Coffee fell to 389.95 USd/Lbs on August 25, 2025, down 0.18% from the previous day. Over the past month, Coffee's price has risen 29.25%, and is up 55.09% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Coffee - values, historical data, forecasts and news - updated on August of 2025.

Coffee growers raise two species of coffee bean: Arabica and robusta. The former is more expensive, selling for 2.93 U.S. dollars per kilogram in 2018 and projected to increase in price to 7.25 U.S. dollars in 2026. Robusta, named because it can grow at a wider range of altitudes and temperatures, sold for 1.87 U.S. dollars in 2018, projected to sell at 5 U.S. dollars per kilogram in 2026. Coffee production Coffee originally comes from Ethiopia, where a significant portion of coffee production continues to take place. The more popular bean, Arabica, takes its name from the Arabian Empire, when coffee consumption spread throughout the Middle East. After overcoming its ban by the Catholic Church, who saw coffee as in intoxicant from the Muslim world, coffee sales per capita are highest in European countries. Major players Starbucks has shaped the modern coffee culture, capitalizing on the Seattle coffee shop scene. This opened gourmet coffee to a wider market, shifting the global demand from cheaper robusta to better-tasting Arabica varieties. This shift has influenced the world coffee market, prompting companies such as McDonalds to open McCafé stores to cater to the evolving tastes of global consumers.

Global prices for coffee have skyrocketed to a seven-year high, driven by fears of a significant reduction in production in Brazil due to freezes and the depletion of global stocks. Further growth in prices for the product will be stimulated by the reduction in production in other leading supplying countries such as Honduras and Indonesia, coupled with increased freight costs. A decrease in coffee production will lead to a fall in global exports by -4% y-o-y, which could lead to local imbalances in supply and demand and drive up consumer prices in key European and American markets.

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.

WestRock's (WEST) Coffee Conundrum: Brewing a Tasty Return?

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 Global price of Coffee, Other Mild Arabica (PCOFFOTMUSDM) from Jan 1990 to Jun 2025 about coffee, World, and price.

Overview This comprehensive dataset offers an in-depth look at the financial performance of five major entities within the coffee industry from 2014 to 2024 (up to May 8, 2024). Included are stock prices of Keurig Dr Pepper, Starbucks, J.M. Smucker, Luckin Coffee, and Nestlé, paired with the corresponding periodical commodity prices for coffee. This data facilitates robust analyses including time series analysis, correlation studies, volatility analysis, and Vector Autoregression (VAR) analysis.

Key Companies Profiled Keurig Dr Pepper (KDP) and J.M. Smucker: These companies are leaders in the North American coffee market, known for their extensive portfolios of coffee products. Their data can provide insights into market strategies and financial health in response to fluctuating coffee prices. Starbucks: As a global leader in coffee retail, Starbucks' data reflects trends in consumer coffee consumption worldwide, offering a unique view of the retail sector's dynamics. Luckin Coffee: Representing a rapidly growing market, Luckin Coffee's data highlights the expansion and consumer trends within the Chinese coffee market. Nestlé: This global giant provides a broader perspective on how multinational food and beverage companies adapt to global commodity price changes, with a particular focus on coffee.

Applications of the Dataset This dataset is ideal for researchers, economists, and data scientists interested in: Market Trend Analysis: Understand how global events and market forces influence coffee prices and, in turn, affect company stocks. Consumer Behaviour Studies: Analyse consumption patterns across different regions, especially with a focus on the burgeoning Asian markets. Risk Management and Forecasting: Develop models to predict future trends and prepare risk management strategies for companies within the food and beverage sector. Sustainability Studies: Explore how price volatility relates to environmental factors and sustainability initiatives.

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

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 CRB Coffee Index Signaling a Shift in Global 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

Westrock Coffee Company stock may experience positive growth opportunities, but investors should be aware of potential market fluctuations and industry competition. The risk associated with these predictions is moderate, as the company faces challenges in a dynamic and competitive market.

Starbucks Corporation is a globally renowned coffeehouse chain founded in 1971 in Seattle, Washington by Jerry Baldwin, Zev Siegl, and Gordon Bowker. From its humble beginnings as a single store selling high-quality coffee beans and equipment, Starbucks has grown into one of the world's largest coffeehouse chains with thousands of stores across the globe. Known for its premium coffee, innovative beverages, and unique customer experience, Starbucks has become a cultural icon in the coffee industry.

This dataset provides a comprehensive record of Starbucks' stock price changes over the years(last 25 years). It includes crucial columns such as the date, opening price, highest price of the day, lowest price of the day, closing price, adjusted closing price, and trading volume.

This data is invaluable for conducting historical analyses, forecasting future stock performance, and understanding market trends related to Starbucks' stock.

The Coffee Market Report is Segmented by Product Type (Whole-Bean, Ground Coffee, and More), Distribution Channel (On-Trade and Off-Trade), Coffee Species (Arabica, Robusta and More), Origin (Single Origin/Specialty and Mixed), and Geography (North America, Europe, Asia-Pacific, South America, and Middle East and Africa). The Market Forecasts are Provided in Terms of Value (USD) and Volume (Tons).

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.

Coffee Prices Poised for Moderate Gains, Suggests CRB Coffee Index Forecast

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

Westrock Coffee p/s ratio from 2021 to 2025. P/s ratio can be defined as the price to sales or PS ratio is calculated by taking the latest closing price and dividing it by the most recent sales per share number. The PS ratio is an additional way to assess whether a stock is over or under valued and is used primarily in cases where earnings are negative and the PE ratio cannot be utilized.

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 Coffee Index: A Reliable Indicator of Coffee 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 Report Covers Global Organic Coffee Trends and the Market is Segmented by Origin (Arabica and Robusta), Product Form (Whole Bean, Ground, Instant, and Pods/Capsules), Packaging Format (Sachets, Pouches, and Jars), Distribution Channel (On-Trade and Off-Trade), and Geography (North America, Europe, Asia-Pacific, South America, and Middle East and Africa). The Market Forecasts are Provided in Terms of Value (USD).

The report covers Italian Coffee Brands and Market Share. The market is segmented by Product Type (Whole-Bean, Ground Coffee, Instant Coffee, and Coffee Pods, and Capsules); and by Distribution Channel (On-Trade and Off-Trade). The report offers market size and values in (USD Million) during the forecasted years for the above segments

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Raw Coffee Beans Market Size 2025-2029

The raw coffee beans market size is forecast to increase by USD 8.06 billion at a CAGR of 3.7% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing number of cafes worldwide and the rising demand for sustainable and ethically sourced coffee beans. Furthermore, consumers are increasingly conscious of the environmental and social impact of their coffee consumption, leading to a preference for beans that are ethically sourced and grown sustainably. However, the market faces challenges, primarily in the form of price volatility for raw coffee beans.
The prices of raw coffee beans have been notoriously unstable, with fluctuations influenced by various factors such as weather conditions, political instability, and economic factors. This volatility can pose significant challenges for coffee roasters and retailers, requiring them to manage their inventory and pricing strategies effectively to mitigate the impact of price fluctuations on their profitability. Companies seeking to capitalize on market opportunities and navigate challenges effectively must stay informed of market trends, build strong relationships with coffee bean suppliers, and adopt flexible pricing strategies to respond to price fluctuations.

What will be the Size of the Raw Coffee Beans Market during the forecast period?

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The market continues to evolve, shaped by dynamic market forces and shifting consumer preferences. Shade-grown coffee, specialty coffee, and Organic Coffee are gaining traction, with a focus on sustainability and traceability becoming increasingly important. Coffee capsules and ground coffee are popular formats in the convenience-driven consumer landscape. Sustainability is a key concern for coffee growers, leading to initiatives like bird-friendly coffee and fair trade certifications. Coffee bean density and cupping play crucial roles in determining bean quality. Coffee importers and exporters navigate complex logistical challenges, including storage and transportation, to ensure timely delivery of seeds. Coffee roasters and blenders innovate to meet diverse consumer demands, from filter coffee to cold brew and instant varieties. The market's continuous unfolding is shaped by ongoing efforts to improve seeds quality, enhance sustainability, and cater to evolving consumer tastes.

How is this Raw Coffee Beans Industry segmented?

The raw coffee beans industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Arabica
  Robusta


Method

  Wet/Washed process
  Dry/Natural process
  Honey process


Grade

  Specialty Grade
  Commercial Grade
  Premium Grade


Consumer Segment

  Commercial (Cafes
  Roasters)
  Household


Geography

  North America

    US
    Mexico


  Europe

    France
    Germany
    UK


  Middle East and Africa

    UAE


  APAC

    Australia
    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Type Insights

The arabica segment is estimated to witness significant growth during the forecast period.

The global coffee market is driven by the increasing preference for specialty coffee, particularly Arabica beans, among consumers, especially in developed countries. Arabica beans, known for their superior taste and lower caffeine content, are highly sought after for their smooth and mild flavor profile. The gourmet coffee shop and café industry's growing popularity, which prioritizes Arabica-based blends, further boosts demand. Arabica coffee is primarily cultivated in regions such as Latin America, with Brazil being the world's largest producer, followed by Colombia and its renowned Medellin beans. Sustainability is a significant factor in the coffee industry, with a growing emphasis on fair trade, organic, and shade-grown coffee.

Coffee cooperatives and direct trade initiatives also play a crucial role in ensuring fair prices for coffee farmers. The coffee supply chain involves various entities, including coffee growers, importers, exporters, roasters, and retailers. Coffee beans undergo various processes, such as grading, cupping, and storage, to ensure optimal quality. The market also caters to various coffee consumption preferences, including ground, whole bean, filter, cold brew, and instant coffee, as well as various coffee pod and capsule systems. Coffee bean traceability and sustainability are essential factors for consumers, leading to an increased focus on transparency and ethical sourcing. The coffee industry continues to evolve, with emerging trends such as bird-friendly and single-origin coffee, Cold Brew Coffee, and the increasing popularity of coffee capsules an

Stock Price Time Series for Colowide Co Ltd. Colowide Co.,Ltd., together with its subsidiaries, engages in restaurant management in Japan and internationally. It also engages in purchasing and selling various foodstuffs and processing sales, as well as tobacco and alcoholic beverages. The company also manufactures and sells confectioneries, baked goods, and chocolates, as well as sauce for commercial and consumer use; sells and distributes liquors and other related beverages; sells cigarettes and liquors; and provides catering services. In addition, it is involved in the operation and maintenance of IT systems, call center services; and procurement and logistics management related to catering service business. Further, the company operates the Wolfgang Puck restaurant; and Izakaya, Japanese, and Italian Cuisine. The company operates its restaurants under the Doma Doma, Kamadoka, Gyu-Kaku, Shabu Shabu On-Yasai, Tonkatsu Kagurazaka SAKURA, FRESHNESS BURGER, Steak MIYA, KARUBI TAISHO, GANKO-EN & GANKO-TEI, NIGIRI-NO-TOKUBE, KATSUDOKI, CHIISANA MORI COFFEE, OOTOYA, NAGISA BASHI CAFÉ, CANTINA, and M.M MARKET & CAFÉ. It operates various direct management and franchise stores. Colowide Co.,Ltd. was incorporated in 1963 and is headquartered in Yokohama, Japan.

During the 2023/24 period, global coffee imports amounted to a total of 137 million 60-kilogram bags. In the same period, around 142 million bags were exported worldwide. Coffee export countries In February 2024, Brazil exported the highest volume of coffee worldwide. The country exported roughly 3.6 million 60-kilo bags that month. Vietnam and Colombia stood in second and third place, exporting approximately 2.7 and 1.1 million sacks, respectively. In terms of global coffee production, Brazil also led the list, producing 69 million 60-kilo bags worth of coffee in 2020. Brazil produced over twice as much as Vietnam that year. Brazilian green coffee Brazil, which is known as one of the top coffee exporting countries worldwide, produced the highest volume of green coffee in Latin America by far in 2024/25. The South American country produced almost 48 million 60-kilogram sacks of green coffee that year. Colombia ranked second, producing just over 12 million green coffee bags.

This statistic shows the market share of Yoo-hoo in the United States from 2007 to 2019. In 2019, Yoo-hoo held a *** percent share of the ready-to-drink coffee market in the United States.