S&P Global Commodity Insights is the leading independent provider of information, benchmark prices, and analytics for the energy and commodities markets.

This dataset contains information about world's coal price from 1987. Data from BP. Follow datasource.kapsarc.org for timely data to advance energy economics research.Notes:- Source: IHS Northwest Europe prices for 1990-2000 are the average of the monthly marker, 2001-2016 the average of weekly prices. IHS Japan prices basis = 6,000 kilocalories per kilogram NAR CIF.- The Asian prices are the average of the monthly marker.- Chinese prices are the average monthly price for 2000-2005, weekly prices 2006 -2016, 5,500 kilocalories per kilogram NAR, including cost and freight (CFR)- Source: Platts. Prices are for CAPP 12,500 Btu, 1.2 SO2 coal, fob. - CAPP = Central Appalachian; cif = cost+insurance+freight (average prices); fob = free on board. &am

Polypropylene fell to 6,818 CNY/T on September 12, 2025, down 0.50% from the previous day. Over the past month, Polypropylene's price has fallen 3.81%, and is down 9.25% compared to the same time last year, 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 Polypropylene.

In July 2025, the average price of one barrel of Brent crude oil was 71.04 U.S. dollars. This was relatively unchanged from the previous month and 14 U.S. dollars below July 2024 prices. Brent terminology and most common uses Brent is the world's leading price benchmark for Atlantic basin crude oils. It is used to price two thirds of the internationally traded crude oil supplies and is also the most significant crude oil benchmark for Europe. Brent crude originates in the North Sea and includes oils from Brent and Forties Oil Field in the United Kingdom, and from the Oseborg and Ekofisk oil fields, both oil reserves in Norway. Other names for Brent are Brent Blend, London Brent and Brent petroleum. The name Brent comes from the Brent oil field, located north-east of the Shetland Islands, and thus part of the United Kingdom. Because the Brent oil field already passed its production peak, today the benchmark Brent includes oil from the other three major oil fields. Brent, next to West Texas Intermediate (WTI), is one of the lightest crude oils. With a low content of sulfur, it is ranged among the so-called sweet crude oils. Most of the Brent crude oil is refined into gasoline and middle distillates in Northwest Europe. Benchmark oil prices Other crucial benchmarks for crude oil prices are the already mentioned U.S.- WTI and Dubai Crude (Fateh). They are indispensable for referencing the many types and grades of oil on the global market. In the past 20 years, the annual price for one barrel of Brent crude oil saw a net increase. For example, the average price per barrel stood at 80.53 U.S. dollars in 2024.

Naphtha fell to 561.12 USD/T on September 11, 2025, down 0.70% from the previous day. Over the past month, Naphtha's price has risen 1.72%, but it is still 9.11% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Naphtha - values, historical data, forecasts and news - updated on September 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.

Leggett & Platt (LEG): Is It Time to Turn the Page?

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.

Leggett & Platt (LEG): Will Comfort and Convenience Lift Shares?

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

As of September 9, 2025, the price of one barrel of the Bonny Light crude oil in Nigeria stood at ***** U.S. dollars, which was a decrease of **** U.S dollar compared to the preceding week. Bonny Light crude oil is a high-grade crude oil produced in Nigeria that is known for its low sulfur content. A low sulfur content means low corrosive effects on the petroleum refinery infrastructure and a low environmental impact of the byproducts.

Iron Ore rose to 105.43 USD/T on September 12, 2025, up 0.24% from the previous day. Over the past month, Iron Ore's price has risen 3.33%, and is up 14.27% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Iron Ore - values, historical data, forecasts and news - updated on September of 2025.

Polyethylene fell to 7,194 CNY/T on September 11, 2025, down 0.15% from the previous day. Over the past month, Polyethylene's price has fallen 1.83%, and is down 11.17% compared to the same time last year, 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 Polyethylene.

Ethanol rose to 1.95 USD/Gal on September 11, 2025, up 2.37% from the previous day. Over the past month, Ethanol's price has risen 12.75%, and is up 14.41% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Ethanol - values, historical data, forecasts and news - updated on September of 2025.

HRC Steel fell to 804.08 USD/T on September 11, 2025, down 0.11% from the previous day. Over the past month, HRC Steel's price has fallen 3.59%, but it is still 15.20% higher 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 HRC Steel.

Browse LSEG's Commodities - Overview , discover our range of data, indices & benchmarks. Our Data Catalogue offers unrivaled data and delivery mechanisms.