GSCI rose to 551.62 Index Points on July 18, 2025, up 0.44% from the previous day. Over the past month, GSCI's price has fallen 5.06%, and is down 0.76% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. GSCI Commodity Index - values, historical data, forecasts and news - updated on July of 2025.

Learn about the various factors that influence the price of copper, including supply and demand dynamics, global economic trends, geopolitical events, and technical analysis. Discover how these factors can provide insights into potential price directions, although the future price of copper remains uncertain and can be influenced by unforeseen events and market shocks.

The World Bank’s Commodity Price historical data and forecasts are published quarterly, in January, April, July and October. The price forecasts go up to 2030. Topics: Agriculture & Rural Development

In 2025, the price of platinum is forecast to hover around 1,150 U.S. dollars per troy ounce. Meanwhile, the cost of per troy ounce of gold is expected to amount to 1,700 U.S. dollars.

Precious metals

Precious metals are counted among the most valuable commodities worldwide. The most well known such metals are gold, silver and the platinum group metals. A precious metal can be used as an industrial commodity or as an investment. The major areas of application include the following sectors: technology, car-making, industrial manufacturing and jewelry making. Furthermore, gold and silver are used as coinage metals, and gold reserves are held by the central banks of many countries worldwide in order to store value or for use as a redemption medium. The idea behind this procedure is that gold reserves will help secure and stabilize the countries’ respective currencies. At 8,100 tons, the United States is the country with the most extensive stock of gold. It is kept in an underground vault at the New York Federal Reserve Bank.

Russia, the United States, Canada, South Africa and China are the main producers of precious metals. Silver is the most abundant of the metals, followed by gold and palladium. Barrick Gold is the world’s largest gold mining company. The Toronto-based firm produced some five million ounces of gold in 2020. The leading silver producers include Mexico-based Fresnillo, Poland’s KGHM Polska Miedž and the mining giant Glencore. Anglo Platinum and Impala are the key mining companies to produce platinum group metals.

In 2023, Silver prices are expected to settle at around 23.5 U.S. dollars per troy ounce. It is expected to remain the precious metal with the lowest value per ounce. The price of gold is forecast to drop to around 1,663 U.S. dollars per ounce, making it the most expensive precious metal in 2023.

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

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.

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.

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.

Graph and download economic data for Global Price Index of All Commodities (PALLFNFINDEXQ) from Q1 2003 to Q2 2025 about World, commodities, price index, indexes, and price.

This data product provides three Excel file spreadsheet models that use futures prices to forecast the U.S. season-average price received and the implied CCP for three major field crops (corn, soybeans, and wheat).

Using Futures Prices to Forecast the Season-Average Price and Counter-Cyclical Payment Rate for Corn, Soybeans, and Wheat

Farmers and policymakers are interested in the level of counter-cyclical payments (CCPs) provided by the 2008 Farm Act to producers of selected commodities. CCPs are based on the season-average price received by farmers. (For more information on CCPs, see the ERS 2008 Farm Bill Side-By-Side, Title I: Commodity Programs.)

This data product provides three Excel spreadsheet models that use futures prices to forecast the U.S. season-average price received and the implied CCP for three major field crops (corn, soybeans, and wheat). Users can view the model forecasts or create their own forecast by inserting different values for futures prices, basis values, or marketing weights. Example computations and data are provided on the Documentation page.

Spreadsheet Models

For each of the three major U.S. field crops, the Excel spreadsheet model computes a forecast for:

1. the national-level season-average price received by farmers and
2. the implied counter-cyclical payment rate.

Note: the model forecasts are not official USDA forecasts. See USDA's World Agricultural Supply and Demand Estimates for official USDA season-average price forecasts. See USDA's Farm Service Agency information for official USDA CCP rates.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Webpage with links to Excel files For complete information, please visit https://data.gov.

Corn rose to 408.99 USd/BU on July 18, 2025, up 1.74% from the previous day. Over the past month, Corn's price has fallen 5.60%, but it is still 1.05% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Corn - values, historical data, forecasts and news - updated on July of 2025.

BCC Forecast: Commodity Price: Avg: Crude Oil: Brent data was reported at 63.000 USD/Barrel in 2021. This records a decrease from the previous number of 65.000 USD/Barrel for 2020. BCC Forecast: Commodity Price: Avg: Crude Oil: Brent data is updated yearly, averaging 65.500 USD/Barrel from Dec 2012 (Median) to 2021, with 10 observations. The data reached an all-time high of 112.000 USD/Barrel in 2012 and a record low of 44.000 USD/Barrel in 2016. BCC Forecast: Commodity Price: Avg: Crude Oil: Brent data remains active status in CEIC and is reported by Central Bank of Chile. The data is categorized under Global Database’s Chile – Table CL.P003: Commodity Price: Forecast: Central Bank of Chile.

Commodity Coffee Beans Market Outlook

The global commodity coffee beans market size was valued at approximately USD 102.5 billion in 2023 and is projected to reach USD 157.4 billion by 2032, growing at a compound annual growth rate (CAGR) of 4.9% during the forecast period. The market's growth is attributed to increasing coffee consumption, shifting consumer preferences towards specialty coffee, and the expanding application areas in various industries. Coffee remains one of the most traded commodities worldwide, driven by an ever-growing base of coffee enthusiasts and the cultural significance of coffee consumption across different regions.

One of the primary growth factors for the commodity coffee beans market is the rising coffee consumption globally. More consumers are adopting coffee as a staple beverage, influenced by lifestyle changes, urbanization, and the proliferation of coffee culture. The entry of specialty coffee shops and the rising trend of home brewing have significantly contributed to this increase in demand. Additionally, the younger demographic, more inclined towards artisanal and high-quality coffee, is further propelling the market forward. This segment of consumers is willing to pay a premium for unique and ethically sourced coffee beans, thus driving the growth of the market.

Technological advancements in coffee cultivation and processing have also played a crucial role in enhancing the market. Innovations in agricultural practices, such as precision farming and sustainable farming techniques, have improved the yield and quality of coffee beans. Furthermore, advancements in processing technologies have enabled producers to offer a diverse range of coffee products with consistent quality. This has not only enhanced production capabilities but also opened new opportunities for product differentiation in an increasingly competitive market. The advent of blockchain technology in the supply chain has further ensured transparency and traceability, which are increasingly important to conscientious consumers.

Another significant driver of market growth is the expanding application of coffee beans beyond traditional beverages. The use of coffee in pharmaceuticals, cosmetics, and food products has widened the scope of the market. Coffee beans are known for their antioxidant properties, which have been harnessed in skincare products and dietary supplements. This diversification into new application areas is expected to sustain the market's growth momentum. Furthermore, the development of coffee-infused products, such as energy drinks and snacks, continues to capture consumer interest, thereby expanding the market further.

The rise of Coffee E Commerce Platform has significantly transformed the way consumers purchase coffee, offering unparalleled convenience and access to a wide variety of coffee products. These platforms provide coffee enthusiasts with the ability to explore and purchase specialty and artisanal coffee from around the world, right from the comfort of their homes. With detailed product descriptions, customer reviews, and the ease of comparison, consumers are empowered to make informed decisions about their coffee purchases. Furthermore, subscription services offered by these platforms ensure a steady supply of fresh coffee, catering to the growing demand for high-quality and ethically sourced beans. As the digital landscape continues to evolve, Coffee E Commerce Platforms are expected to play a pivotal role in shaping the future of the coffee market, driving growth and innovation in the industry.

The regional outlook of the commodity coffee beans market is diverse, with varying consumption patterns and growth rates across different regions. North America and Europe remain dominant markets due to their established coffee culture and high consumption rates. Meanwhile, the Asia Pacific region is emerging as a significant growth area, driven by increasing disposable incomes and the growing popularity of coffee among younger consumers. Latin America, as a major coffee-producing region, continues to play a crucial role in supplying the global market, while also experiencing growing domestic consumption. The Middle East & Africa region, although smaller in market size, is witnessing a steady rise in coffee consumption, influenced by changing consumer preferences and increasing urbanization.

Type Analysis

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.

DJ Commodity Zinc 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

Learn about the key factors that influence the forecast for copper as a commodity, including demand and supply dynamics, economic and industrial growth, global trade and politics, technological advancements, and financial markets. Discover the positive outlook for copper's future, while keeping in mind the potential uncertainties and the need for monitoring evolving market conditions.

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.

SGI Commodities Optimix TR index Sees Moderate Growth Ahead.

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

Global Commodities Trading Services market size 2025 was XX Million. Commodities Trading Services Industry compound annual growth rate (CAGR) will be XX% from 2025 till 2033.

Futures Trading Service Market Outlook

The global futures trading service market size was valued at USD 5.2 billion in 2023 and is projected to reach USD 10.8 billion by 2032, growing at a CAGR of 8.5% during the forecast period. The significant growth in market size can be attributed to increased trading activities, technological advancements in trading platforms, and rising interest from individual and institutional investors alike.

A major growth factor for the futures trading service market is the rising prevalence of advanced trading platforms and technologies. Technological advancements have made futures trading more accessible and efficient, enabling traders to execute complex strategies with greater ease. The integration of artificial intelligence and machine learning into trading algorithms has also enhanced decision-making processes, resulting in improved trading outcomes and increased market participation.

Another key driver is the increased participation of institutional investors. As financial markets become more interconnected, institutional investors are increasingly turning to futures trading to hedge against market volatility and optimize their portfolios. The availability of diverse asset classes within futures trading, including commodities, financials, and indices, provides these investors with a wide range of options to manage their risk exposure effectively.

Moreover, the growing interest among individual investors is fueling market expansion. The democratization of trading platforms has lowered entry barriers, allowing retail traders to participate in futures markets. Educational resources and advisory services provided by brokerage firms further support individual investors in navigating the complexities of futures trading, thereby contributing to market growth.

Commodity Services play a pivotal role in the futures trading market, offering a wide range of opportunities for both hedgers and speculators. These services encompass the trading of various commodities such as agricultural products, energy resources, and precious metals. The inherent volatility in commodity prices makes futures contracts an attractive tool for managing risk and securing price stability. As global demand for commodities continues to rise, driven by factors like population growth and industrialization, the importance of robust commodity services in futures trading becomes increasingly evident. These services not only facilitate efficient price discovery but also provide a platform for market participants to capitalize on price movements and achieve their financial objectives.

In terms of regional outlook, North America holds the largest market share due to the presence of major financial institutions and advanced trading infrastructure. The Asia Pacific region is expected to witness the highest growth rate, driven by increasing economic development, rising disposable incomes, and the expansion of financial markets in countries like China and India. Europe also shows significant potential, with well-established financial hubs such as London and Frankfurt contributing to market growth.

Service Type Analysis

The futures trading service market can be segmented by service type into brokerage services, trading platforms, advisory services, and others. Brokerage services dominate the market, providing essential intermediary functions that facilitate trading activities. These services are crucial for both individual and institutional investors, offering benefits such as access to diverse markets, real-time data, and personalized customer support. The competitive landscape among brokerage firms is intense, with key players continuously enhancing their offerings to attract and retain clients.

Trading platforms are another significant segment within the futures trading service market. These platforms offer a suite of tools and features that enable traders to execute trades, monitor market conditions, and analyze trends. The evolution of trading platforms from desktop-based applications to web-based and mobile solutions has made it easier for traders to engage with the market anytime and anywhere. Features such as automated trading, advanced charting, and customizable interfaces are driving the adoption of these platforms among traders.

Advisory services play a critical role in guiding investors through the complexities of futures trading. These services provide expert anal

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 Ex Energy Index: A Reliable Indicator of Commodity Market Health?

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