Orange Juice fell to 147.99 USd/Lbs on December 2, 2025, down 0.38% from the previous day. Over the past month, Orange Juice's price has fallen 15.22%, and is down 71.10% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Orange Juice - values, historical data, forecasts and news - updated on December of 2025.

Context

The price of frozen concentrated orange juice is a significant indicator in the agricultural commodities market, reflecting factors like weather conditions, crop yields, and global demand. Gaining access to accurate and comprehensive historical data is essential for traders, analysts, and researchers aiming to comprehend its market behavior, predict future price movements, and develop effective trading strategies.

This dataset offers a detailed, daily-updated record of orange juice prices, sourced from the Orange Juice Futures (OJ=F) market, a standard benchmark for historical analysis.

Content

This dataset contains daily price information for Orange Juice Futures (OJ=F) in a clean, tabular format. Each row represents a single trading day and includes the following columns:

Date: The date of the trading session (YYYY-MM-DD).

Open: The price at which orange juice futures first traded for the day in USD.

High: The highest price reached during the trading day in USD.

Low: The lowest price reached during the trading day in USD.

Close: The closing price at the end of the trading day in USD.

Volume: The total number of futures contracts traded during the day.

Graph and download economic data for Producer Price Index by Commodity: Processed Foods and Feeds: Frozen Juices, Ades, Drinks, and Cocktails, Including Orange Juice (WPU024203) from Jun 1981 to Jan 2020 about juice, processed, food, 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.

Orange Juice Futures: TR/CC CRB Index Signals Potential Price Swings

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

Orange juice futures rise to a three-month high over proposed tariffs on Brazilian goods, potentially impacting trade and prices.

✍️ Personal Note: While I'm presenting this dataset for analysis and insights, I want to emphasize the importance of ethical sourcing and consumption, especially in commodities like cocoa and coffee which have known ethical concerns in their supply chains.

About This Dataset:

This dataset delivers an extensive and current assortment of futures related to soft commodities. Futures are financial contracts obligating the buyer to purchase, and the seller to sell, a specified amount of a particular commodity at a predetermined price on a set date in the future.

Use Cases: 1. Price Forecasting: Harness machine learning to predict the price dynamics of commodities like coffee and cocoa, aiding stakeholders in their decision-making. 2. Supply Chain Analysis: Evaluate the correlation between futures prices and global events, offering insights into potential supply chain disruptions. 3. Demand Projections: Utilize deep learning techniques to correlate historical consumption patterns with price movements, projecting future demand.

Dataset Image Source: Photo by Tom Fisk from Pexels: https://www.pexels.com/photo/aerial-shot-of-green-milling-tractor-1595108/

Column Descriptions: 1. Date: The date when the data was recorded. Format: YYYY-MM-DD. 2. Open: The opening market price for the day. 3. High: Maximum price achieved during the trading session. 4. Low: Lowest traded price during the session. 5. Close: Market's concluding price. 6. Volume: Count of contracts traded throughout the session. 7. Ticker: Distinct market quotation symbol for the commodity future. 8. Commodity: Indicates the type of soft commodity the futures contract pertains to (e.g., Cocoa, Coffee).

Remember to link to the correct image source for your dataset's image!

Includes 100% orange juice sold in a 12 oz. frozen concentrate can with 1 to 3 concentration, regardless of packaging or the presence of sweeteners. Includes organic and non-organic."

个人消费支出（PCE）通胀预测：SA：贡献：商品价格：橙汁期货：ICE：结算价格：第一个月在05-12-2025达0.000%，相较于05-05-2025的0.000%保持不变。个人消费支出（PCE）通胀预测：SA：贡献：商品价格：橙汁期货：ICE：结算价格：第一个月数据按周更新，04-01-2019至05-12-2025期间平均值为0.000%，共320份观测结果。该数据的历史最高值出现于11-16-2020，达7.905%，而历史最低值则出现于05-12-2025，为0.000%。CEIC提供的个人消费支出（PCE）通胀预测：SA：贡献：商品价格：橙汁期货：ICE：结算价格：第一个月数据处于定期更新的状态，数据来源于CEIC Data，数据归类于全球数据库的美国 – Table US.CEIC.NC: CEIC Nowcast: Personal Consumption Expenditure (PCE) Inflation: Headline。