Interactive chart of historical daily soybean prices back to 1971. The price shown is in U.S. Dollars per bushel.

Soybeans fell to 1,008.02 USd/Bu on July 2, 2025, down 1.63% from the previous day. Over the past month, Soybeans's price has fallen 3.15%, and is down 14.38% 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 July of 2025.

This statistic depicts the average annual prices for soybeans from 2014 through 2026*. In 2023, the average price for soybeans stood at 598 nominal U.S. dollars per metric ton.

Learn about the factors that influence the price of soybeans, including supply and demand dynamics, weather conditions, government policies, and market trends. Discover how weather events, government policies, and global market trends can affect soybean prices. Understand the importance of monitoring real-time market data and consulting with experts for up-to-date information on soybean prices.

Discover how soybean prices are impacted by supply and demand, weather, and geopolitical factors. Explore insights from USDA reports and understand the influence of trade policies and market trends on soybean markets.

Soybeans prices in , May, 2025 For that commodity indicator, we provide data from January 1960 to May 2025. The average value during that period was 290.86 USD per metric ton with a minimum of 88 USD per metric ton in October 1960 and a maximum of 737.06 USD per metric ton in June 2022. | TheGlobalEconomy.com

Explore the dynamic factors influencing soybean prices, including weather, global demand, trade policies, and speculation. Learn how yields, trade relations, futures contracts, and government policies shape market fluctuations as of October 2023.

Graph and download economic data for Global price of Soybeans (PSOYBUSDM) from Jan 1990 to May 2025 about beans, World, and price.

Learn about the factors that influence daily soybean prices, including supply and demand dynamics, weather conditions, government policies, and global market trends. Find out how stakeholders in the soybean industry use this information to make informed decisions.

The price of soybeans today per kg is influenced by a variety of factors, including supply and demand dynamics, weather conditions, government policies, and global economic trends. This article explores the key drivers of soybean prices, such as global demand, weather events, government policies, and currency exchange rates. It also highlights the current price of soybeans per kg and acknowledges the potential for market fluctuations.

This dataset contains Ontario soybean 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, 2025 to May 31, 2025. Data for June 1, 2025 to December 31, 2025 will be added as it becomes available.

This data set contains Ontario soybean 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.

This data set contains Ontario feed 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.

Graph and download economic data for Global price of Soybeans (PSOYBUSDQ) from Q1 1990 to Q1 2025 about beans, World, and price.

Get statistical data on weekly spot market and forward contract soybean 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 soybean basis * 10-year average for soybean 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.

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

Learn about the factors that influence the current market rate for soybeans, including supply and demand dynamics, weather conditions, government policies, and global trade patterns. Understand how these factors impact soybean prices and why they fluctuate on a daily basis. Stay informed to make informed decisions about planting, harvesting, and selling soybean crops.

The current price of soybeans is influenced by various factors such as supply and demand dynamics, weather conditions, global trade policies, and commodity market trends. This article discusses the importance of soybeans as an agricultural commodity, how to obtain current soybean prices, and the factors that impact soybean prices. It emphasizes the need for stakeholders in soybean-related industries to stay updated on soybean prices to make informed decisions.

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.

Soybean Index: A Reliable Indicator of Market Trends?

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 US soybean farming industry is navigating significant changes in the current period, with soybean prices determining the initial rise and recent decline in industry performance. These prices have been influenced by several key factors, including the growing demand for biofuels and mixed consumer perceptions regarding soy products. The demand for soybean oil in biofuel production surged due to supportive policies like the Renewable Fuel Standard and rising crude oil prices, creating a lucrative market for soybean producers. However, subsequent drops in fertilizer and crude oil prices, paired with record-high soybean production, have sharply dropped soybean prices, bringing revenue and profit down with them as farmers struggle to balance costs with lower incomes. Industry has shrunk a compound annual growth rate (CAGR) of 2.6%, with a decrease of 8.7% in 2025, reaching an estimated $44.2 billion. US soybean exports are facing mounting challenges due to competitive pressures abroad and quickly evolving trade policy. Brazil’s increased production and improved export infrastructure have strengthened its position as a major supplier, particularly to China, which is reducing its reliance on US soybeans. This shift threatens US exports and compels American farmers to reassess their strategies, focusing on market diversification and emphasizing quality and sustainability to remain competitive. Rising geopolitical tensions and newly imposed tariffs, such as those affecting key markets like the EU, Canada and China, have further complicated trade, impacting US farmers' access and pricing power in these vital markets. Through the end of 2025, soybean prices are initially projected to decline due to increased production and growing global supplies. However, as climate change impacts crop yields through extreme weather and pest challenges and supplies become limited prices will be pushed upward alongside rising global demand. Subsidies will continue to play a vital role in supporting farmer incomes amids these fluctuations, providing some stability to an otherwise highly volatile industry. However, the industry faces significant uncertainty due to the ongoing USDA funding freeze is creating significant uncertainty, particularly where government support and subsidies are concerned. This freeze is affecting a wide range of agricultural programs including conservation efforts, market development, research and technical assistance. Over the next five years, the industry is expected to grow at a CAGR of 1.3%, with revenues reaching $47.1 billion by the end of 2030.