Commodity Data

Commodity data refers to information concerning the commodity market. It is used to gain insights on how the commodity market and the commodities being bought and sold are functioning and traded. Datarade helps you find the best commodity market datas feeds and APIs. Learn more →
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Mintec Food & Non-food Commodities Pricing Database - Global Coverage 15K individual items icon
15K individual items
Mintec Food & Non-food Commodities Pricing Database - Global Coverage 135 countries covered icon
135 countries covered
Mintec Food & Non-food Commodities Pricing Database - Global Coverage 15 years of historical data icon
15 years of historical data
The Mintec database covers products across 18 different categories and all world regions. The food spectrum is fully covered along with areas such as packag...
SAVANT Copper Global Smelting Index - Commodities Data for China (Earth-i) 120 Smelters icon
120 Smelters
SAVANT Copper Global Smelting Index - Commodities Data for China (Earth-i) 85% China activity icon
85% China activity
SAVANT Copper Global Smelting Index - Commodities Data for China (Earth-i) 240 countries covered icon
240 countries covered
SAVANT Copper is an innovative product that delivers timely and accurate data, covering the activity of 70% of global copper smelting capacity and 85% of Chi...
Polystyrene (PS) Service: Commodity Data for Russia, Belarus, Ukraine, Kazakhstan and Uzbekistan - Market Report Company 50K records icon
50K records
Polystyrene (PS) Service: Commodity Data for Russia, Belarus, Ukraine, Kazakhstan and Uzbekistan - Market Report Company 100% fundamentals icon
100% fundamentals
Polystyrene (PS) Service: Commodity Data for Russia, Belarus, Ukraine, Kazakhstan and Uzbekistan - Market Report Company 5 countries covered icon
5 countries covered
Unrivalled grade-level historical, current and predictive pricing, supply & demand data and expert insight covering the polystyrene markets of the CIS region...
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FinPricing
Based in Canada
FinPricing
FinPricing provides highly accurate global financial market data from real time to historical via GUI and API. The data are collected from various sources, i...
>5 years
Historical
> 60 years
Curve tenors
>45
Interest rate coverage
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Pynk
Based in United Kingdom
Pynk
Pynk.io is a wealth management fintech with over 36,000 users. Users predict asset prices on our gamified platform at beta.pynk.io. These user-generat...
36000+
Global Users
3000+
Daily Total Predictions
180+
Countries Presence
Above Data
Based in USA
Above Data
Above Data procures and packages unique data assets in a flexible, intuitive and no-code environment allowing you to get quick answers before the competition
Compliant
Ethically Sourced
Exclusive
Unique Insights
No-Code
Platform
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The Ultimate Guide to Commodity Data 2021

Learn about commodity data analytics, sources, and collection.

What is Commodity Data?

Commodity data is information on the sales and purchasing activities of commodities such as mineral resources, national products and exported materials in international markets. This involves the type of commodities, falls and rises in price, what they are being used for, who is buying them, who sells commodities, and all other information concerning trading commodities, especially factors that determine the conditions of the commodity market. It is usually used in the documentation and analysis of the international commodity market’s structure.

How is Commodity Data collected?

Commodity data is a type of financial market data. This means that the methods and measures employed in the collection of most financial market data can be used in the collection of commodities data. These methods and measures include research from research firms, trading information, economic data, the opinions of investors, traders and buyers, as well as expert opinions. Regulatory bodies are also a source of information for collecting commodities data, as well as online services. News aggregators are also a valid means of data collection for commodities data and the commodities market as a whole.

What are the attributes of Commodity Data?

Commodities data is information on agricultural, mineral, metal, energy and manufactured materials, how they are bought, sold or exchanged, their prices, and all other trading activities. A typical commodities data should contain accurate pricing for these items, their price rises or price falls, the current commodities market conditions, and projected trends. Commodities data should contain information on exchange rates, trading attributes, and bidding attributes. All of these should help make decision-making for market participants in commodities more accurate and informed.

What is Commodity Data used for?

Commodity data is a type of financial market data. Commodity data can be used in various cases:
Portfolio optimization - creating portfolios on commodities that avoid as much risk as possible.
Yield increase - to increase profit returns on investments.
Trading - to make informed decisions about which commodities are profitable trade items, and how to go about trade processes.
Asset management - to help businesses properly manage or handle wealth.
Commodity market intelligence - for investment decisions, as well as academic purposes.

What information is available from Commodity Data today?

In contemporary businesses, commodity data is actionable intelligence which presents business owners and financial traders with detailed overviews of trends concerning different commodities, such as fossil fuels and precious metal. Commodity data today allows users to forecast future supply and demand and identify the market factors that are likely to affect them. Commodity data providers offer data systems that can be integrated into business and trading strategies and offer detailed insights and analytics of commodities’ trends. Commodity data today gives investors and business owners a ‘bird’s eye view’ of the performance of their commodities. Through tools like commodity data models, a trader can carry out analytics, modelling, finance agreements and settlements based on real-time commodity data.

What is Commodity Data analytics?

Commodity data analytics refers to means by which commodity traders make decisions based on accurate, consistent, timely, well-documented and structured data. Analytics is a branch of data science. As a result of the digitisation of trading and the constant stream of financial news updates, over recent years, there’s been an unprecedented rise in data concerning commodities being sold. As such, commodities data analysis is a complex process that often requires machine learning and artificial intelligence to obtain meaningful insights. Data marketplaces today continue to make big data accessible to trader who need external intelligence to analyze commodity market trends. Commodity data vendors provide commercial datasets to these traders, primed for their analytics.

How to carry out Commodity Data science?

Modern day commodity trading activities sometimes bring unpredictable developments. Coupled by the need for businesses to succeed in a competitive environment, commodity trading challenges are further exacerbated by price volatility and economic uncertainties. These challenges in commodity trading has prompted commodity traders to search for data science mechanisms that will help them optimise the value of assets or speculate upon price shifts as a means to enhance trading activities. Commodity data science involves finding the right analytical tools from data vendors and using these tools to obtain meaningful data that help the business gain complete market transparency, reduce the risks of a loss, and help make optimal decisions concerning trading and market strategies. As far as commodity data science is concerned, seeking the services of professional data scientists to assist in commodity data acquisition and analysis can often be a smart move for traders and investors, as it helps their commodity portfolio management in the long run.

What is a Commodity Price?

The market price of a commodity that is usually quoted in news platforms essentially represents the market futures price for the given commodity. This futures price differs from the spot price, which refers to the price of the commodity that a buyer would pay for in the present moment. Commodity prices are affected by the laws of demand and supply. As such, commodity prices rise with inflation.

Does the World Bank provide Commodity Data?

Yes, the World Bank provides commodity data. However, for a trader who is looking for detailed analytical models of commodity data, the World Bank’s provision is a bit narrow because in most cases, the body only provides prices and price fluctuations of commodities without due consideration of other data analytics factors that may affect these changes. In order to bridge the gap in the data provided by World Bank, commodity data vendors and data marketplaces provide professional data mining and analytics services to data consumers. Proprietors are increasingly choosing to buy commodity data from professional data providers for these high level insights.

Does the IMF provide Commodity Data?

No, the IMF does not provide commodity data. The core mandate of the International Monetary Fund (IMF) is to ensure that the overall stability of the international monetary system is maintained. This is accomplished by means of three core initiatives: keeping tabs of the overall international economic wellbeing as well as that of individual member states, advancing financial assistance to countries that are struggling to maintain their balance of payment, and giving practical assistance to member states through the help of economic experts.

How can a user assess the quality of Commodity Data?

Commodities data is used by a great number of individuals, businesses and countries. It is important that whatever data you buy is of high quality. To assess the quality of commodities data, it must be transparent, in such a way that users of the information are able to make informed and accurate decisions and expectations on market conditions. Commodities data must also be authentic, meaning whatever sources it is being attained from, must verify its impartiality and collection methods. Commodities data must also be accurate, reliable, and precise for users and participants in the commodities market.

What is the Commodity Data outlook for 2021?

2020 has been the most eventful year in recent human history. The economic implications of the pandemic are expected to reverberate deep into 2021, a factor that will have repercussions on commodity prices. In spite of this, 2021 is set to be a better year for commodity trading than 2020. Economic activities are expected to pick up by the middle of the year, which will see the commodity market begin to recover. Experts predict that the global real GDP growth will advance by 5.5 % in 2021.

Who are the best Commodity Data providers?

Finding the right Commodity Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular Commodity Data providers that you might want to buy Commodity Data from are FinPricing, Pynk, Above Data, Mintec Global, and Market Report Company.

Where can I buy Commodity Data?

Data providers and vendors listed on Datarade sell Commodity Data products and samples. Popular Commodity Data products and datasets available on our platform are Mintec Food & Non-food Commodities Pricing Database - Global Coverage by Mintec Global, SAVANT Copper Global Smelting Index - Commodities Data for China (Earth-i) by Earth-i, and Polystyrene (PS) Service: Commodity Data for Russia, Belarus, Ukraine, Kazakhstan and Uzbekistan - Market Report Company by Market Report Company.

How can I get Commodity Data?

You can get Commodity Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Commodity Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Commodity Data APIs, feeds and streams to download the most up-to-date intelligence.

What are similar data types to Commodity Data?

Commodity Data is similar to Stock Market Data, Alternative Data, ESG Data, Merger & Acquisition Data, and Proprietary Market Data. These data categories are commonly used for Trading and Commodity Data analytics.

What are the most common use cases for Commodity Data?

The top use cases for Commodity Data are Trading, Asset Management, and Portfolio Optimization.