its importance, trading specifications, and how investors monitor its price.

Brent fell to 67.39 USD/Bbl on June 27, 2025, down 0.50% from the previous day. Over the past month, Brent's price has risen 4.77%, but it is still 20.72% 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 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.

Interactive daily chart of 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.

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.

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.

Interactive chart showing the daily closing price for West Texas Intermediate (NYMEX) Crude Oil over the last 10 years. The prices shown are in U.S. dollars.

Crude oil stock price forecast is a prediction of the future movement and value of stock prices in the crude oil industry. This article explains the methods used in forecasting, such as time series analysis, regression analysis, and machine learning, and emphasizes the importance of considering multiple forecast models and consulting with financial experts for more accurate predictions.

The price of crude oil per barrel is influenced by factors such as supply and demand, geopolitical events, and economic indicators. This article explores the fluctuations in crude oil prices, the impact on the global economy, and the role of benchmarks like Brent crude and WTI crude. It also discusses the historical volatility of oil prices, the influence of geopolitical tensions, economic indicators, market speculation, and the shale oil revolution. Understanding crude oil prices is crucial as they have si

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.

Crude Oil Price Forecasting

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 2025 annual OPEC oil price stood at ***** U.S. dollars per barrel, as of May. This would be lower than the 2024 average, which amounted to ***** U.S. dollars. The abbreviation OPEC stands for Organization of the Petroleum Exporting Countries and includes Algeria, Angola, Congo, Equatorial Guinea, Gabon, Iraq, Iran, Kuwait, Libya, Nigeria, Saudi Arabia, Venezuela, and the United Arab Emirates. The aim of the OPEC is to coordinate the oil policies of its member states. It was founded in 1960 in Baghdad, Iraq. The OPEC Reference Basket The OPEC crude oil price is defined by the price of the so-called OPEC (Reference) basket. This basket is an average of prices of the various petroleum blends that are produced by the OPEC members. Some of these oil blends are, for example: Saharan Blend from Algeria, Basra Light from Iraq, Arab Light from Saudi Arabia, BCF 17 from Venezuela, et cetera. By increasing and decreasing its oil production, OPEC tries to keep the price between a given maxima and minima. Benchmark crude oil The OPEC basket is one of the most important benchmarks for crude oil prices worldwide. Other significant benchmarks are UK Brent, West Texas Intermediate (WTI), and Dubai Crude (Fateh). Because there are many types and grades of oil, such benchmarks are indispensable for referencing them on the global oil market. The 2025 fall in prices was the result of weakened demand outlooks exacerbated by extensive U.S. trade tariffs.

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.

Crude Oil Futures: Experts Predict Volatility for S&P GSCI Crude Oil Index.

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.

Crude Oil Futures Show Bullish Outlook for S&P GSCI Crude Oil Index.

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

Urals Oil fell to 63.77 USD/Bbl on June 26, 2025, down 0.76% from the previous day. Over the past month, Urals Oil's price has risen 10.62%, but it is still 20.34% 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.

The latest closing stock price for Marathon Petroleum as of June 17, 2025 is 170.08. An investor who bought $1,000 worth of Marathon Petroleum stock at the IPO in 2011 would have $12,079 today, roughly 12 times their original investment - a 20.16% compound annual growth rate over 14 years. The all-time high Marathon Petroleum stock closing price was 213.36 on April 05, 2024. The Marathon Petroleum 52-week high stock price is 183.31, which is 7.8% above the current share price. The Marathon Petroleum 52-week low stock price is 115.10, which is 32.3% below the current share price. The average Marathon Petroleum stock price for the last 52 weeks is 155.18. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

The US crude oil stocks chart provides a visual representation of the levels of crude oil inventories in the United States. It is closely monitored by global oil markets as fluctuations in oil stocks can have a significant impact on oil prices. The chart is published by the US Energy Information Administration (EIA) and displays a time series of crude oil inventories. Traders, investors, and analysts use the chart to identify trends and patterns that could influence the oil market. It is an essential tool f

Short-term predictions indicate a cautiously optimistic outlook for S&P GSCI Crude Oil, with potential for moderate upside driven by a combination of supply constraints and rising global energy demand. However, risks to this prediction include geopolitical uncertainties, increased interest rates, and the potential for new COVID-19 variants to disrupt economic recovery and demand.