Tradefeeds Commodity Prices API enables you to get commodity prices data of the major commodity asset types like energy commodities, metals, industrial commodities, agricultural commodities and livestock commodities. Each commodity asset type has a different historical coverage. A commodity within its commodity asset type has not the same historical coverage as another commodity from the group. For example, within the group of energy commodities, crude oil has a historical coverage of 34 years while coal of only 13 years. Tradefeeds offers commodity prices data either via JSON REST API, or via downloadable databases in CSV or Excel format.

If you are interested to learn more, check out the company website: https://tradefeeds.com/commodities-prices-api/

Real-time oil and energy commodity price data feed

Quick Stats API is the programmatic interface to the National Agricultural Statistics Service's (NASS) online database containing results from the 1997, 2002, 2007, and 2012 Censuses of Agriculture as well as the best source of NASS survey published estimates. The census collects data on all commodities produced on U.S. farms and ranches, as well as detailed information on expenses, income, and operator characteristics. The surveys that NASS conducts collect information on virtually every facet of U.S. agricultural production.

Commodity Hedging APIs for Corporate Banking Market Outlook

According to our latest research, the global Commodity Hedging APIs for Corporate Banking market size reached USD 1.96 billion in 2024, driven by a rising demand for advanced risk mitigation tools and seamless integration in digital banking platforms. The market is projected to register a robust CAGR of 13.7% during the forecast period, with the market size expected to reach USD 5.62 billion by 2033. This growth is primarily fueled by the increasing volatility in commodity prices, digitization of banking infrastructure, and the expanding adoption of API-driven solutions for enhanced corporate treasury management.

One of the most significant growth factors for the Commodity Hedging APIs for Corporate Banking market is the escalating volatility in global commodity prices, which has heightened the necessity for sophisticated risk management solutions among corporates. As businesses face unpredictable fluctuations in energy, metals, agricultural products, and other commodities, the need for real-time, automated, and data-driven hedging strategies has become paramount. APIs facilitate seamless integration of hedging functionalities into existing banking and treasury systems, allowing corporates to react swiftly to market changes, optimize their risk exposure, and safeguard profit margins. This critical requirement for agility and resilience in treasury operations is a key driver propelling market expansion.

Another core driver is the rapid digital transformation sweeping across the banking and financial services sector. Corporate banks are under increasing pressure to modernize their technology stacks and offer clients innovative, value-added services. The deployment of Commodity Hedging APIs enables banks to provide clients with real-time access to market data, automated trading and execution, and comprehensive portfolio management tools. This not only enhances customer experience but also streamlines internal processes, reduces operational costs, and opens up new revenue streams. As regulatory demands become more stringent and clients demand greater transparency and efficiency, API-based solutions are emerging as the backbone of next-generation corporate banking platforms.

Furthermore, the proliferation of cloud computing and advancements in API security are catalyzing the adoption of Commodity Hedging APIs among both large enterprises and SMEs. Cloud-based APIs offer scalability, flexibility, and lower upfront investment, making them attractive for organizations seeking to digitize their treasury functions without significant infrastructure overhaul. Enhanced security protocols and compliance features embedded within these APIs also address concerns around data privacy and regulatory adherence, encouraging broader market penetration. This technological evolution, combined with growing awareness of the strategic value of proactive risk management, is expected to sustain the market’s upward trajectory.

From a regional perspective, North America currently leads the global Commodity Hedging APIs for Corporate Banking market, accounting for a significant share due to the presence of major financial institutions, advanced technological infrastructure, and a mature commodities trading ecosystem. Europe follows closely, with increasing regulatory focus on transparency and risk management driving adoption. The Asia Pacific region is anticipated to witness the fastest growth, propelled by the rapid expansion of digital banking, increasing commodity trade volumes, and supportive government initiatives aimed at modernizing financial markets. Latin America and the Middle East & Africa are also emerging as promising markets, though adoption is somewhat constrained by infrastructural and regulatory challenges.

Component Analysis

The Commodity Hedging APIs for Corporate Banking market by component is segmented into Software and Services. The software segment comprises API platforms, integration modules, and user interfaces that enable seamless connectivity between corporate banking systems and commodit

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Commodity Hedging APIs for Corporate Banking Market Outlook

As per the latest research, the global Commodity Hedging APIs for Corporate Banking market size reached USD 1.32 billion in 2024, registering a robust growth with a CAGR of 11.8% from 2025 to 2033. The market is projected to reach USD 3.55 billion by 2033, driven by the increasing demand for real-time risk management, automation, and compliance in commodity trading and treasury operations. The surge in digital transformation initiatives within the banking sector and the need for seamless integration between corporate banking systems and commodity trading platforms are significant growth factors propelling this market.

The primary growth driver for the commodity hedging APIs for corporate banking market is the intensifying volatility in global commodity prices, compelling corporates to adopt advanced risk mitigation tools. As commodity prices fluctuate due to geopolitical tensions, supply chain disruptions, and macroeconomic uncertainties, banks are under pressure to offer more sophisticated hedging solutions to their corporate clients. Commodity hedging APIs enable real-time data exchange and automation of hedging strategies, allowing corporates to respond swiftly to market movements. This capability not only enhances risk management but also provides a competitive edge to banks that can offer such technologically advanced services, thereby fueling the market’s expansion.

Another significant factor contributing to the market’s growth is the rapid digitalization of the corporate banking sector. Financial institutions are increasingly investing in API-driven architectures to modernize their service offerings, streamline operations, and foster connectivity across diverse financial ecosystems. Commodity hedging APIs facilitate seamless integration with existing banking platforms, treasury management systems, and trading desks, resulting in improved efficiency and reduced operational overheads. The ability to deliver customizable and scalable solutions through APIs is particularly attractive to banks serving multinational corporations with complex hedging requirements across multiple commodities and geographic regions.

Regulatory compliance is also a critical driver in the adoption of commodity hedging APIs within corporate banking. Stringent regulations around transparency, reporting, and risk management in commodity markets have necessitated the deployment of automated and auditable solutions. APIs empower banks to automate compliance workflows, monitor exposures in real-time, and generate comprehensive audit trails for regulatory reporting. This not only minimizes the risk of non-compliance and associated penalties but also instills greater confidence among corporate clients regarding the integrity and reliability of their hedging operations. As regulatory frameworks evolve, the demand for flexible and up-to-date API solutions is expected to grow further, supporting sustained market expansion.

From a regional perspective, North America currently leads the global commodity hedging APIs for corporate banking market, accounting for the largest share due to its advanced financial infrastructure and early adoption of fintech innovations. However, Asia Pacific is anticipated to exhibit the fastest growth rate over the forecast period, driven by the rapid expansion of commodity markets, increasing cross-border trade, and the ongoing digital transformation of banking services in emerging economies. Europe remains a significant market, supported by the presence of major multinational banks and a strong regulatory framework promoting transparency and risk management in commodity trading. Meanwhile, Latin America and the Middle East & Africa are gradually catching up, as local banks and corporates recognize the benefits of API-driven hedging solutions for managing currency and commodity price risks in volatile markets.

Component Analysis

The component segment of the commodity hedging APIs for corporate banking market is bifurcated into software and services. Software solutions form the backbone of the market, offering banks and their corporate clients robust platforms for automating commodity hedging operations, integrating with trading desks, and ensuring seamless connectivity with internal risk management systems. These software APIs are designed to support a wide range of commodities, from energy to metals and agricultural products, providing real-time analytics, pricing feeds, and automated trade execution capabil

Release Date: 2020-07-16.Release Schedule:.The data in this file was released in July 2020...Source:.Suggested Citation: U.S. Department of Transportation, Bureau of Transportation Statistics; and, U.S. Department of Commerce, U.S. Census Bureau. (2020-07-16). Geographic Area Series: Shipment Characteristics by Commodity by Mode by Distance Shipped for the United States: 2017 [dataset]. 2017 Commodity Flow Survey. Accessed [enter date you accessed/downloaded this table here] from https://data.census.gov/cedsci/table?q=cf1700a13&hidePreview=true&tid=CFSAREA2017.CF1700A13...Key Table Information:.The estimates presented are based on data from the 2017 Commodity Flow Surveys (CFS) and supersede data previously released in the 2017 CFS Preliminary Report. These estimates only cover businesses with paid employees. All dollar values are expressed in current dollars, i.e., they are based on price levels in effect at the time of each sample. Estimates may not be additive due to rounding...Due to definitional and processing changes made each survey year, any data comparisons between one CFS survey and another should be made with caution. See the Comparability of Estimates section of the Survey Methodology for more details...Data Items and Other Identifying Records:.This file contains data on:.Value ($ Millions). Tons (Thousands). Ton-miles (Millions). Coefficient of variation or standard error for all above data items...Geography Coverage:.The data are shown at the U.S. only. For information on Commodity Flow Survey geographies, including changes for 2017, see Census Geographies...Industry Coverage:.N/A..Footnotes:.N/A..FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/cfs/data/2017/CF1700A13.zip...API Information:.Commodity Flow Survey data are housed in the Census Bureau API. For more information, see https://api.census.gov/data/2017/cfsarea.html...Methodology:.The noise infusion data protection method has been applied to prevent data disclosure, and to protect respondent's confidentiality. Estimates are based on a sample of establishments and are subject to both sampling and nonsampling error. Estimated measures of sampling variability are provided in the tables. For information on confidentiality protection, sampling error, and nonsampling error see Survey Methodology...Symbols:. S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.. Z - Rounds to Zero.. X - Not Applicable..For a complete list of all economic programs symbols, see the Symbols Glossary...Contact Information:.U.S. Census Bureau.Commodity Flow Survey.Tel: (301) 763 - 2108.Email: erd.cfs@census.gov

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This dataset contains monthly historical prices of 10 different commodities from January 1980 to April 2023. The data was collected from the Alpha Vantage API using Python. The commodities included in the dataset are WTI crude oil, cotton, natural gas, coffee, sugar, aluminum, Brent crude oil, corn, copper, and wheat. Prices are reported in USD per unit of measurement for each commodity. The dataset contains 520 rows and 12 columns, with each row representing a monthly observation of the prices of the 10 commodities. The 'All_Commodities' column is new.

WTI: WTI crude oil price per unit of measurement (USD). COTTON: Cotton price per unit of measurement (USD). NATURAL_GAS: Natural gas price per unit of measurement (USD). ALL_COMMODITIES: A composite index that represents the average price of all 10 commodities in the dataset, weighted by their individual market capitalizations. Prices are reported in USD per unit of measurement. COFFEE: Coffee price per unit of measurement (USD). SUGAR: Sugar price per unit of measurement (USD). ALUMINUM: Aluminum price per unit of measurement (USD). BRENT: Brent crude oil price per unit of measurement (USD). CORN: Corn price per unit of measurement (USD). COPPER: Copper price per unit of measurement (USD). WHEAT: Wheat price per unit of measurement (USD).

Note that some values are missing in the dataset, represented by NaN. These missing values occur for some of the commodities in the earlier years of the dataset.

It may be useful for time series analysis and predictive modeling.

NaN values were included so that you as a Data Scientist can get some practice on dealing with NaN values.

https://www.alphavantage.co/documentation/

FAS's PSD Online data for those commodities published in the WASDE Report are reviewed and updated monthly by an interagency committee chaired by USDA's World Agricultural Outlook Board (WAOB), and consisting of: the Foreign Agricultural Service (FAS), the Economic Research Service (ERS), the Farm Service Agency (FSA), and the Agricultural Marketing Service (AMS). The international portion of the data is updated with input from agricultural attachés stationed at U.S. embassies around the world, FAS commodity analysts, and country and commodity analysts with ERS. The U.S. domestic component is updated with input from analysts in FAS, ERS, the National Agricultural Statistical Service, and FSA. Interagency work on the database is carried out under the aegis of the WAOB. The official USDA supply and use data is published monthly in: WAOB, World Agricultural Supply and Demand Estimates (WASDE); in the foreign agricultural commodity circular series issued by FAS; and in the regional situation and outlook reports and monthly commodity newsletters of ERS (see keywords Crops and Animal Products) data for horticultural products are usually published twice a year. Resources in this dataset:Resource Title: PSD Web API. File Name: Web Page, url: https://apps.fas.usda.gov/psdonline/app/index.html#/app/about Programmatically access Production, Supply, and Distribution data via Web API.

Argus is a prominent source of pricing evaluations and business insights extensively utilized in the energy and commodity sectors, specifically for physical supply agreements and the settlement and clearing of financial derivatives. Argus pricing is also employed as a benchmark in swaps markets, for mark-to-market valuations, project financing, taxation, royalties, and risk management. Argus provides comprehensive services globally and continuously develops new assessments to mirror evolving market dynamics and trends. Covered assets encompass Energy, Oil, Refined Products, Power, Gas, Generation fuels, Petrochemicals, Transport, and Metals.

Xavvy Fuel is a global leader in Fuel Station POI and price data, specializing in data quality and enrichment across various sectors. We provide high-quality POI data on gas stations and fuel types throughout all European countries, tailored to our customers' specific needs, whether through one-time or regular data delivery, push or pull services, and in any data format.

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Furthermore, our data enhances the accuracy and consistency of existing datasets, allowing for easy data mapping to detect and correct errors.

With over 130 sources—including governments, petroleum companies, fuel card providers, and crowd-sourcing—Xavvy offers extensive insights into AdBlue/DEF stations across Europe. For those displaying AdBlue station information on maps or applications, data quality is essential to delivering an exceptional customer experience. Our continuously refined processes ensure the highest data quality through: - Regular quality controls via monitoring dashboards - Geocoding systems to correct and refine geocoordinates - Cleaning and standardizing datasets - Keeping up with current developments and mergers - Expanding data sources to cross-reference and enrich data

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