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

Crude Oil rose to 65.49 USD/Bbl on July 23, 2025, up 0.27% from the previous day. Over the past month, Crude Oil's price has risen 1.73%, but it is still 15.60% 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 July of 2025.

On July 21, 2025, the Brent crude oil price stood at 68.98 U.S. dollars per barrel, compared to 67.2 U.S. dollars for WTI oil and 70.65 U.S. dollars for the OPEC basket. Brent and OPEC prices fell slightly that week, while WTI prices rose.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 (where a contract is agreed upon while 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.

Heating Oil fell to 2.45 USD/Gal on July 24, 2025, down 0.16% from the previous day. Over the past month, Heating Oil's price has risen 6.48%, but it is still 0.98% 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 July of 2025.

Understanding the relationship between the stock market and barrel oil price, and the factors that influence oil prices, can help investors make informed decisions. This article explores the impact of oil price changes on the stock market and the various factors that drive oil 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.

Oil Prices Reach New Highs as Global Demand Grows

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 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

According to a 2025 survey, oil producers operating in the Permian region needed WTI oil prices to amount to a minimum of ** U.S. dollars per barrel in order to profitably drill a new well. This compared to a minimum breakeven price of ** U.S. dollars per barrel for existing wells. The monthly average WTI oil price ranged between ** and ** U.S. dollars per barrel around the time of the survey. Most productive oil basins Operators in shale basins have the lowest average breakeven prices for new wells. However, when it comes to existing wells, operators in the Permian (Delaware) basin can afford even lower oil prices. The Permian basin, located in Texas and New Mexico, accounts for the greatest U.S. oil production output of any region. In 2024, production in the Permian reached nearly *********** barrels per day - more than **** times the amount extracted from the neighboring Eagle Ford rock formation. Texas is leading oil producing state With both regions located in Texas, it is not surprising that this is also the leading crude oil producing U.S. state. Nearly two billion barrels worth of crude oil were extracted in Texas per year, far more than any other state. Texas is home to a total of five major oil and gas formations.

Get the latest stock price and market updates for Crude Oil WTI. Stay informed about fluctuations in oil prices and make smart investment decisions.

A crude oil stock price graph shows the historical movement and fluctuations in the price of crude oil over a specific period. The graph represents the changes in the value of crude oil stocks, helping investors and analysts analyze trends and make predictions.

Snapshot img { margin: 10px !important; } The fuel oil market size will decrease by USD 84.77 billion during 2020-2024. This report provides a detailed analysis of the market by application (marine, industrial, and others) and geography (APAC, Europe, MEA, North America, and South America). Also, the report analyzes the market’s competitive landscape and offers information on several market vendors, including BP Plc, Chevron Corp., Exxon Mobil Corp., JXTG Holdings Inc., PJSC LUKOIL, PT Pertamina(Persero), Qatar Petroleum, Reliance Industries Ltd., Royal Dutch Shell Plc, and SK Innovation Co. Ltd.

Market Overview

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Market Competitive Analysis

The fuel oil market is fragmented with numerous vendors that produce and supply fuel oil to customers. Vendors need to make high capital investments to remain competitive in the market. BP Plc, Chevron Corp., and Exxon Mobil Corp. are some of the major market participants. Although the rise in world energy demand will offer immense growth opportunities, the fluctuations in crude oil prices will challenge the growth of the market participants. To make the most of the opportunities, market vendors should focus more on the growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments.

To help clients improve their market position, this fuel oil market forecast report provides a detailed analysis of the market leaders and offers information on the competencies and capacities of these companies. The report also covers details on the market’s competitive landscape and offers information on the products offered by various companies. Moreover, this fuel oil market analysis report also provides information on the upcoming trends and challenges that will influence market growth. This will help companies create strategies to make the most of future growth opportunities.

This report provides information on the production, sustainability, and prospects of several leading companies, including:

BP Plc
Chevron Corp.
Exxon Mobil Corp.
JXTG Holdings Inc.
PJSC LUKOIL
PT Pertamina(Persero)
Qatar Petroleum
Reliance Industries Ltd.
Royal Dutch Shell Plc
SK Innovation Co. Ltd.

Fuel Oil Market: Segmentation by Application

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The primary requirement of any marine engine is to propel the ship or generate onsite power by using the energy obtained from burning fuel oil. The mega marine engines of ships burn tons of fuel every day to propel the massively loaded ships. The rise in demand for bunker fuel oil due to the growing seaborne trade and growing naval activities will drive the demand for fuel oil for marine.

However, market growth in this segment will be slower than the growth of the market in the industrial and other segments. This report provides an accurate prediction of the contribution of all the segments to the growth of the fuel oil market size.

Fuel Oil Market: Segmentation by Geography

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North America will offer several growth opportunities to market vendors during the forecast period. The strong consumption of space heating fuel, growing refinery capacity, and proliferating marine trade will significantly influence fuel oil market growth in this region over the forecast period. The US is a key market for fuel oil in North America.

Fuel Oil Market: Key Drivers and Trends

The fluctuation in oil prices has affected the business of several oil and gas companies and refinancing companies. As a result, crude oil processing projects generate less revenue and many oil and gas companies suspend or postpone their exploration and production projects. Fluctuations in crude oil prices also impact investments in E&P and refining projects. Such factors will result in a slowdown in the growth of the global fuel oil market during the forecast period.

The adoption of blockchain in the oil and gas industry helps in overcoming several issues including the complexity of logistics, high fuel prices, and environmental pollution. Blockchain platforms facilitate secure and faster transactions between the entities and maintain transparency. Blockchain also helps in reducing cash cycle time and intermediary costs. These benefits will result in an increase in the adoption of blockchain to enhance the overall operational efficiency of the existing refineries. As a result of such factors, the fuel oil market will register a CAGR of (13)% during the forecast period.

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Fuel Oil Market: Key Highlights of the Report for 2020-2024

CAGR of the market

Learn about the complex relationship between crude oil prices and the DJIA (Dow Jones Industrial Average) and how they impact the economy and stock market. Understand the various factors that influence both indicators and how traders and investors analyze them to make investment decisions.

The price of oil per barrel is influenced by various factors such as supply and demand dynamics, geopolitical events, economic conditions, and market speculation. This article explores the impact of oil prices on the stock market, as well as its effects on different industries and the broader economy. Investors and traders closely monitor oil price movements to make informed investment decisions and capitalize on potential opportunities or mitigate risks in the market.

Brent rose to 68.87 USD/Bbl on July 23, 2025, up 0.41% from the previous day. Over the past month, Brent's price has risen 2.57%, but it is still 15.72% 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 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.

Oil Prices on the Rise as OPEC+ Deepens Output Cuts

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

Snapshot img

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

Learn about the role of the Energy Information Administration (EIA) in monitoring and reporting on WTI oil prices, including its weekly report on crude oil stocks and production levels, its monthly analysis of the energy sector, and its historical data on WTI oil prices. Discover how these reports and analysis are used by market participants to make informed decisions in the oil market.

A crude oil stock price chart is a graphical representation of the historical performance of a company's stock that relates to the production, exploration, or refining of crude oil. It provides investors and traders with a visual tool to analyze price trends, identify patterns, and make informed investment decisions.

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.

Oil Prices Soar on Debt Deal, But Rate Hikes Loom

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

Learn about the live crude oil stock price and its impact on global industries and the economy. Discover how the price is influenced by factors such as supply and demand dynamics, geopolitical events, and economic indicators. Find out how investors and traders use the live stock price to make informed decisions and the different types of crude oil that affect the price. Explore the technical indicators, market trends, and fundamental factors used to forecast the live crude oil stock price.