The annual price of West Texas Intermediate (WTI) crude oil is expected to reach an average of 61.81 U.S. dollars per barrel in 2025, according to a May 2025 forecast. This would be a decrease of roughly 15 U.S. dollar compared to the previous year. In the first months weeks of 2025, weekly crude oil prices largely stayed below 70 U.S. dollars per barrel amid trade tariffs and expected economic downturn. What are benchmark crudes? WTI is often used as a price reference point called a benchmark (or ”marker”) crude. This category includes Brent crude from the North Sea, Dubai Crude, as well as blends in the OPEC reference basket. WTI, Brent, and the OPEC basket have tended to trade closely, but since 2011, Brent has been selling at a higher annual spot price than WTI, largely due to increased oil production in the United States. What causes price volatility? Oil prices are historically volatile. While mostly shaped by demand and supply like all consumer goods, they may also be affected by production limits, a change in U.S. dollar value, and to an extent by market speculation. In 2022, the annual average price for WTI was close to the peak of nearly 100 U.S. dollars recorded in 2008. In the latter year, multiple factors, such as strikes in Nigeria, an oil sale stop in Venezuela, and the continuous increase in oil demand from China were partly responsible for the price surge. Higher oil prices allowed the pursuit of extraction methods previously deemed too expensive and risky, such as shale gas and tight oil production in the U.S. The widespread practice of fracturing source rocks for oil and gas extraction led to the oil glut in 2016 and made the U.S. the largest oil producer in the world.

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.

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.

Explore the dynamic factors influencing Brent crude oil prices, including geopolitical tensions, supply-demand shifts, economic trends, and technological advancements. This comprehensive analysis highlights how these elements shape future price forecasts.

United States EIA Forecast: Crude Oil Price: Brent Spot Average data was reported at 71.000 USD/Barrel in Dec 2019. This stayed constant from the previous number of 71.000 USD/Barrel for Nov 2019. United States EIA Forecast: Crude Oil Price: Brent Spot Average data is updated monthly, averaging 62.750 USD/Barrel from Mar 2016 (Median) to Dec 2019, with 46 observations. The data reached an all-time high of 83.000 USD/Barrel in Oct 2018 and a record low of 34.000 USD/Barrel in Mar 2016. United States EIA Forecast: Crude Oil Price: Brent Spot Average data remains active status in CEIC and is reported by Energy Information Administration. The data is categorized under Global Database’s United States – Table US.P003: Energy Price: Forecast: Energy Information Administration.

The WTI oil forecast is a projection of the future price movement of West Texas Intermediate (WTI) crude oil. Traders, investors, and analysts closely monitor these forecasts to make informed decisions regarding oil-related investments and trading strategies. Factors such as supply and demand dynamics, geopolitical events, economic indicators, and weather conditions influence the WTI oil forecast. Different analysis methods including technical analysis, fundamental analysis, and sentiment analysis are used

United States EIA Forecast: Crude Oil Price: WTI Spot Average data was reported at 67.000 USD/Barrel in Dec 2019. This stayed constant from the previous number of 67.000 USD/Barrel for Nov 2019. United States EIA Forecast: Crude Oil Price: WTI Spot Average data is updated monthly, averaging 58.250 USD/Barrel from Mar 2016 (Median) to Dec 2019, with 46 observations. The data reached an all-time high of 74.000 USD/Barrel in Oct 2018 and a record low of 32.000 USD/Barrel in Mar 2016. United States EIA Forecast: Crude Oil Price: WTI Spot Average data remains active status in CEIC and is reported by Energy Information Administration. The data is categorized under Global Database’s United States – Table US.P003: Energy Price: Forecast: Energy Information Administration.

DoF Forecast: Brent Crude Oil Price data was reported at 68.300 USD/Barrel in 2023. This stayed constant from the previous number of 68.300 USD/Barrel for 2022. DoF Forecast: Brent Crude Oil Price data is updated yearly, averaging 72.400 USD/Barrel from Dec 2010 (Median) to 2023, with 14 observations. The data reached an all-time high of 111.900 USD/Barrel in 2012 and a record low of 44.000 USD/Barrel in 2016. DoF Forecast: Brent Crude Oil Price data remains active status in CEIC and is reported by Department of Finance. The data is categorized under Global Database’s Ireland – Table IE.P005: Brent Crude Oil Price: Forecast.

Goldman Sachs updates its Brent and WTI crude oil price forecasts, projecting significant declines by 2026 due to economic and geopolitical influences.

This dataset contains Oil price short term forecast, including STEO and historical from 2016-2022. Data from U.S. Energy Information Administration. Follow datasource.kapsarc.org for timely data to advance energy economics research.

Learn about the various factors that influence the forecast for WTI (West Texas Intermediate) crude oil, including geopolitical tensions, OPEC & non-OPEC production, economic outlook, supply and demand dynamics, crude oil inventories, environmental and renewable energy policies, and speculative trading. Understand the challenges of accurate forecasting and the importance of consulting a professional before making 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.

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

United Kingdom BOE Forecast: Brent Crude Oil Price data was reported at 71.000 USD/Barrel in 2021. This records a decrease from the previous number of 74.000 USD/Barrel for 2020. United Kingdom BOE Forecast: Brent Crude Oil Price data is updated yearly, averaging 72.500 USD/Barrel from Dec 2014 (Median) to 2021, with 8 observations. The data reached an all-time high of 81.000 USD/Barrel in 2018 and a record low of 43.000 USD/Barrel in 2015. United Kingdom BOE Forecast: Brent Crude Oil Price data remains active status in CEIC and is reported by Bank of England. The data is categorized under Global Database’s United Kingdom – Table UK.P009: Crude Oil and Gas Prices: Forecast.

This statistic displays a global forecast on oil prices by quarter in 2015, for UK Brent and West Texas Intermediate (WTI). In the first quarter of 2015, Brent oil prices is predicted to reach ** U.S. dollars per barrel.

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

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

Learn about the various factors influencing the forecast for Brent crude oil prices, including geopolitical tensions, supply and demand dynamics, and regulations affecting the oil industry. Understand how factors such as global oil demand, oil supply, geopolitical tensions, and market sentiment can impact the forecasted prices. Discover the importance of monitoring key factors and staying updated on global oil market dynamics for assessing the accuracy and reliability of the Brent crude oil price forecast.

BMF Forecast: Brent Oil Price data was reported at 71.000 USD/Barrel in 2027. This records a decrease from the previous number of 73.000 USD/Barrel for 2026. BMF Forecast: Brent Oil Price data is updated yearly, averaging 67.500 USD/Barrel from Dec 2016 (Median) to 2027, with 12 observations. The data reached an all-time high of 82.000 USD/Barrel in 2023 and a record low of 41.700 USD/Barrel in 2020. BMF Forecast: Brent Oil Price data remains active status in CEIC and is reported by Federal Ministry of Finance. The data is categorized under Global Database’s Austria – Table AT.P002: Brent Oil Price: Forecast.

SECO Forecast: Crude Oil Price: Brent data was reported at 66.500 USD/Barrel in 2020. This records an increase from the previous number of 64.600 USD/Barrel for 2019. SECO Forecast: Crude Oil Price: Brent data is updated yearly, averaging 66.500 USD/Barrel from Dec 2012 (Median) to 2020, with 9 observations. The data reached an all-time high of 112.000 USD/Barrel in 2012 and a record low of 43.300 USD/Barrel in 2016. SECO Forecast: Crude Oil Price: Brent data remains active status in CEIC and is reported by State Secretariat for Economic Affairs. The data is categorized under Global Database’s Switzerland – Table CH.P003: Crude Oil Price: Forecast.

BOP Forecast: Brent Oil Price data was reported at 58.000 EUR/Barrel in 2020. This records a decrease from the previous number of 62.100 EUR/Barrel for 2019. BOP Forecast: Brent Oil Price data is updated yearly, averaging 60.050 EUR/Barrel from Dec 2017 (Median) to 2020, with 4 observations. The data reached an all-time high of 62.200 EUR/Barrel in 2018 and a record low of 48.200 EUR/Barrel in 2017. BOP Forecast: Brent Oil Price data remains active status in CEIC and is reported by Bank of Portugal. The data is categorized under Global Database’s Portugal – Table PT.P001: Brent Crude Oil: Forecast.