The Basics of Commodities Price Reporting Methodologies
An Introduction to Different Reporting Methodologies Practiced in the Market
Introduction
Commodity markets are dynamic arenas, where various players interact and transact: producers and consumers participate in physical markets, engaging in spot transactions and long-term contracts to balance supply and demand, while futures markets allow trading expectations and risk transfer for end users speculating on future price movements.
Within this complex market framework, distinct types of transactions lead to different types of prices. In order to navigate these diverse pricing mechanisms effectively, it becomes crucial to have access to reliable commodity price references, which is a challenge in and out itself. Such price references are typically provided in reports or industry publications, issued by companies referred to as Price Reporting Agencies (PRAs).
This article delves into the realm of such companies, aiming to explain general approaches used to develop price assessments, and highlight some key differences in practices adopted. More specifically, this article will compare practices employed by traditional PRAs, such as S&P Platts, Argus and ICIS, and Newcomers such as Intratec Solutions.
The main goal is to provide readers with a basic understanding of practices employed by PRAs in developing price assessments.
“Word of Mouth” Approaches
Traditional Price Reporting Agencies have long been established players in the information industry — some of which with many decades of existence. Such companies have played a pivotal role in commodities markets, providing price assessments widely used by market participants. Examples of the most traditional PRAs include:
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S&P Global Commodity Insights (formerly Platts)
These companies typically employ teams of experienced price reporters and journalists who develop price assessments based, mainly, on inputs from market participants. Such companies engage in contact with market participants through a number of ways — in panels of different types and formats, by conducting market surveys — to gather information and compile their view of the market dynamics for a given commodity over a given period.
By way of illustration, in traditional PRAs, one of the main practices of price reporters involves conducting surveys among commodity producers, consumers, banks and/or brokers, to collect information on recent bids, offers and deals, and seek their perspectives on topics like supply, demand, and market trends. Price assessments developed are then based on transactions reported by market players and may be influenced by their market views, informed in phone conversations, emails or text messages.
It is worth to highlight that, while traditional PRAs may employ a number of commodity pricing, in the vast majority of them price reporters working in such companies rely on their experience and judgment to develop price assessments, in such a way the human element plays a central role.
Data-Driven, Mathematical Approaches
For decades, PRAs have been pivotal in commodity pricing, and this industry has been remarkably stable. However, the landscape is now witnessing the emergence of two potential game changers: technology advancements and increasingly stricter regulations towards more transparency and auditability from international organizations. Indeed, as observed by Owain Johnson in his book The Price Reporters¹:
“Assuming that regulation is not wound back dramatically, the greater transparency and the easier auditing of a screen-based methodology will likely come to displace assessments by traditional price reporters, especially as phone calls, emails and face-to-face meetings with traders become increasingly discouraged by commodity firms’ compliance departments.”
Amid such backdrop, emerging price reporting agencies are disrupting established practices of traditional PRAs. Newcomers, with teams of data scientists and engineers, are adopting more data-driven approaches to develop reliable price assessments.
More specifically, companies like Intratec Solutions develop price assessments based mainly on volume-weighted averages (VWA), calculated in turn from aggregated data over deals effectively closed over a given period. Inputs come not from a set of market participants, but from auditable sources, mainly official trade statistics released by national institutions.
All inputs are gathered and treated with advanced data processing techniques, and reconciled by means of statistical analysis, so that outliers can be eliminated. When faced with input gaps, data scientists and engineers employ mathematical models to estimate prices and ensure the completeness of the price assessments presented.
Such automated methodologies are innovative in the sense that they eliminate the need for subjective judgment, leaving no room from human mistakes or biases. Also, while opinions and bids/offers reported by market players used by traditional PRAs may provide valuable insights, effectively closed deals typically hold the highest position in the information hierarchy when it comes to assessing prices.
Key Differences between Approaches
While traditional companies and newcomers aim to provide reliable commodity price assessments, their approaches differ significantly. This section will compare the practices employed by traditional Price Reporting Agencies and newcomers according to some key aspects, shedding light on the advantages and disadvantages of each approach.
Data Sources Auditability
While traditional companies rely on deals made in private, as reported by unknown market participants, their data sources are non-auditable. This lack of transparency can undermine trust in price assessments provided by these companies.
And in this context, biased sources can be a problem for Traditional PRAs, as the data they rely on may come from individuals or entities with vested interests. As market players, both commodity sellers and buyers naturally have their own agenda — while sellers wish prices to go up, buyers like to see prices falling. In fact, Lananh Nguyen and Isaac Arnsdorf already pointed out on their Bloomberg article² that most traders had already have a concern that
“others could be using these price making mechanisms to bias the price up or down depending on their interests”.
Price assessments developed with automated methodologies, in turn, are not derived from the opinion of some market participants. They are actually based on aggregated, auditable data: official information that all market participants must provide to national governments when exporting or importing a commodity.
Inputs Representativeness
By relying mostly on inputs from some market participants, the amount of data gathered by PRAs may not be representative of the market of a given commodity, potentially leading to distorted price assessments.
Conversely, as Newcomers price assessments are based on regional aggregated data, statistically treated, they are less prone to such distortions.
Data Validation
Traditional PRAs count on teams of journalists and reporters with market expertise, in such a way that these professionals use their experience and judgment to validate data gathered and develop price assessments.
According to more data-driven methodologies employed by Newcomers, data validation is made exclusively via statistical treatment.
Price Assessments Depth
Price assessments developed by traditional PRAs are often presented with a detailed assessment basis, describing for instance the quantity and specifications of the commodity being traded, price and payment terms, trade terms (Incoterm), delivery dates and delivery locations, etc. Such assessments then provide an in-depth view of the different prices and market dynamics around a given commodity.
On the other hand, while Newcomers derive their price assessments from aggregated data, those are generally presented with a less detailed assessment basis, and the assessments may often encompass commodities with different grades and/or specifications.
Final Remarks
Overall, traditional PRAs employ a combination of reporter-based information gathering and subjective expertise knowledge to generate their assessments. However, the reliance on potentially biased sources, limited sampling, and the absence of auditability remain areas of concern within their methodologies.
Newcomers’ strength lies in basing their assessments on deals effectively closed, as well as in the use of highly automated processes based on advanced techniques in data processing and statistical analysis. This approach not only ensures that the data reflects real transactions, but also avoids the pitfalls associated with human mistakes and potentially biased sources.
It must be noted, however, that in these approaches adopted by Newcomer’s there are no price reporters to perform a sense-check on the final price assessment developed.
References
[1] Johnson, O. 2017. The Price Reporters (1st ed.). Routledge
[2] Nguyen, L., Arnsdorf, I. 2013. Setting Prices by Word of Mouth. Bloomberg
About Intratec Solutions
Intratec Solutions — Independent Commodity, Energy & Industrial Intelligence. In operation since 2002, Intratec turns complex commodity and industrial data into clear, comparable intelligence. Its AI-enabled products cover prices, market dynamics, production economics, and the broader conditions that shape competitiveness. More at intratec.us.