GSCI fell to 556.57 Index Points on December 2, 2025, down 0.34% from the previous day. Over the past month, GSCI's price has fallen 0.80%, but it is still 3.06% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. GSCI Commodity Index - values, historical data, forecasts and news - updated on December of 2025.

Graph and download economic data for Global Price Index of All Commodities (PALLFNFINDEXQ) from Q1 2003 to Q2 2025 about World, commodities, price index, indexes, and price.

CRB Index rose to 378.33 Index Points on December 1, 2025, up 0.45% from the previous day. Over the past month, CRB Index's price has fallen 0.80%, but it is still 10.95% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. CRB Commodity Index - values, historical data, forecasts and news - updated on December of 2025.

Historical commodity (daily) price from 2000-2022 (March). 1. Gold 2. Palladium 3. Nickel 4. Brent Oil 5. Natural Gas 6. Wheat

• cover image credit: https://www.pexels.com/photo/industrial-machine-during-golden-hour-162568/

Corn rose to 433.53 USd/BU on December 2, 2025, up 0.01% from the previous day. Over the past month, Corn's price has fallen 0.17%, but it is still 2.43% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Corn - values, historical data, forecasts and news - updated on December of 2025.

Gold fell to 4,199.97 USD/t.oz on December 2, 2025, down 0.75% from the previous day. Over the past month, Gold's price has risen 4.93%, and is up 58.92% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gold - values, historical data, forecasts and news - updated on December of 2025.

This dataset contains historical daily closing prices for significant natural resource futures contracts. It includes comprehensive data covering a range of key commodities such as Crude Oil (WTI and Brent), Gold, Silver, Natural Gas, Corn, Wheat, Soybean, Copper, Platinum, and Palladium.

The dataset provided is particularly suitable for a variety of analytical and predictive purposes, including:

Market trend analysis and visualization to understand price fluctuations and long-term cycles.

Economic research to assess the impact of economic events, policy changes, or supply-demand dynamics on commodity prices.

Building forecasting models, including machine learning and time series predictive analytics, to predict future price movements.

Portfolio optimization and risk management by analyzing commodity correlations and volatility.

Educational purposes, offering practical datasets for training students in economics, finance, statistics, and data science courses.

Due to the nature of historical data collection, certain entries may be missing. For example, there is an instance where an entire month of Platinum price data is absent. Such missing data points can typically be handled effectively by imputing values—calculating an average between the last known entry and the subsequent available entry—without negatively impacting the integrity of analytical studies.

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.

Graph and download economic data for Producer Price Index by Commodity: Farm Products: Breaker Stock and Checks and Undergrades (WPU017108) from Dec 1991 to Aug 2025 about checkable, stocks, agriculture, commodities, PPI, inflation, price index, indexes, price, and USA.

Time series data for the commodity Primary Commodity Prices, Coffee index . Indicator Definition:Primary Commodity Prices, Coffee index The indicator "Primary Commodity Prices, Coffee index " stands at 223.80 as of 8/31/2025. Regarding the One-Year-Change of the series, the current value constitutes an increase of 11.39 percent compared to the value the year prior.The 1 year change in percent is 11.39.The 3 year change in percent is 55.61.The 5 year change in percent is 146.61.The 10 year change in percent is 132.43.The Serie's long term average value is 93.49. It's latest available value, on 8/31/2025, is 139.38 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 10/31/2001, to it's latest available value, on 8/31/2025, is +638.31%.The Serie's change in percent from it's maximum value, on 2/28/2025, to it's latest available value, on 8/31/2025, is -18.14%.

This statistic shows the stock prices of selected food commodities from January 2, 2020 to February 6, 2025. After the Russian invasion of Ukraine in February 2022, wheat prices increased significantly since both Russia and Ukraine are the key suppliers of the product. With the beginning of 2023, prices of selected food commodities started to decrease, but still stood higher than early-2020 levels.

Time series data for the commodity Primary Commodity Prices, Legumes, Chickpea. Indicator Definition:Primary Commodity Prices, Legumes, ChickpeaThe indicator "Primary Commodity Prices, Legumes, Chickpea" stands at 69.52 as of 08/31/2025. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -21.67 percent compared to the value the year prior.The 1 year change in percent is -21.67.The 3 year change in percent is 15.89.The 5 year change in percent is 13.91.The 10 year change in percent is -3.35.The Serie's long term average value is 64.55. It's latest available value, on 08/31/2025, is 7.71 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 03/31/2009, to it's latest available value, on 08/31/2025, is +66.53%.The Serie's change in percent from it's maximum value, on 10/31/2016, to it's latest available value, on 08/31/2025, is -55.84%.

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

Iron Ore rose to 106.94 USD/T on December 1, 2025, up 2.00% from the previous day. Over the past month, Iron Ore's price has risen 1.04%, and is up 1.54% 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 December of 2025.

Tradefeeds Commodity Prices API enables you to get commodity prices data of the major commodity asset types like energy commodities, metals, industrial commodities, agricultural commodities and livestock commodities. Each commodity asset type has a different historical coverage. A commodity within its commodity asset type has not the same historical coverage as another commodity from the group. For example, within the group of energy commodities, crude oil has a historical coverage of 34 years while coal of only 13 years. Tradefeeds offers commodity prices data either via JSON REST API, or via downloadable databases in CSV or Excel format.

If you are interested to learn more, check out the company website: https://tradefeeds.com/commodities-prices-api/

Sharp economic volatility, the continued effects of high interest rates and mixed sentiment among investors created an uneven landscape for stock and commodity exchanges. While trading volumes soared in 2020 due to the pandemic and favorable financial conditions, such as zero percent interest rates from the Federal Reserve, the continued effects of high inflation in 2022 and 2023 resulted in a hawkish pivot on interest rates, which curtailed ROIs across major equity markets. Geopolitical volatility amid the Ukraine-Russia and Israel-Hamas wars further exacerbated trade volatility, as many investors pivoted away from traditional equity markets into derivative markets, such as options and futures to better hedge on their investment. Nonetheless, the continued digitalization of trading markets bolstered exchanges, as they were able to facilitate improved client service and stronger market insights for interested investors. Revenue grew an annualized 0.1% to an estimated $20.9 billion over the past five years, including an estimated 1.9% boost in 2025. A core development for exchanges has been the growth of derivative trades, which has facilitated a significant market niche for investors. Heightened options trading and growing attraction to agricultural commodities strengthened service diversification among exchanges. Major companies, such as CME Group Inc., introduced new tradeable food commodities for investors in 2024, further diversifying how clients engage in trades. These trends, coupled with strengthened corporate profit growth, bolstered exchanges’ profit. Despite current uncertainty with interest rates and the pervasive fear over a future recession, the industry is expected to do well during the outlook period. Strong economic conditions will reduce investor uncertainty and increase corporate profit, uplifting investment into the stock market and boosting revenue. Greater levels of research and development will expand the scope of stocks offered because new companies will spring up via IPOs, benefiting exchange demand. Nonetheless, continued threat from substitutes such as electronic communication networks (ECNs) will curtail larger growth, as better technology will enable investors to start trading independently, but effective use of electronic platforms by incumbent exchange giants such as NASDAQ Inc. can help stem this decline by offering faster processing via electronic trade floors and prioritizing client support. Overall, revenue is expected to grow an annualized 3.5% to an estimated $24.8 billion through the end of 2031.

Commodity Price Range 1877-Present

Historical Futures Contract Pricing for Wheat, Corn, and Oats

By [source]

About this dataset

This dataset contains over 140 years of historical commodity price ranges for wheat, corn, and oats futures contracts. It provides a glimpse into the evolution of our modern economic markets and the constant fluctuations in demand and supply that occur at all times. This data is invaluable to academic researchers, corporate strategists, economists, investors and traders alike as it reveals timely insight into various commodities' pricing trends over time. Each record includes the corresponding highest and lowest prices for each particular well-traded commodity on each particular day since 1877— providing an essential view into market dynamics across multiple decades. Use this data to identify recent pricing patterns or make predictions about future prices – no matter how you decide to use it–this may give you further insight into the ever-changing marketplace

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How to use the dataset

This dataset contains historical commodity price ranges for wheat, corn, and oats futures contracts from 1877 to present. It is a great resource for anyone interested in analyzing the trends of these commodities over time. Each row contains one day's data on the low and high prices of each contract.

To use this dataset, start by looking at the columns. There are several columns to choose from depending on which type of commodity you would like to analyze: Range_W_F1 (Lowest Price of Wheat Futures Contract), Range_W_F2 (Highest Price of Wheat Futures Contract), Range_C_F1 (Lowest Price of Corn Futures Contract), Range_C_F2 (Highest Price of Corn Futures Contract) and Range_O_F1 & 2 (Lowest and Highest Prices respectively for Oats Futures Contracts). Once you have selected the relevant columns for your analysis, pick a date range to focus on and filter out the rows outside that range. This will leave only those days within your chosen timeframe in the dataset so you can begin analyzing them more closely.

For an in-depth analysis it can be helpful to add other pieces data such as weather information or other economic indicators alongside these price ranges so you can investigate possible correlations between different factors that affect pricing in these markets over time. No matter how complex an analysis you might want to do with this data, this dataset provides a good starting point with reliable historical records dating all the way back over 140 years ago!

Research Ideas

• Market analysis to identify trends in prices of different commodities over time.
• Predictive modeling to forecast future prices based on past price ranges and market conditions.
• Proactive risk management strategies by tracking changes in commodity prices and anticipating potential changes in raw material costs for manufacturers or businesses that rely on commodities as part of their production processes

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: rangedata_commodities_since1877.csv | Column name | Description | |:---------------|:---------------------------------------------------------------| | Date | Date of the commodity price range. (Date) | | Range_W_F1 | Lowest price of wheat futures contract for the day. (Numeric) | | Range_W_F2 | Highest price of wheat futures contract for the day. (Numeric) | | Range_C_F1 | Lowest price of corn futures contract for the day. (Numeric) | | Range_C_F2 | Highest price of corn futures contract for the day. (Numeric) | | Range_O_F1 | Lowest price of oats futures contract for the day. (Numeric) | | Range_O_F2 | Highest price of oats futures contract for the day. (Numeric) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit .

Export Price Index - All Commodities - Historical chart and current data through 2025.

The World Bank’s Commodity Markets Outlook is published quarterly, in January, April, July and October. The report provides detailed market analysis for major commodity groups, including energy, metals, agriculture, precious metals and fertilizers. Price forecasts to 2025 for 46 commodities are presented along with historical price data. For more information, please visit: http://www.worldbank.org/commodities For current and past data on Commodity Price Forecasts, please see the Archives data tab on the website.

Time series data for the commodity Primary Commodity Prices, Vegetables, Tomato. Indicator Definition:Primary Commodity Prices, Vegetables, TomatoThe indicator "Primary Commodity Prices, Vegetables, Tomato" stands at 3.90 as of 08/31/2025. Regarding the One-Year-Change of the series, the current value constitutes an increase of 12.86 percent compared to the value the year prior.The 1 year change in percent is 12.86.The 3 year change in percent is 42.51.The 5 year change in percent is 22.99.The 10 year change in percent is 38.59.