Real-time commodities pricing data allows you to grasp where the market is, was and will be – from exchange data and OTC prices to specialist fundamentals.

Cbonds collects and normalizes indices data, offering daily updated and historical data on over 40,000 indices, including macroeconomic indicators, yield curves and spreads, currency markets, stock and funds markets, and commodities. Using the Indices API, you can access an index's holdings, such as its assets, sectors, and weight, as well as basic data on the asset. You can obtain end-of-day, and historical API indicator prices in CSV, XLS, and JSON formats. Cbonds provides a free Indices API for a limited test period of two weeks or for a longer period with a limited number of instruments.

Gold rose to 3,349.44 USD/t.oz on July 18, 2025, up 0.32% from the previous day. Over the past month, Gold's price has fallen 0.60%, but it is still 39.85% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gold - values, historical data, forecasts and news - updated on July of 2025.

Crude Oil fell to 67.30 USD/Bbl on July 18, 2025, down 0.36% from the previous day. Over the past month, Crude Oil's price has fallen 8.86%, and is down 14.42% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Crude Oil - values, historical data, forecasts and news - updated on July of 2025.

Content

The dataset contains monthly prices for 70 сommodities. Columns description is available in a separate attached file.

Acknowledgements

Data is collected from the official website of The World Bank: Commodity Markets (https://www.worldbank.org/en/research/commodity-markets#1).

Inspiration

Data can be used for time series modelling or time series clustering methods as well as for conducting exploratory data analysis for research papers or any other scientific activity.

This dataset aggregates daily wholesale price data for a wide spectrum of agricultural commodities traded across India’s regulated markets (mandis). It captures minimum, maximum, and modal prices, enabling detailed analysis of price dispersion and volatility over time. Data is sourced directly from the AGMARKNET portal and made available under the National Data Sharing and Accessibility Policy (NDSAP). With over 165,000 views and nearly 400,000 downloads, it’s a cornerstone resource for economists, agronomists, and data scientists studying India’s commodity markets.

This dataset provides daily wholesale minimum, maximum, and modal prices for a wide variety of agricultural commodities across India’s mandis, sourced from the AGMARKNET portal and published on Data.gov.in under NDSAP, with records dating back to 2013 and updated as of 19 May 2025 via a REST API; it includes key fields like Arrival_Date, State, District, Market, Commodity, Variety, Min_Price, Max_Price, and Modal_Price, making it ideal for time-series analysis, price-trend visualizations, and commodity forecasting.

This dataset contains historical data on chili prices and weather conditions in Kota Singkawang. It includes monthly records of various chili prices, shallot and garlic prices, rainfall levels, number of rainy days, and inflation rates. This dataset is a cleaned and merged version of several publicly available datasets from Statistics Indonesia (BPS). See the attached README file for detailed sources and descriptions.

This Data is associated to the paper "PREDICTION OF FOOD COMMODITY PRICES IN KOTA SINGKAWANG USING MACHINE LEARNING: A COMPARATIVE STUDY OF RANDOM FOREST, LINEAR REGRESSION, AND XGBOOST" by Lestari, D. , Bangun, E., Gaol, F. and Matsuo, T.

Natural gas rose to 3.57 USD/MMBtu on July 18, 2025, up 0.73% from the previous day. Over the past month, Natural gas's price has fallen 12.66%, but it is still 67.66% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Natural gas - values, historical data, forecasts and news - updated on July of 2025.

Commodity Services Market Outlook

In 2023, the global commodity services market size was valued at approximately USD 12 billion and is projected to reach USD 18 billion by 2032, growing at a CAGR of 4.5% during the forecast period. The market's growth can be attributed to the increasing globalization of trade, advancements in technology, and heightened demand for risk management and advisory services in volatile markets. These factors are driving the market toward a sustainable growth trajectory.

The primary growth factor for the commodity services market is the growing need for risk management in the face of fluctuating commodity prices. As global markets become more interconnected, the volatility in commodity prices has escalated, necessitating advanced risk management tools and services. Companies across various sectors, including agriculture, energy, and metals, are increasingly leveraging these services to mitigate risks and ensure market stability. These risk management services cover a broad spectrum, from hedging strategies using futures and options to more complex financial instruments.

Another key driver is the technological advancements in commodity trading and brokerage services. The advent of sophisticated trading platforms and algorithms has revolutionized the commodity services market. These technologies enable faster transaction execution, enhanced data analytics, and improved market intelligence, thereby attracting more participants into the market. Furthermore, blockchain technology is being integrated for increased transparency and reduced fraud, which further boosts market confidence and participation.

The increasing demand for specialized research and advisory services also fuels the market's growth. With the complexity of global markets, businesses seek in-depth market analysis, trend forecasting, and strategic advice to make informed decisions. Research and advisory firms provide valuable insights into market dynamics, regulatory changes, and economic indicators, helping companies navigate the intricate landscape of commodity trading. This service segment is seeing robust growth as companies become more dependent on expert guidance to optimize their trading strategies.

Regionally, North America holds a significant share of the commodity services market, driven by its well-established financial markets and advanced technological infrastructure. The region's dominance is expected to continue, supported by the presence of major commodity exchanges and brokerage firms. Meanwhile, the Asia Pacific region is experiencing the fastest growth, primarily due to expanding industrial activities and increasing participation in global trade. The burgeoning economies of China and India, in particular, are key contributors to this regional growth, with their rising demand for various commodities.

Trading and Brokerage Analysis

The trading and brokerage segment is a cornerstone of the commodity services market, providing essential platforms and services for buying and selling various commodities. This segment has evolved significantly with the advent of electronic trading platforms that offer real-time market data, automated trading systems, and enhanced connectivity across global markets. These platforms have democratized access to commodity trading, allowing even small and medium-sized enterprises to participate actively.

In recent years, the role of brokerage firms has expanded beyond mere transaction facilitation to providing comprehensive market analysis, trading recommendations, and personalized investment strategies. Brokerage firms are now leveraging advanced analytics and big data to offer tailored solutions to their clients, enhancing their decision-making capabilities. This trend is particularly prominent in the energy and metals sectors, where market dynamics are highly complex and require specialized expertise.

Moreover, the integration of blockchain technology is poised to transform the trading and brokerage landscape. Blockchain offers unparalleled transparency and security, reducing the risk of fraud and ensuring the integrity of transactions. Several commodity exchanges and brokerage firms are already piloting blockchain-based platforms, which could set a new standard for the industry. This technological shift is expected to attract more institutional investors, further boosting market liquidity and stability.

The trading and brokerage segment also faces challenges, particularly in terms of regulatory compliance and cybersecurity. With increasi

The global commodity trading services market is experiencing robust growth, driven by increasing globalization, fluctuating commodity prices, and the need for efficient supply chain management. The market size in 2025 is estimated at $2 trillion, exhibiting a Compound Annual Growth Rate (CAGR) of 6% between 2025 and 2033. This growth is fueled by several key factors. Firstly, the rising demand for raw materials across various sectors, including metals, energy, and agriculture, is creating lucrative opportunities for commodity trading firms. Secondly, technological advancements in areas like data analytics and blockchain technology are improving transparency, efficiency, and risk management within commodity trading, further stimulating market expansion. Finally, the increasing complexity of global supply chains necessitates the expertise of specialized commodity traders to navigate market volatility and ensure secure and timely delivery of goods. The market is segmented by commodity type (metals, energy, agricultural, and others) and by the size of the businesses served (large enterprises and SMEs). While large enterprises dominate the market currently, the SME segment shows strong potential for future growth as businesses increasingly rely on external expertise for commodity sourcing. The geographical distribution of the commodity trading services market is diverse, with North America, Europe, and Asia Pacific representing the major regions. However, emerging markets in Asia and Africa are showing significant growth potential due to rapid industrialization and rising consumer demand. Competitive pressures within the industry are high, with numerous large multinational corporations vying for market share. These companies, including Vitol, Glencore, Trafigura, Mercuria, and Cargill, possess extensive global networks, strong financial capabilities, and deep expertise in risk management, allowing them to dominate the market. Nevertheless, smaller, specialized trading firms are also finding success by focusing on niche markets or employing innovative trading strategies. The overall outlook for the commodity trading services market remains optimistic, with continued growth expected over the coming years, albeit with some potential challenges related to geopolitical instability and regulatory changes.

This paper provides an empirical reconsideration of evidence for excess co-movement of commodity prices within the framework of univariate and multivariate GARCH(1, 1) models. Alternative formulations of zero excess co-movement are provided, and corresponding score and likelihood ratio tests are developed. Monthly time series data for two sample periods, 1960-85 and 1974-92, on up to nine commodities are used. In contrast to earlier work, only weak evidence of excess co-movement is found.

Wheat rose to 547 USd/Bu on July 18, 2025, up 2.53% from the previous day. Over the past month, Wheat's price has fallen 4.54%, but it is still 0.78% higher than a year ago, 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.

This dataset is designed for the commodity market, featuring over 10,000 manually annotated news headlines. It aims to provide deep insights into news sentiment and its implications for commodity prices. The headlines were collected from various news sources and evaluated by three subject experts over a period of more than 20 years, from 2000 to 2021. Each news item has been assessed across multiple dimensions, including implied price direction (up, down, or constant), whether the news discusses past or future events, and if it involves asset comparisons. This dataset is particularly valuable for developing machine learning models that can understand commodity news, which can then serve as an additional input for both short-term and long-term price forecasting models. It is also useful for creating news-based indicators for commodities. Researchers focused on text analytics and classification problems will find this dataset beneficial, although some classes are highly imbalanced, which may present challenges for machine learning algorithms.

Columns

The dataset includes the following columns:

• Dates: The date of the news headline.
• URL: The URL where the news headline was published.
• News: The actual news headline text.
• Price Direction Up: A binary indicator (1 for Yes, 0 for No) if the news headline suggests an increase in price.
• Price Direction Constant: A binary indicator (1 for Yes, 0 for No) if the news headline suggests a stable price (no change).
• Price Direction Down: A binary indicator (1 for Yes, 0 for No) if the news headline suggests a decrease in price.
• Asset Comparison: A binary indicator (1 for Yes, 0 for No) if the news headline compares different assets.
• Past Information: A binary indicator (1 for Yes, 0 for No) if the news headline refers to past events.
• Future Information: A binary indicator (1 for Yes, 0 for No) if the news headline refers to future events.
• Price Sentiment: The overall sentiment of the gold commodity price based on the headline, categorised as positive, negative, or other.

Distribution

The dataset contains over 10,000 unique news headlines and corresponding metadata. Data files are typically provided in CSV format. Key distribution statistics for some dimensions are as follows:

• Dates: 3,761 unique values.
• URL: 10,570 unique values.
• News: 10,570 unique values.
• Price Direction Up: 6,158 headlines do not imply up, 4,412 imply up.
• Price Direction Constant: 10,126 headlines do not imply constant, 444 imply constant.
• Price Direction Down: 6,658 headlines do not imply down, 3,912 imply down.
• Asset Comparison: 8,569 headlines do not compare assets, 2,001 compare assets.
• Past Information: 318 headlines do not discuss past information, 10,252 discuss past information.
• Future Information: 10,251 headlines do not discuss future information, 319 discuss future information.
• Price Sentiment: Approximately 42% positive, 36% negative, and 22% other sentiment.

Usage

This dataset is ideally suited for:

• Developing machine learning models that understand commodity news for price forecasting.
• Creating news-based indicators for commodity markets.
• Evaluating text classification models in the context of news analytics.
• Research into the impact of news on commodity market volatility.

Coverage

The dataset has a global regional coverage. It spans a significant time range of over 20 years, from 2000 to 2021, with headlines collected across this period. There are no specific demographic notes beyond the focus on gold commodity news.

License

CC-BY-NC

Who Can Use It

This dataset is primarily intended for:

• Researchers and practitioners specialising in news analytics for commodities, who can leverage it for building predictive models.
• Data scientists and machine learning engineers working on text classification and natural language processing tasks, especially those dealing with imbalanced datasets.
• Financial analysts and market strategists interested in incorporating news sentiment into their commodity market analysis.

Dataset Name Suggestions

• Gold News Sentiment Analysis Dataset
• Commodity Market News Classifier
• Financial News Headline Sentiment
• Gold Price Direction News Data
• Annotated Commodity News for ML

Attributes

Original Data Source: Sentiment Analysis of Commodity News (Gold)

Sharp economic volatility, the continued effects of high interest rates and mixed sentiment among investors created an uneven landscape for stock and commodity exchanges. While trading volumes soared in 2020 due to the pandemic and favorable financial conditions, such as zero percent interest rates from the Federal Reserve, the continued effects of high inflation in 2022 and 2023 resulted in a hawkish pivot on interest rates, which curtailed ROIs across major equity markets. Geopolitical volatility amid the Ukraine-Russia and Israel-Hamas wars further exacerbated trade volatility, as many investors pivoted away from traditional equity markets into derivative markets, such as options and futures to better hedge on their investment. Nonetheless, the continued digitalization of trading markets bolstered exchanges, as they were able to facilitate improved client service and stronger market insights for interested investors. Revenue grew an annualized 0.1% to an estimated $20.9 billion over the past five years, including an estimated 1.9% boost in 2025. A core development for exchanges has been the growth of derivative trades, which has facilitated a significant market niche for investors. Heightened options trading and growing attraction to agricultural commodities strengthened service diversification among exchanges. Major companies, such as CME Group Inc., introduced new tradeable food commodities for investors in 2024, further diversifying how clients engage in trades. These trends, coupled with strengthened corporate profit growth, bolstered exchanges’ profit. Despite current uncertainty with interest rates and the pervasive fear over a future recession, the industry is expected to do well during the outlook period. Strong economic conditions will reduce investor uncertainty and increase corporate profit, uplifting investment into the stock market and boosting revenue. Greater levels of research and development will expand the scope of stocks offered because new companies will spring up via IPOs, benefiting exchange demand. Nonetheless, continued threat from substitutes such as electronic communication networks (ECNs) will curtail larger growth, as better technology will enable investors to start trading independently, but effective use of electronic platforms by incumbent exchange giants such as NASDAQ Inc. can help stem this decline by offering faster processing via electronic trade floors and prioritizing client support. Overall, revenue is expected to grow an annualized 3.5% to an estimated $24.8 billion through the end of 2031.

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.

General Index provides robust, reliable price transparency for the world’s commodity markets with quick and convenient access through a single desktop.

In economic studies and popular media, interest rates are routinely cited as a major factor behind commodity price fluctuations. At the same time, the transmission channels are far from transparent, leading to long-running debates on the sign and magnitude of interest rate effects. Purely empirical studies struggle to address these issues because of the complex interactions between interest rates, prices, supply changes, and aggregate demand. To move this debate to a solid footing, we extend the competitive storage model to include stochastically evolving interest rates. We establish general conditions for existence and uniqueness of solutions and provide a systematic theoretical and quantitative analysis of the interactions between interest rates and prices.

The global commodity trading services market is a highly concentrated industry dominated by major players like Vitol, Glencore, Trafigura, and Cargill. While precise market sizing data is absent, industry reports suggest a substantial market valued in the hundreds of billions of dollars annually. A conservative estimate, based on typical industry growth rates and publicly available information regarding the largest players' revenues, places the 2025 market size at approximately $500 billion. This sector is characterized by a moderate Compound Annual Growth Rate (CAGR), projected to be around 4-5% from 2025 to 2033, driven primarily by increasing global demand for raw materials, particularly in emerging economies experiencing rapid industrialization. Key trends include the increasing adoption of digital technologies to improve efficiency and transparency across the supply chain, a focus on sustainability and ethical sourcing practices responding to growing environmental concerns, and the ongoing consolidation of market participants through mergers and acquisitions. However, the market faces constraints such as geopolitical instability, volatile commodity prices, and increasing regulatory scrutiny related to environmental, social, and governance (ESG) factors. Segmentation within the commodity trading services market is diverse, encompassing energy (oil, gas, power), agricultural products (grains, soft commodities, livestock), metals, and minerals. Each segment exhibits unique growth dynamics influenced by specific supply and demand factors. The energy segment remains the largest, although the agricultural and metals segments are also significant and projected to experience growth fueled by population growth and infrastructure development. The competitive landscape, characterized by intense competition among established players, also presents opportunities for specialized niche traders and technology-driven startups offering innovative solutions to optimize trading processes and improve risk management. Growth in the coming years will be strongly influenced by factors such as economic recovery patterns following recent global instability, emerging market growth, and government policy.

Commodity Management Software Market Outlook

The global commodity management software market size was valued at approximately USD 1.5 billion in 2023 and is projected to reach around USD 3.2 billion by 2032, showcasing a robust CAGR of 8.9% during the forecast period. This impressive growth is primarily driven by increasing demand for efficient supply chain management, rising commodity price volatility, and the integration of advanced technologies such as AI and blockchain.

The demand for commodity management software is significantly influenced by the need for enhanced supply chain visibility and risk management. As global trade continues to expand, companies are increasingly seeking advanced solutions to mitigate risks associated with commodity price fluctuations and supply chain disruptions. The ability of commodity management software to provide real-time data analytics and insights is a major growth factor, helping organizations make informed decisions and optimize their operations.

Another critical growth factor driving the commodity management software market is the adoption of advanced technologies such as artificial intelligence (AI) and blockchain. These technologies enhance the capabilities of commodity management software by enabling predictive analytics, improving transaction transparency, and automating complex processes. AI-driven analytics can forecast market trends and commodity prices with higher accuracy, while blockchain ensures secure and transparent transactions, reducing the risk of fraud.

Additionally, the increasing regulatory requirements and compliance standards in various industries are fueling the adoption of commodity management software. Governments and regulatory bodies are imposing stringent regulations to ensure transparency and accountability in commodity trading. This has led organizations to invest in robust software solutions that can help them adhere to these regulations and avoid hefty penalties. The software's ability to streamline compliance processes and provide comprehensive reporting is a significant advantage driving market growth.

Regionally, North America dominates the commodity management software market, accounting for the largest market share. This is attributed to the presence of major commodity trading hubs and advanced technological infrastructure in the region. Europe follows closely, driven by stringent regulatory frameworks and a strong focus on sustainability. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, fueled by rapid industrialization, increasing commodity trading activities, and rising adoption of digital solutions in emerging economies such as China and India.

Component Analysis

The commodity management software market is segmented by component into software and services. The software segment holds the largest market share, driven by the increasing need for advanced software solutions that offer real-time data analytics, risk management, and supply chain optimization. The software segment encompasses various applications, including trading and risk management (TRM), procurement, logistics, and inventory management. These applications enable organizations to streamline their operations, reduce costs, and improve decision-making processes.

Trading and risk management (TRM) software is a critical component of the commodity management software market. It helps organizations manage their trading activities, mitigate risks, and ensure compliance with regulatory requirements. The growing volatility in commodity prices and increasing regulatory scrutiny have led to a surge in demand for TRM software. This software provides real-time market data, advanced analytics, and risk assessment tools, enabling organizations to make informed trading decisions and minimize risks.

Procurement software is another vital component, helping organizations manage their procurement processes more efficiently. It offers tools for supplier management, contract management, and procurement analytics, allowing organizations to optimize their procurement strategies, reduce costs, and enhance supplier relationships. The increasing complexity of global supply chains and the need for efficient procurement processes are driving the demand for procurement software.

The services segment includes consulting, implementation, and support services, which are essential for the successful deployment and operation of commodity management software. Consulting services help organizations assess their requireme

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