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 fell to 66.61 USD/Bbl on July 3, 2025, down 1.24% from the previous day. Over the past month, Crude Oil's price has risen 5.99%, 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. Crude Oil - values, historical data, forecasts and news - updated on July of 2025.

The 2025 preliminary average annual price of West Texas Intermediate crude oil reached 68.24 U.S. dollars per barrel, as of May. This would be eight U.S. dollars below the 2024 average and the lowest annual average since 2021. WTI and other benchmarks WTI is a grade of crude oil also known as “Texas light sweet.” It is measured to have an API gravity of around 39.6 and specific gravity of about 0.83, which is considered “light” relative to other crude oils. This oil also contains roughly 0.24 percent sulfur, and is therefore named “sweet.” Crude oils are some of the most closely observed commodity prices in the world. WTI is the underlying commodity of the Chicago Mercantile Exchange’s oil futures contracts. The price of other crude oils, such as UK Brent crude oil, the OPEC crude oil basket, and Dubai Fateh oil, can be compared to that of WTI crude oil. Since 1976, the price of WTI crude oil has increased notably, rising from just 12.23 U.S. dollars per barrel in 1976 to a peak of 99.06 dollars per barrel in 2008. Geopolitical conflicts and their impact on oil prices The price of oil is controlled in part by limiting oil production. Prior to 1971, the Texas Railroad Commission controlled the price of oil by setting limits on production of U.S. oil. In 1971, the Texas Railroad Commission ceased limiting production, but OPEC, the Organization of Petroleum Exporting Countries with member states Iran, Iraq, Kuwait, Saudi Arabia, and Venezuela among others, continued to do so. In 1972, due to geopolitical conflict, OPEC set an oil embargo and cut oil production, causing prices to quadruple by 1974. Oil prices rose again in 1979 and 1980 due to the Iranian revolution, and doubled between 1978 and 1981 as the Iran-Iraq War prevented oil production. A number of geopolitical conflicts and periods of increased production and consumption have influenced the price of oil since then.

The West Texas Intermediate (WTI) is a benchmark crude oil primarily traded on the NYMEX. This article discusses the factors influencing WTI prices, including supply and demand dynamics, geopolitical events, economic indicators, and speculative trading.

Graph and download economic data for Spot Crude Oil Price: West Texas Intermediate (WTI) (WTISPLC) from Jan 1946 to Jun 2025 about WTI, crude, oil, price, and USA.

This dataset contains information about daily spot prices for crude oil WTI and Brent from 1986. data from US Energy Information AdministrationNotes:Citation: "Spot Prices For Crude Oil And Petroleum Products". Eia.gov. N.p., 2016. Web. 10 Mar. 2016.

W&T Offshore stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

The West Texas Intermediate (WTI) crude oil stock price is a key indicator of the global oil market. This article explores the factors affecting WTI crude oil stock price and its impact on various sectors of the global economy.

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

In May 2025, the price for one barrel of West Texas Intermediate (WTI) crude oil averaged 62.17 U.S. dollars. This was a decrease compared to the previous month and the lowest figure in the past 24-month period amid continued weak demand outlooks. WTI and other benchmark crudes WTI is also known as "Texas light sweet", and is a grade of crude oil used as a benchmark for oil produced in the United States. It has an API gravity of around 39.6 and specific gravity of about 0.827, which, relative to other crude oils, is considered “light,” hence the name. WTI also contains about 0.24 percent sulfur, making it a “sweet” crude oil. The price of WTI can be compared to the prices other of crude oils, i.e. UK Brent, the OPEC basket, and Dubai Fateh oil. WTI crude oil is the underlying commodity of the Chicago Mercantile Exchange’s oil futures contracts. U.S. oil production and its influence on light oil prices The price development of WTI crude oil relative to Brent crude oil has been influenced by variances in U.S. crude oil transportation and increased U.S. oil production. New transportation infrastructure became operational in early 2013, easing the movement of crude oil in the mid-continent and raising the price of WTI. Since then, U.S. refineries have increased production of crude oil to record levels, also raising the price of WTI. Meanwhile, expedited crude transport in the U.S. put downward pressure on Brent crude oil as domestic crude replaced some imported Brent crude. Between 2014 and 2016, UK Brent prices dropped rapidly, as was the case for all other crude oils.

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.

WTI Futures x3 Leveraged USD Index: The Next Big Play?

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.

WTI Futures Triple-Leveraged USD Index: A Volatile Ride?

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 dataset is about stocks per day. It has 376 rows and is filtered where the stock is WTI.L. It features 6 columns including stock, opening price, highest price, and lowest price.

Tracking and analyzing WTI oil prices is essential for individuals, businesses, and governments involved in the energy market. Oil prices impact various sectors, including transportation, manufacturing, and energy production. Learn about the factors that affect WTI oil prices and the importance of monitoring and interpreting them for investors and policymakers.

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.

WTI Futures x3 Leveraged USD Index 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

W&T Offshore reported $381.1M in Market Capitalization this April of 2024, considering the latest stock price and the number of outstanding shares.Data for W&T Offshore | WTI - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last July in 2025.

W&T Offshore market cap as of June 27, 2025 is $0.17B. W&T Offshore market cap history and chart from 2010 to 2025. Market capitalization (or market value) is the most commonly used method of measuring the size of a publicly traded company and is calculated by multiplying the current stock price by the number of shares outstanding.

The average spot price for West Texas Intermediate crude oil came to 76.63 U.S. dollars per barrel in 2024, a decrease of nearly one U.S. dollars compared to the previous year. The 2024 average spot price for Brent crude oil was 80.52 U.S. dollars. Both Brent and WTI are light crude oils, with the first used as a benchmark for gasoline prices around the world. Spot prices vs. future prices Spot prices refer to current market prices under which a commodity such as one barrel of crude oil may be bought for immediate delivery. In contrast, future prices refer to settlement and delivery at a later date. As a major refinery and storage hub, Cushing in Oklahoma is the delivery location for WTI traded via the New York Mercantile Exchange. When storage capacities threatened to reach their maximum capacity in April 2020, the WTI oil price crashed as a result, trading at record low prices. The WTI oil price fell into negative numbers for the first time in its history, closing out at negative 37.63 U.S. dollars per barrel on April 20th. The lowest value for Brent prices was 19.33 U.S. dollars per barrel. Influences on oil prices Oil prices are volatile commodities as their trading and delivery is heavily influenced by overall market development and geopolitical events. For example, the Russia-Ukraine war and resulting Russian sanctions brought about fears of supply bottlenecks, which pushed oil prices to decade-highs also reflected in the 2022 annual average.

The WTI price stock is a key benchmark used in the pricing of oil globally. This article explains the factors that influence the WTI stock price, including supply and demand dynamics, geopolitical events, production levels, economic growth rates, and financial market movements. It also highlights the significance of WTI stock prices in analyzing trends, making investment decisions, and managing risk in the crude oil industry.

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