Coffee fell to 288.72 USd/Lbs on July 11, 2025, down 0.41% from the previous day. Over the past month, Coffee's price has fallen 16.63%, but it is still 15.90% higher than a year ago, 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 July of 2025.

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

📈 Daily Historical Stock Price Data for Coffee Day Enterprises Limited (2015–2025)

A clean, ready-to-use dataset containing daily stock prices for Coffee Day Enterprises Limited from 2015-11-02 to 2025-05-28. This dataset is ideal for use in financial analysis, algorithmic trading, machine learning, and academic research.

  🗂️ Dataset Overview

Company: Coffee Day Enterprises Limited Ticker Symbol: COFFEEDAY.NS Date Range: 2015-11-02 to 2025-05-28 Frequency: Daily Total… See the full description on the dataset page: https://huggingface.co/datasets/khaledxbenali/daily-historical-stock-price-data-for-coffee-day-enterprises-limited-20152025.

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.

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.

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

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 4.8 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 3.9 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.

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.

Westrock Coffee (WEST) Faces Mixed Analyst Outlook, Coffee Demand Concerns

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 global market size of Coffee Shop is $XX million in 2018 with XX CAGR from 2014 to 2018, and it is expected to reach $XX million by the end of 2024 with a CAGR of XX% from 2019 to 2024.
Global Coffee Shop Market Report 2019 - Market Size, Share, Price, Trend and Forecast is a professional and in-depth study on the current state of the global Coffee Shop industry. The key insights of the report:
1.The report provides key statistics on the market status of the Coffee Shop manufacturers and is a valuable source of guidance and direction for companies and individuals interested in the industry.
2.The report provides a basic overview of the industry including its definition, applications and manufacturing technology.
3.The report presents the company profile, product specifications, capacity, production value, and 2013-2018 market shares for key vendors.
4.The total market is further divided by company, by country, and by application/type for the competitive landscape analysis.
5.The report estimates 2019-2024 market development trends of Coffee Shop industry.
6.Analysis of upstream raw materials, downstream demand, and current market dynamics is also carried out
7.The report makes some important proposals for a new project of Coffee Shop Industry before evaluating its feasibility.
There are 4 key segments covered in this report: competitor segment, product type segment, end use/application segment and geography segment.
For competitor segment, the report includes global key players of Coffee Shop as well as some small players.
The information for each competitor includes:
* Company Profile
* Main Business Information
* SWOT Analysis
* Sales, Revenue, Price and Gross Margin
* Market Share

For product type segment, this report listed main product type of Coffee Shop market
* Product Type I
* Product Type II
* Product Type III

For end use/application segment, this report focuses on the status and outlook for key applications. End users sre also listed.
* Application I
* Application II
* Application III

For geography segment, regional supply, application-wise and type-wise demand, major players, price is presented from 2013 to 2023. This report covers following regions:
* North America
* South America
* Asia & Pacific
* Europe
* MEA (Middle East and Africa)
The key countries in each region are taken into consideration as well, such as United States, China, Japan, India, Korea, ASEAN, Germany, France, UK, Italy, Spain, CIS, and Brazil etc.

Reasons to Purchase this Report:
* Analyzing the outlook of the market with the recent trends and SWOT analysis
* Market dynamics scenario, along with growth opportunities of the market in the years to come
* Market segmentation analysis including qualitative and quantitative research incorporating the impact of economic and non-economic aspects
* Regional and country level analysis integrating the demand and supply forces that are influencing the growth of the market.
* Market value (USD Million) and volume (Units Million) data for each segment and sub-segment
* Competitive landscape involving the market share of major players, along with the new projects and strategies adopted by players in the past five years
* Comprehensive company profiles covering the product offerings, key financial information, recent developments, SWOT analysis, and strategies employed by the major market players
* 1-year analyst support, along with the data support in excel format.
We also can offer customized report to fulfill special requirements of our clients. Regional and Countries report can be provided as well.

In 2024, the U.S. coffee and tea market increased by 8.6% to $18.3B, rising for the sixth year in a row after three years of decline. The market value increased at an average annual rate of +3.7% over the period from 2013 to 2024; the trend pattern indicated some noticeable fluctuations being recorded throughout the analyzed period. Over the period under review, the market hit record highs in 2024 and is expected to retain growth in the near future.

In 2024, the Colombian roasted coffee market increased by 1.7% to $1.3B, rising for the fifth year in a row after five years of decline. The market value increased at an average annual rate of +2.2% over the period from 2012 to 2024; the trend pattern indicated some noticeable fluctuations being recorded throughout the analyzed period. Over the period under review, the market attained the peak level in 2024 and is likely to see gradual growth in the immediate term.

For the third consecutive year, the MENA's decaffeinated or roasted coffee market recorded growth in sales value, which increased by 3.6% to $3.6B in 2024. The market value increased at an average annual rate of +1.0% over the period from 2012 to 2024; the trend pattern remained relatively stable, with somewhat noticeable fluctuations being recorded in certain years. As a result, consumption reached the peak level of $3.7B. From 2021 to 2024, the growth of the market failed to regain momentum.

The Raw Coffee Beans Market report segments the industry into Geography (North America, Europe, Asia-Pacific, South America, Middle East and Africa). The report includes Production Analysis by Volume, Consumption Analysis by Value and Volume, Import Analysis by Value and Volume, Export Analysis by Value and Volume, and Price Trend Analysis. Get five years of historical data alongside five-year market forecasts.

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

In 2024, the Austrian coffee substitutes market increased by 12% to $22M, rising for the third consecutive year after two years of decline. The market value increased at an average annual rate of +1.4% over the period from 2012 to 2024; the trend pattern remained relatively stable, with only minor fluctuations being recorded in certain years. Coffee substitutes consumption peaked at $22M in 2017; however, from 2018 to 2024, consumption stood at a somewhat lower figure.

Graph and download economic data for Global price of Coffee, Other Mild Arabica (PCOFFOTMUSDM) from Jan 1990 to Apr 2025 about coffee, World, and price.

The global coffee machines market is expected to grow at a CAGR of 4.10% during the period 2025-2034. The market is expected to be driven by consumers’ evolving tastes with respect to coffee. Consumers invest time and money in purchasing a coffee making machine, and seek a continual return on such investment. Further, manufacturers seek benefits by offering better taste, the ability to adjust taste, and enabling consumers to get a superior coffee experience. North America, Europe and Asia are expected to be key markets.

The Belgian roasted coffee market dropped significantly to $434M in 2024, reducing by -23.9% against the previous year. Overall, the total consumption indicated mild growth from 2012 to 2024: its value increased at an average annual rate of +1.4% over the last twelve-year period. The trend pattern, however, indicated some noticeable fluctuations being recorded throughout the analyzed period. Based on 2024 figures, consumption increased by +11.5% against 2022 indices.