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Corn futures fall by 7 cents per bushel, reversing gains. Increased open interest and new long positions noted. USDA reports slight decrease in export inspections.
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Corn fell to 389.36 USd/BU on August 1, 2025, down 1.19% from the previous day. Over the past month, Corn's price has fallen 9.29%, and is down 3.45% compared to the same time last year, 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 August of 2025.
In 2022, the average price of one bushel of corn was around **** U.S. dollars. That year, the United States was the largest producer of corn in the world.
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The dataset contains daily price ranges calculated from the daily high and low prices for Chicago Wheat, Corn, and Oats futures contracts, starting in 1877. The data is manually extracted from the ``Annual Reports of the Trade and Commerce of Chicago'' (today, the Chicago Board of Trade, CBOT, which is part of the CME group).
The price range is calculated as Ranget = ln(Ht) - ln(Lt), where Ht and Lt are the highest and lowest price observed on trading day t.
Description of the dataset:
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In 2024, the U.S. wet corn market decreased by -6.9% to $10.5B, falling for the second year in a row after four years of growth. In general, consumption recorded a relatively flat trend pattern. As a result, consumption attained the peak level of $11.9B. From 2023 to 2024, the growth of the market remained at a lower figure.
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Get statistical data on weekly spot market and forward contract corn prices in Ontario. Data includes: * old and new crop Chicago Board of Trade (CBOT) prices * old and new crop weekly unadjusted basis * old and new crop weekly adjusted basis * old crop weekly cash price * new crop cash price * cash price spread * CBOT price spread * Canadian dollar value * 5-year average for corn basis * 10-year average for corn basis * 10-year average cash price Statistical data are compiled to serve as a source of agriculture and food statistics for the province of Ontario. Data are prepared primarily by Statistics and Economics staff of the Ministry of Agriculture, Food and Rural Affairs, in co-operation with the Agriculture Division of Statistics Canada and various government departments and farm marketing boards.
Download Historical Corn Futures Data. CQG daily, 1 minute, tick, and level 1 data from 1899.
The dataset are the individual futures prices for Chicago corn in 2017
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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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
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China Settlement Price: Dalian Commodity Exchange: Corn: 2nd Month data was reported at 2,365.000 RMB/Ton in Apr 2025. This records an increase from the previous number of 2,250.000 RMB/Ton for Mar 2025. China Settlement Price: Dalian Commodity Exchange: Corn: 2nd Month data is updated monthly, averaging 1,983.500 RMB/Ton from Sep 2004 (Median) to Apr 2025, with 248 observations. The data reached an all-time high of 2,971.000 RMB/Ton in Apr 2022 and a record low of 1,126.000 RMB/Ton in Oct 2004. China Settlement Price: Dalian Commodity Exchange: Corn: 2nd Month data remains active status in CEIC and is reported by Dalian Commodity Exchange. The data is categorized under China Premium Database’s Financial Market – Table CN.ZB: Dalian Commodity Exchange: Commodity Futures: Settlement Price.
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Graph and download economic data for Global price of Corn (PMAIZMTUSDM) from Jan 1990 to Jun 2025 about corn, World, and price.
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This data product provides three Excel file spreadsheet models that use futures prices to forecast the U.S. season-average price received and the implied CCP for three major field crops (corn, soybeans, and wheat).
Farmers and policymakers are interested in the level of counter-cyclical payments (CCPs) provided by the 2008 Farm Act to producers of selected commodities. CCPs are based on the season-average price received by farmers. (For more information on CCPs, see the ERS 2008 Farm Bill Side-By-Side, Title I: Commodity Programs.)
This data product provides three Excel spreadsheet models that use futures prices to forecast the U.S. season-average price received and the implied CCP for three major field crops (corn, soybeans, and wheat). Users can view the model forecasts or create their own forecast by inserting different values for futures prices, basis values, or marketing weights. Example computations and data are provided on the Documentation page.
For each of the three major U.S. field crops, the Excel spreadsheet model computes a forecast for:
Note: the model forecasts are not official USDA forecasts. See USDA's World Agricultural Supply and Demand Estimates for official USDA season-average price forecasts. See USDA's Farm Service Agency information for official USDA CCP rates.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Webpage with links to Excel files For complete information, please visit https://data.gov.
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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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
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China Settlement Price: Dalian Commodity Exchange: Corn: 5th Month data was reported at 2,294.000 RMB/Ton in Apr 2025. This records an increase from the previous number of 2,246.000 RMB/Ton for Mar 2025. China Settlement Price: Dalian Commodity Exchange: Corn: 5th Month data is updated monthly, averaging 2,007.000 RMB/Ton from Sep 2004 (Median) to Apr 2025, with 248 observations. The data reached an all-time high of 3,011.000 RMB/Ton in Apr 2022 and a record low of 1,164.000 RMB/Ton in Sep 2004. China Settlement Price: Dalian Commodity Exchange: Corn: 5th Month data remains active status in CEIC and is reported by Dalian Commodity Exchange. The data is categorized under China Premium Database’s Financial Market – Table CN.ZB: Dalian Commodity Exchange: Commodity Futures: Settlement Price.
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Wheat fell to 516.75 USd/Bu on August 1, 2025, down 1.24% from the previous day. Over the past month, Wheat's price has fallen 8.38%, and is down 4.13% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Wheat - values, historical data, forecasts and news - updated on August of 2025.
Basis reflects both local and global supply and demand forces. It is calculated as the difference between the local cash price and the futures price. It affects when and where many grain producers and shippers buy and sell grain. Many factors affect basis—such as local supplies, storage and transportation availability, and global demand—and they interact in complex ways. How changes in basis manifest in transportation is likewise complex and not always direct. For instance, an increase in current demand will drive cash prices up relative to future prices, and increase basis. At the same time, grain will enter the transportation system to fulfill that demand. However, grain supplies also affect basis, but will have the opposite effect on transportation. During harvest, the increase in the supply of grain pushes down cash prices relative to futures prices, and basis weakens, but the demand for transportation increases to move the supplies.
For more information on how basis is linked to transportation, see the story, "Grain Prices, Basis, and Transportation" (https://agtransport.usda.gov/stories/s/sjmk-tkh6), and links below for research on the topic.
This data has corn, soybean, and wheat basis for a variety of locations. These include origins—such as Iowa, Minnesota, Nebraska, and many others—and destinations, such as the Pacific Northwest, Louisiana Gulf, Texas Gulf, and Atlantic Coast.
This is one of three companion datasets. The other two are grain prices (https://agtransport.usda.gov/d/g92w-8cn7) and grain price spreads (https://agtransport.usda.gov/d/an4w-mnp7). These datasets are separate, because the coverage lengths differ and missing values are removed (e.g., there needs to be a cash price and a futures price to have a basis price).
The cash price comes from the grain prices dataset and the futures price comes from the appropriate futures market, which is Chicago Board of Trade (CME Group) for corn, soybeans, and soft red winter wheat; Kansas City Board of Trade (CME Group) for hard red winter wheat; and the Minneapolis Grain Exchange for hard red spring wheat.
Download Historical Corn (Pit) Futures Data. CQG daily, 1 minute, tick, and level 1 data from 1899.
This data set contains Ontario wheat grain prices collected by University of Guelph, Ridgetown Campus. The dataset includes daily prices of agricultural commodities at individual elevators in Ontario. Daily highs and lows are given for each commodity, as well as, daily Bank of Canada exchange rates.This dataset includes data from January 1, 2024 to December 31, 2024.
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France Open Interest: Commodity Product Futures: Corn data was reported at 26,206.000 Unit in Nov 2018. This records an increase from the previous number of 24,459.000 Unit for Oct 2018. France Open Interest: Commodity Product Futures: Corn data is updated monthly, averaging 13,481.000 Unit from Jan 2002 (Median) to Nov 2018, with 203 observations. The data reached an all-time high of 40,446.000 Unit in Dec 2014 and a record low of 2,202.000 Unit in Jun 2006. France Open Interest: Commodity Product Futures: Corn data remains active status in CEIC and is reported by Euronext. The data is categorized under Global Database’s France – Table FR.Z005: Euronext: Open Interest.
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Long Term Projections: Corn: Farm Price data was reported at 4.300 USD/Bushel in 2034. This stayed constant from the previous number of 4.300 USD/Bushel for 2033. Long Term Projections: Corn: Farm Price data is updated yearly, averaging 4.300 USD/Bushel from Dec 2022 (Median) to 2034, with 13 observations. The data reached an all-time high of 6.540 USD/Bushel in 2022 and a record low of 3.900 USD/Bushel in 2025. Long Term Projections: Corn: Farm Price data remains active status in CEIC and is reported by U.S. Department of Agriculture. The data is categorized under Global Database’s United States – Table US.RI005: Agricultural Projections: Feed Grains: Corn.
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Corn futures fall by 7 cents per bushel, reversing gains. Increased open interest and new long positions noted. USDA reports slight decrease in export inspections.