Buy Commodity Data

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Polystyrene (PS) Service: Commodity Data for Russia, Belarus, Ukraine, Kazakhstan and Uzbekistan - Market

by Market Report Company
Data Analytics: Monthly Fundamental data/statistics on consumption, production, import, export and inventory ... Unrivalled grade-level historical, current and predictive pricing, supply & demand data and expert insight
Available for 5 countries
50K records
10 years of historical data
100% fundamentals
Available Pricing:
One-off purchase
Yearly License
Revenue share
Monthly License

Polyethylene (PE) Service: Commodity Data for Russia, Belarus, Ukraine, Kazakhstan and Uzbekistan - Market

by Market Report Company
Data Analytics: Monthly Fundamental data/statistics on consumption, production, import, export and inventory ... Unrivalled grade-level historical, current and predictive pricing, supply & demand data and expert insight
Available for 5 countries
50K records
10 years of historical data
100% fundamentals
Available Pricing:
One-off purchase
Yearly License
Revenue share
Monthly License

Currency conversion, current and historical forex exchange rate and currency fluctuation data through

Historical data can be accessed from 1984-11-28 it varies on Historical Data Limits from which date each ... Trusted Data Data collected from various trusted commercial sources, banks, forex exchanges, cryptocurrency
Available for 249 countries
52.4K currency pairs
35 years of historical data
100% high quality professional database
Starts at
$100$92 / 10K API call...
8% Datarade discount
Free sample available
8% revenue share - Mysteel Global profile banner
Mysteel Global
Based in China
Mysteel Global
A respected source of market intelligence for China's iron ore and steelmaking industry, Mysteel Group provides visibility and understanding of the world's l...
200 M+
Pricing Point
Industrial Partners
Staffs - Mintec Global profile banner
Mintec Global
Based in United Kingdom
Mintec Global
For over 30 years Mintec has been the leading provider of raw material market prices and analysis covering more than 14,000 food ingredients and non-food raw...
Lower Cost
Reduce spend by 3%
Reduce time preparing
Lower Risk
Mitigate Competitive Risk
Based in Pakistan
The world’s good data science community with powerful tools and resources to help you achieve your data science goals. Explore, analyze, and share quality... - Twelve Data profile banner
Twelve Data
Based in Singapore
Twelve Data
We take the financial market data of the highest quality, add convenient formats and tools, with all running in cloud infrastructure - this is the recipe for...
Requests daily
Global exchanges
Based in Canada
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
> 60 years
Curve tenors
Interest rate coverage - Pynk profile banner
Based in United Kingdom
Pynk is a wealth management fintech with over 36,000 users. Users predict asset prices on our gamified platform at These user-generat...
Global Users
Daily Total Predictions
Countries Presence

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 Mysteel Global, Mintec Global,, Twelve Data, and FinPricing.

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, Brain Sentiment Indicator - Currencies, Cryptocurrencies and Commodities by Brain Company, and SAVANT Copper Global Smelting Index - Commodities Data - Global Service by Earth-i.

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 Asset Management.

What are the most common use cases for Commodity Data?

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