Crude Oil fell to 64.78 USD/Bbl on July 1, 2025, down 0.50% from the previous day. Over the past month, Crude Oil's price has risen 3.62%, but it is still 21.77% 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.

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.

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.

Learn how oil prices impact the stock market through the oil prices stock market chart. Discover the correlation between oil prices and stock market movements and gain insights for informed investment decisions.

Heating Oil fell to 2.24 USD/Gal on June 30, 2025, down 3.10% from the previous day. Over the past month, Heating Oil's price has risen 8.54%, but it is still 14.42% 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 June 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.

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.

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.

Brent fell to 66.38 USD/Bbl on July 1, 2025, down 0.53% from the previous day. Over the past month, Brent's price has risen 2.71%, but it is still 23.02% 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.

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.

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 article discusses the relationship between crude oil prices and the stock market, highlighting the impact of oil price fluctuations on various sectors of the economy. It explains how changes in oil prices can affect industries that heavily rely on oil and explores the factors influencing the crude oil market. The article also discusses the potential effects of oil price changes on stock prices and consumer spending. Additionally, it emphasizes the complexity of the relationship between crude oil prices

Context

Abstract of associated article: This paper contributes to the debate on the role of oil prices in predicting stock returns. The novelty of the paper is that it considers monthly time-series historical data that span over 150years (1859:10–2013:12) and applies a predictive regression model that accommodates three salient features of the data, namely, a persistent and endogenous oil price, and model heteroscedasticity. Three key findings are unraveled: first, oil price predicts US stock returns. Second, in-sample evidence is corroborated by out-sample evidence of predictability. Third, both positive and negative oil price changes are important predictors of US stock returns, with negative changes relatively more important. Our results are robust to the use of different estimators and choice of in-sample periods.

Acknowledgements

Narayan, Paresh K. (2016), “Data for: Has oil price predicted stock returns for over a century? ”, Mendeley Data, V1, doi: 10.17632/7s446mxhyv.1

License - CC by NC 3.0

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.

Motor Oil stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

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

Palm Oil rose to 3,993 MYR/T on July 1, 2025, up 0.15% from the previous day. Over the past month, Palm Oil's price has risen 2.97%, but it is still 2.37% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Palm 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.

Crude Conundrum: Where Will Oil Prices Head Next?

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

Graph and download economic data for No. 2 Heating Oil Prices: New York Harbor (WHOILNYH) from 1986-06-06 to 2025-06-13 about new york harbor, heating, New York, oil, commodities, and USA.

Heating Oil Stocks in the United States decreased to -716 Thousand Barrels in June 20 from 152 Thousand Barrels in the previous week. This dataset provides - United States Heating Oil Stocks - actual values, historical data, forecast, chart, statistics, economic calendar and news.