United States Agricultural Price Index: Received by Farmers: Food Commodities data was reported at 88.800 2011=100 in Oct 2018. This records a decrease from the previous number of 90.600 2011=100 for Sep 2018. United States Agricultural Price Index: Received by Farmers: Food Commodities data is updated monthly, averaging 101.000 2011=100 from Jan 2010 (Median) to Oct 2018, with 106 observations. The data reached an all-time high of 126.000 2011=100 in Apr 2014 and a record low of 81.000 2011=100 in Feb 2010. United States Agricultural Price Index: Received by Farmers: Food Commodities data remains active status in CEIC and is reported by National Agricultural Statistics Service. The data is categorized under Global Database’s United States – Table US.I043: Agricultural Price Index.

GSCI rose to 546.69 Index Points on July 16, 2025, up 0.36% from the previous day. Over the past month, GSCI's price has fallen 5.53%, and is down 3.83% 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.

Graph and download economic data for Export Price Index (End Use): Agricultural Commodities (IQAG) from Mar 1985 to May 2025 about end use, agriculture, exports, commodities, price index, indexes, price, and USA.

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.

The balanced annual panel data for 32 sub-Saharan countries from 2000 to 2020 was used for this study. The countries and period of study was informed by availability of data of interest. Specifically, 11 agricultural commodity dependent countries, 7 energy commodity dependent countries and 14 mineral and metal ore dependent countries were selected (Appendix 1). The annual data comprised of agricultural commodity prices, global oil prices (GOP) and mineral and metal ore prices, export value of the dependent commodity, total export value of the country, real GDP (RGDP) and terms of trade (TOT). The data for export value of the dependent commodity, total export value of the country, real GDP and terms of trade was sourced from world bank database (World Development Indicators). Data for agricultural commodity prices, global oil prices (GOP) and mineral and metal ore prices are obtained from World Bank commodity price data portal. This study used data from global commodity prices from the World Bank's commodity price data site since the error term (endogenous) is connected with each country's commodity export price index. The pricing information covered agricultural products, world oil, minerals, and metal ores. One benefit of adopting international commodity prices, according to Deaton and Miller (1995), is that they are frequently unaffected by national activities. The utilization of studies on global commodity prices is an example (Tahar et al., 2021). The commodity dependency index of country i at time i was computed as the as the ratio of export value of the dependent commodity to the total export value of the country. The commodity price volatility is estimated using standard deviation from monthly commodity price index to incorporate monthly price variation (Aghion et al., 2009). This approach addresses challenges of within the year volatility inherent in the annual data. In footstep of Arezki et al. (2014) and Mondal & Khanam (2018), standard deviation is used in this study as a proxy of commodity price volatility. The standard deviation is used because of its simplicity and it is not conditioned on the unit of measurement.

Wheat fell to 541.48 USd/Bu on July 14, 2025, down 0.65% from the previous day. Over the past month, Wheat's price has risen 0.93%, and is up 1.69% compared to the same time last year, 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 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.

Succeed in the agricultural commodities market place with LSEG's Agriculture Data, including global cash price data, agriculture flows, and more.

Graph and download economic data for Producer Price Index by Commodity: Farm Products: Soft Red Winter Wheat (WPU01210104) from Jan 1947 to Jun 2025 about wheat, agriculture, commodities, PPI, inflation, price index, indexes, price, and USA.

As an essential part of daily life, the drastic fluctuations in agricultural commodity prices significantly impact producers’ motivation and consumers’ quality of life, further exacerbating market uncertainty and unsustainability. The ability to scientifically and effectively predict agricultural commodity prices is of great significance for the rational deployment of market mechanisms, the timely adjustment of supply chains, and the promotion of food policy adjustments. This paper proposes a sustainable hybrid model SV-PSO-BiLSTM which integrates Seasonal-Trend decomposition procedure based on Loess (STL), Variational Mode Decomposition (VMD), Particle Swarm Optimization (PSO), and Bidirectional Long Short-Term Memory (BiLSTM) neural networks. This innovative approach first performs seasonal decomposition of the original data using the STL method, then applies the VMD method for double decomposition of the residual components, reconstructs the data based on sample entropy, and finally predicts agricultural commodity market prices using the BiLSTM network model optimized by the PSO algorithm. This paper investigates the market price dynamics of four agricultural commodities (chili, garlic, ginger, and pork) and one agricultural financial derivative (soybean futures). The experimental results indicate that the proposed SV-PSO-BiLSTM hybrid model achieves average values of 0.2241 for root mean square error (RMSE), 0.1665 for mean absolute error (MAE), 0.0207 for mean absolute percentage error (MAPE), and 0.9851 for the coefficient of determination (R2). These results surpass those of other comparative models, demonstrating stronger generalization, reliability, and stability. The research findings can provide effective guidance for the reasonable regulation of agricultural commodity market prices and further promote the healthy and sustainable development of the agricultural commodity industry.

Nepal Wholesale Price Index: Annual: Agricultural Commodities (AC) data was reported at 385.100 1999-2000=100 in 2018. This records a decrease from the previous number of 386.100 1999-2000=100 for 2017. Nepal Wholesale Price Index: Annual: Agricultural Commodities (AC) data is updated yearly, averaging 202.000 1999-2000=100 from Jul 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 386.100 1999-2000=100 in 2017 and a record low of 98.200 1999-2000=100 in 2001. Nepal Wholesale Price Index: Annual: Agricultural Commodities (AC) data remains active status in CEIC and is reported by Nepal Rastra Bank. The data is categorized under Global Database’s Nepal – Table NP.I0032: Wholesale Price Index: 1999-2000=100: Annual.

The objective of the project was to provide econometric analysis and theory for modelling energy and soft commodity prices. This necessitated data analysis and modelling together with theoretical econometrics, dealing with the specific stylised facts of commodity prices. In order to analyse energy and soft commodity prices, the determination of spot energy prices in regulated markets was first considered, from the point of view of the regulator. Direct data analysis of futures commodity prices was then undertaken, resulting in the collection of an extensive dataset of most traded futures commodity prices at a daily frequency, covering 16 different commodities over a 10-year period.

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.

Overview
The March edition of Agricultural commodities contains ABARES' latest outlook for Australia's key agricultural commodities to 2022-23. The report provides commodity production and export forecasts.

It also includes articles and boxes that cover: Farm performance - broadacre and dairy farms; Australia's competitiveness in the fresh produce export market; Changes to China's grain policy; The Peru FTA; Market diversity of Australian wine exports; and, Trends in Australian cotton and horticulture production.

Key Issues

Commodity production forecasts • The gross value of farm production is forecast to decline by 5 per cent to $59 billion in 2017-18, reflecting an assumed return to average seasonal conditions, before increasing by 3 per cent to $61 billion in 2018-19. ◦ The gross value of farm production nevertheless remains high. If realised, the forecast value of farm production in 2018-19 would be around 11 per cent higher than the average of $55 billion over the five years to 2016-17. ◦ The gross value of farm production is forecast to grow steadily over the outlook period to around $63 billion by 2022-23 (in 2017-18 dollars). Strong demand for livestock and some horticultural products, and improved productivity in cropping, are expected to support growth.

• The gross value of livestock production is forecast to increase by around 3 per cent to $29.6 billion in 2018-19, following a forecast increase of 2 per cent in 2017-18. ◦ The value of lamb, wool and dairy production is forecast to contribute strongly to growth in the value of livestock production in 2018-19 (as in 2017-18), driven by strong export demand (particularly from China). ◦ The value of beef and veal production is forecast to fall slightly, as a decline in export prices offsets an increase in the volume of beef produced. Despite the fall in price, returns are well above the historical average and supportive of farm profitability.

• The gross value of crop production is forecast to increase by 3 per cent to $31 billion in 2018-19, after a forecast decline of 11 per cent in 2017-18. ◦ The decline in 2017-18 follows record production of wheat, barley and canola in 2016-17 due to very favourable seasonal conditions during winter and spring. ◦ In 2018-19 the value of wheat, coarse grains and canola production is forecast to underpin growth in the value of total crop production. Wheat yields are assumed to improve (and to be around trend) following the frosts, above average temperatures and dry conditions during the winter of 2017. Area planted to coarse grains is forecast to increase due to strong global demand for feed and rotational constraints to planting pulses. Canola production is expected to increase as prices become comparatively favourable to the low coarse grain and falling pulse prices.

Commodity export forecasts • Export earnings from farm commodities are forecast to be $48.5 billion in 2018-19, slightly higher than the forecast $47 billion in 2017-18. • Export earnings for fisheries products are forecast to increase by 1 per cent in 2018-19 to $1.5 billion, after increasing by a forecast 5 per cent in 2017-18. • In 2018-19 export earnings are forecast to rise for canola (22 per cent), cotton (17 per cent), barley (12 per cent), lamb (9 per cent), wool (7 per cent), wheat (6 per cent), rock lobster (4 per cent) and live feeder/slaughter cattle (1 per cent). ◦ Forecast higher prices are a strong contributor to growth in export earnings. In Australian dollar terms, export prices of cotton (11 per cent), wheat (9 per cent), wool (4 per cent), barley (4 per cent), mutton (4 per cent), rock lobster (3 per cent), lamb (2 per cent) and cheese (1 per cent) are forecast to increase in 2018-19.

• Export earnings are forecast to decline in 2018-19 for chickpeas (54 per cent), sugar (11 per cent) and wine (2 per cent). Export earnings for beef and veal, cheese and mutton are forecast to be unchanged. ◦ The decline in export earnings for these commodities is driven by a fall in export prices. Prices for chickpeas (27 per cent), sugar (11 per cent) and wine (2 per cent) are forecast to fall due to increasing global supply and competition. Prices for beef and veal (3 per cent), live feeder/slaughter cattle (3 per cent) and canola (1 per cent) are also forecast to decline.

• In 2022-23 the value of farm exports is projected to be around $49.6 billion (in 2017-18 dollars), 8 per cent higher than the average of $46 billion over the five years to 2016-17 in real terms. ◦ The value of crop exports is projected to be $25.2 billion in 2022-23 (in 2017-18 dollars), 2.4 per cent higher than the average of $24.6 billion over the five years to 2016-17 in real terms. The value of livestock exports is projected to be $24.4 billion in 2022-23 (in 2017-18 dollars), 15 per cent higher than the average of $21 billion over the five years to 2016-17 in real terms.

Assumptions underlying this set of commodity forecasts

Forecasts of commodity production and exports are based on global and domestic demand and supply assumptions.

• On the demand side, stronger world economic growth will translate to higher per person incomes in most of Australia's export markets, supporting stronger demand. ◦ World economic growth is assumed to be 3.7 per cent in 2018 and 2019. From 2020 to 2023 economic growth is assumed to average 3.6 per cent. ◦ Economic growth in Australia is assumed to be 3 per cent in 2018-19 and over the medium term to 2022-23. ◦ The Australian dollar is assumed to average US76 cents in 2018-19, slightly lower than the forecast average of US78 cents in 2017-18. It is assumed to depreciate further to US74 cents in 2019-20 and remain at that level over the outlook period.

• On the supply side, agricultural production is assumed to be consistent with average seasonal conditions in Australia and globally. ◦ Seasonal conditions have significant implications for crop yields and livestock production cycles.

Global Agricultural Commodity market size is expected to reach $293.91 billion by 2029 at 5.8%, segmented as by soybeans, non-gmo soybeans, gmo soybeans

United States Export Price Index: Non Agricultural Commodities data was reported at 94.900 1990=100 in Dec 2001. This records a decrease from the previous number of 95.300 1990=100 for Nov 2001. United States Export Price Index: Non Agricultural Commodities data is updated monthly, averaging 95.700 1990=100 from Dec 1988 (Median) to Dec 2001, with 157 observations. The data reached an all-time high of 100.800 1990=100 in Jun 1995 and a record low of 89.500 1990=100 in Dec 1988. United States Export Price Index: Non Agricultural Commodities data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.I034: Import and Export Price Index: 1995=100: By End Use.

This data set contains Ontario feed grain prices collected by University of Guelph, Ridgetown Campus. The dataset includes daily prices of agricultural commodities at individual elevators in Ontario. Daily highs and lows are given for each commodity, as well as, daily Bank of Canada exchange rates.This dataset includes data from January 1, 2024 to June 30, 2024. Data for July 1, 2024 to December 31, 2024 will be added as it becomes available.

Lumber rose to 659.07 USD/1000 board feet on July 17, 2025, up 0.54% from the previous day. Over the past month, Lumber's price has risen 7.05%, and is up 33.25% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Lumber - values, historical data, forecasts and news - updated on July of 2025.

The global commodities trading services market, valued at $4226.9 million in 2025, is projected to experience robust growth, driven by increasing global demand for raw materials across various sectors. The 5.5% CAGR from 2025 to 2033 indicates a significant expansion, fueled by several key factors. Growth in emerging economies, particularly in Asia-Pacific, is a primary driver, coupled with rising industrialization and infrastructure development. The energy sector, encompassing oil, gas, and related products, is expected to dominate the market, followed by metals trading. However, increasing regulatory scrutiny and price volatility in commodity markets represent key challenges. Furthermore, the agricultural commodities segment is poised for considerable growth due to population increases and shifting dietary patterns. The market is segmented by type (metals, energy, agricultural, and others) and application (large enterprises and SMEs), with large enterprises currently dominating. Competitive dynamics are shaped by the presence of major players like Vitol, Glencore, and Trafigura, all vying for market share through strategic partnerships, technological advancements, and geographical expansion. The increasing adoption of digital technologies for efficient trading and risk management is further shaping the market landscape. The forecast period (2025-2033) reveals substantial growth opportunities across all segments. The North American and European markets are established strongholds, but significant expansion is anticipated in Asia-Pacific, driven by China and India's burgeoning economies. The market's future hinges on several factors, including geopolitical stability, technological innovation in trading platforms, and the implementation of sustainable practices across the commodity supply chain. Effective risk management strategies and adaptation to evolving regulatory frameworks will be critical for success in this dynamic market. Companies are focusing on enhancing their logistical capabilities and strengthening their relationships with producers and consumers to secure a competitive edge. The focus on sustainability and responsible sourcing will play an increasingly important role in shaping the future of the commodities trading services market.