Within the context of increased oversight of value creation and economic substance, transfer pricing practices involving intragroup commodity trading entities have become the target of inquiries by multiple tax authorities. It is therefore worthwhile to review some key concepts and arm’s length remuneration considerations.
The trader
Commodity traders operate within the dynamic world of materials and resources, including agricultural products, engaging in the buying and selling of assets like crude oil, copper, natural gas, gold, wheat, and coffee among many others. Their operations are particularly relevant to the energy, mining and agricultural industries and any potential player within associated supply chains.
The primary objective of the trader is to profit from the price swings that characterize these markets. To achieve this, they analyze a complex interplay of factors, including global supply and demand dynamics, geopolitical or natural events, and broader macroeconomic trends. By anticipating market movements, traders strategically take positions hoping for a gain.
Trading entities can be diverse, ranging from large corporations that physically handle and trade vast quantities of materials and resources to boutique sales and marketing entities. Regardless of their scale, traders play a crucial role in the global economy by providing liquidity to markets and facilitating price discovery. Their activities help to connect producers and consumers, ensuring the efficient flow of essential materials and resources while simultaneously profiting from the inherent volatility. Their expertise in analyzing market dynamics and forecasting price movements contributes to price discovery, allowing for a more accurate valuation. Furthermore, traders can bear significant financial risk by committing capital and taking positions in volatile markets.
Considerations regarding the related-party trader’s remunerations
To define arm’s length pricing for transactions involving a related party trader it is fundamental to clearly understand the exact nature of that related-party transaction. This understanding requires a detailed analysis of the functions performed, the assets employed, and the risks assumed by each party involved. Delineating the transaction and reviewing the fact pattern allows for a clear definition of the economic analysis needed to determine the arm’s length remuneration.
A first step is to look at data from sufficiently comparable, independent deals that could serve as a reference for pricing transactions with a related-party commodity trader. This can include information on commissions, or margins obtained by independent resellers. Alternatively, the related-party trader’s profit margin can be estimated based on their functional profile (i.e., by referring to the activities they perform and/or risks they assume).
In practice, the role of the related-party entity can vary; in fact, there is a full spectrum from low-risk service providers, simply executing routine tasks without ownership, up to fully-fledged traders, which take ownership and handle most of the marketing and commercial risks associated with commercialization. In the latter case, the compensation should be based not just on the tasks they perform, but also on the risks being assumed by the trader (price fluctuations, inventory risks, and credit or counterparty risk, among many others).
A fully-fledged trader commonly receives a market price minus a margin, and this profit margin is meant to cover both the tasks performed and the risks borne. While it can be relatively easy to access data on what independent companies earn for developing similar marketing or sales tasks, it is much harder to find direct comparisons with arm’s length compensation for the risks a trader assumes (i.e., risks that the trader takes away from the producer, effectively derisking it). This is because the risks involved in selling different materials or resources can differ greatly depending on their specific market dynamics and on contractual obligations for the parties to the transaction.
One possible approach is to employ mathematical tools like Monte Carlo simulations to model the financial impact of these transferred risks by assessing exposure, ultimately providing a robust approach to value risk, and subsequently deriving appropriate compensation for the entity bearing said risk.
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