Corn rose to 384.15 USd/BU on August 15, 2025, up 2.44% from the previous day. Over the past month, Corn's price has fallen 5.21%, and is down 2.13% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Corn - values, historical data, forecasts and news - updated on August of 2025.

Graph and download economic data for Producer Price Index by Commodity: Farm Products: Corn (WPU012202) from Jan 1971 to Jun 2025 about corn, vegetables, agriculture, commodities, PPI, inflation, price index, indexes, price, and USA.

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.

Is the TR/CC CRB Corn Index an Accurate Reflection of Corn Market Performance?

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

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.

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.

Explore the complexities of trading corn commodity stocks, including futures, options, and ETFs. Understand the factors affecting global corn prices and how to invest wisely in this vital agricultural product.

United States - Producer Price Index by Commodity: Farm Products: Corn was 182.83400 Index 1982=100 in March of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Commodity: Farm Products: Corn reached a record high of 324.61700 in June of 2022 and a record low of 43.20000 in November of 1971. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Commodity: Farm Products: Corn - last updated from the United States Federal Reserve on August of 2025.

United States - Export Price Index (End Use): Corn was 219.60000 Index 2000=100 in June of 2025, according to the United States Federal Reserve. Historically, United States - Export Price Index (End Use): Corn reached a record high of 370.50000 in May of 2022 and a record low of 83.70000 in September of 1986. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Export Price Index (End Use): Corn - last updated from the United States Federal Reserve on August 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.

TR/CC CRB Corn Index: A Reliable Gauge of Global Corn 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

Graph and download economic data for Producer Price Index by Commodity: Farm Products: Sweet Corn (WPU01130214) from Jan 1960 to Jun 2025 about corn, vegetables, agriculture, commodities, PPI, inflation, price index, indexes, price, and USA.

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.

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.

Corn Futures: TR/CC CRB Corn Index Projects Moderate Price Fluctuations

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

China Open Interest: Dalian Commodity Exchange: Corn data was reported at 2,120.279 Lot th in 13 May 2025. This records a decrease from the previous number of 2,168.241 Lot th for 12 May 2025. China Open Interest: Dalian Commodity Exchange: Corn data is updated daily, averaging 1,344.629 Lot th from Sep 2004 (Median) to 13 May 2025, with 5012 observations. The data reached an all-time high of 5,083.242 Lot th in 13 Feb 2017 and a record low of 251.066 Lot th in 09 Jan 2015. China Open Interest: Dalian Commodity Exchange: Corn data remains active status in CEIC and is reported by Dalian Commodity Exchange. The data is categorized under High Frequency Database’s Commodity Prices and Futures – Table CN.ZB: Dalian Commodity Exchange: Commodity Futures: Open Position: Daily.

Studies comparing profitability of tillage systems often examine narrow historic windows or exclude annual price fluctuations. This study uses a continuous corn (Zea mays L.) (CC; 1970–1990) and corn–soybean Glycine max (L.) Merr. Tillage × Fertilizer study in somewhat poorly drained soils in southern Illinois to reconstruct partial annual budgets with historical prices for crops, fertilizers, lime, herbicides, fuel, labor, and machinery. Combinations of tillage (moldboard plow [MP], chisel tillage [ChT], alternate tillage [AT], and no-till [NT]) and fertilizer (Control, N-only, N+NPK starter, NPK+NPK starter, and NPK broadcast) treatments were evaluated. The CC profits were highest in NPK-applied treatments followed by N-only and Control. The MP treatments were similar to ChT and more profitable than NT, while AT fell between. In CS, NPK-applied treatments were similar regardless of tillage. Combined costs for herbicide, machinery, labor, and diesel were higher in MP ...

Learn about the factors that impact corn prices in the commodity market, including weather, supply and demand, government policies, and market speculation. Gain insight into this complex market to make informed decisions and plan for changes in this vital commodity cost.

This statistic shows the price increase in food commodities between mid-June and mid-July, 2012. The price of corn increased by 33 percent in this period.

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.

Discover the latest shifts in corn futures as volume and open interest see significant changes, affecting global commodity trends.

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.

Corn Price Volatility Expected, Impacting TR/CC CRB Corn Index

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 Wholesale Price Index of maize across India during financial year 2024 was over ***. The price index value of maize increased by about ** percent from the base year of 2012. An overall increase in the price index was seen over the years from financial year 2013 in the country.