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.

Learn about crude oil share price charts and how they are used by traders, investors, and analysts to analyze historical price patterns, identify trends, and make predictions about future price movements. Understand the key elements of a crude oil share price chart and how they can help inform trading decisions.

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.

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

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.

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.

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

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 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

The US stock market and crude oil price are closely interconnected as crude oil is a critical component of the global economy, and its price fluctuations directly impact the stock market. This article explores the various factors that influence both the US stock market and crude oil prices, including geopolitical events, global economic conditions, supply and demand dynamics, and government policies.

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.

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.

Graph and download economic data for CBOE Crude Oil ETF Volatility Index (OVXCLS) from 2007-05-10 to 2025-06-25 about ETF, VIX, volatility, crude, oil, stock market, and USA.

The crude oil stock market allows individuals and institutional investors to trade and invest in companies involved in the exploration, production, refining, and distribution of crude oil. This article discusses the factors influencing crude oil stock performance, the different categories of crude oil stocks, and the risks associated with investing in this sector.

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

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

Brent crude oil is projected to have an average annual spot price of 65.85 U.S. dollars per barrel in 2025, according to a forecast from May 2025. This would mean a decrease of nearly 15 U.S. dollars compared to the previous year, and also reflects a reduced forecast WTI crude oil price. Lower economic activity, an increase in OPEC+ production output, and uncertainty over trade tariffs all impacted price forecasting. All about Brent Also known as Brent Blend, London Brent, and Brent petroleum, Brent Crude is a crude oil benchmark named after the exploration site in the North Sea's Brent oilfield. It is a sweet light crude oil but slightly heavier than West Texas Intermediate. In this context, sweet refers to a low sulfur content and light refers to a relatively low density when compared to other crude oil benchmarks. Price development in the 2020s Oil prices are volatile, impacted by consumer demand and discoveries of new oilfields, new extraction methods such as fracking, and production caps routinely placed by OPEC on its member states. The price for Brent crude oil stood at an average of just 42 U.S. dollars in 2020, when the coronavirus pandemic resulted in a sudden demand drop. Two years later, sanctions on Russian energy imports, had pushed up prices to a new decade-high, above 100 U.S. dollars per barrel.

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The crude oil market has the potential to grow by 4781.60 million barrels during 2021-2025, and the market’s growth momentum will decelerate at a CAGR of 2.73%.

This crude oil market research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches. Furthermore, this report extensively covers market segmentation by production area (onshore and offshore) and geography (APAC, North America, Europe, MEA, and South America). The report also offers information on several market vendors, including BP Plc, Chevron Corp., and ConocoPhillips Co., among others.

What will the Crude Oil Market Size be in 2021?

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Crude Oil Market: Key Drivers and Trends

Based on our research output, there has been a negative impact on the market growth during and post COVID-19 era. The increasing upstream investment is notably driving the crude oil market growth, although factors such as fluctuations in global crude oil prices may impede market growth. To unlock information on the key market drivers and the COVID-19 pandemic impact on the crude oil industry get your FREE report sample now.

      The rising energy demand across the world has prompted governments to explore untapped oil and gas resources in the upstream sector, using advanced technologies.
      The production of oil and natural gas is declining from many conventional oilfields. To overcome this issue, oil and gas operators are increasing investments in mature oil and gas fields.
      The adoption of unconventional exploration and production technologies in large shale deposits has widened opportunities for upstream oil and gas companies.
      The growing investments in the upstream oil and gas sector will significantly influence crude oil market growth over the forecast period.




      Technological development in the hydraulic fracturing process is aiding in the exploration and production of oil and gas from shale plays.
      The advances in the drilling technology and proppant placement in downhole wells increased hydrocarbon recovery from unconventional wells.
      Technological advances such as integration of the internet of things (IoT) for data acquisition, as well as the use of data analytics and machine learning, supports the efficiency of tools that is one of the key crude oil market trends.
      Real-time pressure data is crucial in crude oil production as it eliminates the over-fracturing issue.
      Automation of hydraulic fracturing optimizes the hydraulic fracturing method using algorithmic controls and supports enhanced well performance.

This crude oil market analysis report also provides detailed information on other upcoming trends and challenges that will have a far-reaching effect on the market growth. Get detailed insights on the trends and challenges, which will help companies evaluate and develop growth strategies.

Who are the Major Crude Oil Market Vendors?

The report analyzes the market’s competitive landscape and offers information on several market vendors, including:

BP Plc
Chevron Corp.
ConocoPhillips Co.
Exxon Mobil Corp.
PetroChina Co. Ltd.
Petroleo Brasileiro SA
Qatar Petroleum
Rosneft Oil Co.
Royal Dutch Shell Plc
Saudi Arabian Oil Co.

The crude oil market is fragmented and the vendors are deploying various organic and inorganic growth strategies to compete in the market. Click here to uncover other successful business strategies deployed by the vendors.

To make the most of the opportunities and recover from post COVID-19 impact, market vendors should focus more on the growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments.

Download a free sample of the crude oil market forecast report for insights on complete key vendor profiles. The profiles include information on the production, sustainability, and prospects of the leading companies.

Which are the Key Regions for Crude Oil Market?

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44% of the market’s growth will originate from APAC during the forecast period. China, India, and Japan are the key markets for crude oil in APAC. Market growth in this region will be faster than the growth of the market in Europe, North America, and South America.

To garner further competitive intelligence and regional opportunities in store for vendors, view our sample report.

What are the Revenue-generating Production Area Segments in the Crude Oil Market?

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The crude oil market share growth by the onshore segment will be significant during the forecast period. In onshore exploration and pr

On April 20th, 2020, the price of West Texas Intermediate crude oil slumped into negative for the first time in history, falling to negative 37.63 U.S. dollars per barrel. The ongoing coronavirus pandemic has had a catastrophic impact on the global oil and gas industry. Declining consumer demand and high levels of production output are threatening to exceed oil storage capacities, which resulted in the lowest ever oil prices noted between April 20th and April 22nd.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Fact and Figures page.