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 57.03 USD/Bbl on October 21, 2025, up 0.01% from the previous day. Over the past month, Crude Oil's price has fallen 8.43%, and is down 20.51% compared to the same time last year, 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 October of 2025.

Learn about crude oil stock indices, how they track and measure the performance of crude oil related stocks, and their importance in the financial markets.

Graph and download economic data for CBOE Crude Oil ETF Volatility Index (OVXCLS) from 2007-05-10 to 2025-10-17 about ETF, VIX, volatility, crude, stock market, oil, and USA.

Stocks of crude oil in the United States decreased by 0.96million barrels in the week ending October 17 of 2025. This dataset provides the latest reported value for - United States Crude Oil Stocks Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Short-term predictions indicate a cautiously optimistic outlook for S&P GSCI Crude Oil, with potential for moderate upside driven by a combination of supply constraints and rising global energy demand. However, risks to this prediction include geopolitical uncertainties, increased interest rates, and the potential for new COVID-19 variants to disrupt economic recovery and demand.

Graph and download economic data for Producer Price Index by Commodity: Fuels and Related Products and Power: Lubricating Oil Base Stocks (WPU0578) from Jun 2009 to Aug 2025 about lubricants, stocks, fuels, oil, commodities, PPI, inflation, price index, indexes, price, and USA.

Brent rose to 62.69 USD/Bbl on October 22, 2025, up 2.24% from the previous day. Over the past month, Brent's price has fallen 7.30%, and is down 16.37% compared to the same time last year, 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 October of 2025.

Iran Index: TSE: Oil and Gas Extraction and Related Services excl Surveying data was reported at 339.200 21Mar1998=100 in May 2018. This records a decrease from the previous number of 360.100 21Mar1998=100 for Apr 2018. Iran Index: TSE: Oil and Gas Extraction and Related Services excl Surveying data is updated monthly, averaging 437.100 21Mar1998=100 from Jul 2009 (Median) to May 2018, with 107 observations. The data reached an all-time high of 1,051.400 21Mar1998=100 in Jan 2014 and a record low of 115.800 21Mar1998=100 in Jul 2009. Iran Index: TSE: Oil and Gas Extraction and Related Services excl Surveying data remains active status in CEIC and is reported by Tehran Stock Exchange. The data is categorized under Global Database’s Iran – Table IR.Z001: Tehran Stock Exchange: Index.

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 Indicator of Global Energy Markets?

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

Israel Index: TASE: Sector: Oil and Gas Exploration data was reported at 1,555.270 01Jan1984=95.27 in Sep 2018. This records an increase from the previous number of 1,398.600 01Jan1984=95.27 for Aug 2018. Israel Index: TASE: Sector: Oil and Gas Exploration data is updated monthly, averaging 476.960 01Jan1984=95.27 from Jan 2000 (Median) to Sep 2018, with 225 observations. The data reached an all-time high of 1,966.460 01Jan1984=95.27 in Sep 2014 and a record low of 78.500 01Jan1984=95.27 in Oct 2002. Israel Index: TASE: Sector: Oil and Gas Exploration data remains active status in CEIC and is reported by Tel Aviv Stock Exchange. The data is categorized under Global Database’s Israel – Table IL.Z001: Tel Aviv Stock Exchange: Index.

The Dow Jones North America Select Junior Oil index may exhibit upward momentum, potentially reaching slightly higher levels. However, it's important to note that this prediction carries moderate risk due to potential market fluctuations and geopolitical uncertainties that could influence the oil industry.

Abstract of associated article: Using a binomial probability distribution model this paper creates an endurance index of oil service investor sentiment. The index reflects the probability of the high or low stock price being the close price for the PHLX Oil Service Sector Index. Results of this study reveal the substantial forecasting ability of the sentiment endurance index. Monthly and quarterly rolling forecasts of returns of oil service stocks have an overall accuracy as high as 52% to 57%. In addition, the index shows decent forecasting ability on changes in crude oil prices, especially, WTI prices. The accuracy of 6-quarter rolling forecasts is 55%. The sentiment endurance index, along with the procedure of true forecasting and accuracy ratio, applied in this study provides investors and analysts of oil service sector stocks and crude oil prices as well as energy policy-makers with effective analytical tools.

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

Graph and download economic data for Producer Price Index by Industry: Petroleum Refineries: Unfinished Oils and Lubricating Oil Base Stock (PCU324110324110J) from Jun 1985 to Aug 2025 about refineries, lubricants, petroleum, stocks, oil, PPI, industry, inflation, price index, indexes, price, and USA.

Italy Index: Oil & Gas data was reported at 16,516.388 19Dec2008=20000 in Nov 2018. This records a decrease from the previous number of 17,812.396 19Dec2008=20000 for Oct 2018. Italy Index: Oil & Gas data is updated monthly, averaging 20,175.802 19Dec2008=20000 from Dec 2008 (Median) to Nov 2018, with 120 observations. The data reached an all-time high of 24,325.880 19Dec2008=20000 in Apr 2011 and a record low of 14,507.375 19Dec2008=20000 in Sep 2016. Italy Index: Oil & Gas data remains active status in CEIC and is reported by Italian Stock Exchange. The data is categorized under Global Database’s Italy – Table IT.Z001: Stock Exchange Index.

View monthly updates and historical trends for Olive Oil Price. Source: International Monetary Fund. Track economic data with YCharts analytics.

The US_Stock_Data.csv dataset offers a comprehensive view of the US stock market and related financial instruments, spanning from January 2, 2020, to February 2, 2024. This dataset includes 39 columns, covering a broad spectrum of financial data points such as prices and volumes of major stocks, indices, commodities, and cryptocurrencies. The data is presented in a structured CSV file format, making it easily accessible and usable for various financial analyses, market research, and predictive modeling. This dataset is ideal for anyone looking to gain insights into the trends and movements within the US financial markets during this period, including the impact of major global events.

Key Features and Data Structure

The dataset captures daily financial data across multiple assets, providing a well-rounded perspective of market dynamics. Key features include:

• Commodities: Prices and trading volumes for natural gas, crude oil, copper, platinum, silver, and gold.
• Cryptocurrencies: Prices and volumes for Bitcoin and Ethereum, including detailed 5-minute interval data for Bitcoin.
• Stock Market Indices: Data for major indices such as the S&P 500 and Nasdaq 100.
• Individual Stocks: Prices and volumes for major companies including Apple, Tesla, Microsoft, Google, Nvidia, Berkshire Hathaway, Netflix, Amazon, and Meta.

The dataset’s structure is designed for straightforward integration into various analytical tools and platforms. Each column is dedicated to a specific asset's daily price or volume, enabling users to perform a wide range of analyses, from simple trend observations to complex predictive models. The inclusion of intraday data for Bitcoin provides a detailed view of market movements.

Applications and Usability

This dataset is highly versatile and can be utilized for various financial research purposes:

• Market Analysis: Track the performance of key assets, compare volatility, and study correlations between different financial instruments.
• Risk Assessment: Analyze the impact of commodity price movements on related stock prices and evaluate market risks.
• Educational Use: Serve as a resource for teaching market trends, asset correlation, and the effects of global events on financial markets.

The dataset’s daily updates ensure that users have access to the most current data, which is crucial for real-time analysis and decision-making. Whether for academic research, market analysis, or financial modeling, the US_Stock_Data.csv dataset provides a valuable foundation for exploring the complexities of financial markets over the specified period.

Acknowledgements:

This dataset would not be possible without the contributions of Dhaval Patel, who initially curated the US stock market data spanning from 2020 to 2024. Full credit goes to Dhaval Patel for creating and maintaining the dataset. You can find the original dataset here: US Stock Market 2020 to 2024.

Index Time Series for DWCOGS: Dow Jones U.S. Oil & Gas Tota. The frequency of the observation is daily. Moving average series are also typically included.

New York Stock Exchange: Index: Dow Jones US Oil & Gas Index data was reported at 675.620 NA in Apr 2025. This records a decrease from the previous number of 780.190 NA for Mar 2025. New York Stock Exchange: Index: Dow Jones US Oil & Gas Index data is updated monthly, averaging 594.840 NA from Aug 2013 (Median) to Apr 2025, with 141 observations. The data reached an all-time high of 846.020 NA in Jun 2014 and a record low of 239.560 NA in Mar 2020. New York Stock Exchange: Index: Dow Jones US Oil & Gas Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: New York Stock Exchange: Dow Jones: Monthly.