Corn fell to 419.27 USd/BU on July 1, 2025, down 0.29% from the previous day. Over the past month, Corn's price has fallen 4.33%, and is down 0.47% 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 July 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.

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

Grain Stocks Corn in the United States decreased to 4.64 Billion Bushels in the second quarter of 2025 from 8.15 Billion Bushels in the first quarter of 2025. This dataset provides - United States Quarterly Grain Stocks - Corn- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Interactive chart of historical daily corn prices back to 1959. The price shown is in U.S. Dollars per bushel.

The global preserved sweet corn market reached $X in 2022, growing by X% against the previous year. The market value increased at an average annual rate of X% from 2012 to 2022; the trend pattern remained relatively stable, with somewhat noticeable fluctuations being recorded throughout the analyzed period. The most prominent rate of growth was recorded in 2019 with an increase of X% against the previous year. Over the period under review, the global market reached the peak level in 2022 and is expected to retain growth in years to come.

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

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.

The global corn market reached a volume of 1183.43 MMT in 2024. The market is projected to grow at a CAGR of 1.10% between 2025 and 2034, to reach a volume of around 1320.24 MMT by 2034.

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

Global corn market size & share estimated to surpass USD 410.02 billion by 2032, to grow at a CAGR of 3.6% during the forecast period. The food & beverages segment held the majority share on account of growing food consumption and advancements in food processing techniques.

Wheat rose to 534.93 USd/Bu on July 1, 2025, up 1.17% from the previous day. Over the past month, Wheat's price has fallen 0.75%, and is down 7.93% 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 July of 2025.

The Corn Market size was valued at USD 305.32 billion in 2023 and is projected to reach USD 391.09 billion by 2032, exhibiting a CAGR of 3.6 % during the forecasts period. Corn which is also referred to as maize is a cereal grain which is being widely grown in the world today. It was initially cultivated in Mesoamerica and has since spread to many other regions across different continents where it is a major source of food. Corn is widely consumed as staple food and also an essential part of animal’s meal and produce biofuel. Other than corn, its derivatives can also be used for wide range of applications in food & beverages, pharmaceuticals, animal feed and other industrial applications. Growing demand of convenience and processed food due to busy lifestyle is expected to boost corn sweeteners and starch market as well as overall corn market. Recent developments include: In August 2023, Bayer has introduced biotech seeds ‘Deklab DK95R’ in Indonesia with the aim of boosting the country's corn production. , In April 2023, Origin Agritech Ltd., a Chinese agriculture technology company, announced its majority-owned joint venture agreement with Shihezi City in Xinjiang Province. The deal was made to allocate 13,300 hectares of farmland for cultivating Nutritionally Enhanced Corn (NEC). , In March 2023, Corteva Agriscience revealed its intentions to launch Vorceed Enlist corn products commercially. Vorceed Enlist corn incorporates three above-ground insect protection modes of action and three below-ground insect protection modes of action, including RNAi technology. .

The Mexican frozen sweet corn market was finally on the rise to reach $X in 2022, after two years of decline. The market value increased at an average annual rate of X% from 2012 to 2022; the trend pattern remained consistent, with only minor fluctuations being observed throughout the analyzed period. Frozen sweet corn consumption peaked at $X in 2019; however, from 2020 to 2022, consumption failed to regain momentum.

The China Corn Market size was valued at USD 6.17 Million in 2023 and is projected to reach USD 6.52 Million by 2032, exhibiting a CAGR of 3.10 % during the forecast periods. China's corn market is a major global player, characterized by extensive production, government support, and a focus on diverse applications such as food, feed, and biofuels. Advanced farming technologies and various corn types drive growth. The market impacts rural economies, food security, and trade, offering advantages like enhanced food security and rural development. Recent developments include: June 2022: The Chinese National Crop Variety Approval Committee released two sets of standards to clear the cultivation of genetically modified (GM) crops in China. For the commercial production of GM maize in China, the government has two steps in these regulations: a "safety certificate" and a "variety approval" before crops can be commercially cultivated in the provinces., July 2021: Chinese farmers sharply increased corn planting to cash in on demand-fuelled record prices, a trend that cooled the country's rampant import appetite. This expansion, mainly at the expense of soybeans and other crops, including sorghum and edible beans, boosted China's maize output in 2021-22 by at least 6 percent., June 2021: China started sustainable production of maize that could 'boost yields and cut greenhouse gas emissions and fertilizer use' in the country by 2035.. Notable trends are: Increasing Demand for Corn as Animal-based Protein Sources.

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 Cornindex: A Reliable Indicator of Corn Market Health?

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

Uncover Market Research Intellect's latest Corn Market Report, valued at USD 225 billion in 2024, expected to rise to USD 300 billion by 2033 at a CAGR of 4.2% from 2026 to 2033.

Soybeans fell to 1,027.21 USd/Bu on June 30, 2025, down 0.05% from the previous day. Over the past month, Soybeans's price has fallen 0.61%, 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. Soybeans - values, historical data, forecasts and news - updated on June 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.

Cornindex: The Future of Corn Pricing?

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 EU preserved sweet corn market stood at $X in 2022, increasing by X% against the previous year. The market value increased at an average annual rate of X% over the period from 2012 to 2022; the trend pattern remained relatively stable, with somewhat noticeable fluctuations being recorded in certain years. The level of consumption peaked in 2022 and is likely to see gradual growth in the near future.

Explore the growth potential of Market Research Intellect's Corn Flake Market Report, valued at USD 14.5 billion in 2024, with a forecasted market size of USD 22.1 billion by 2033, growing at a CAGR of 5.8% from 2026 to 2033.