Analog Assets in a Digital Book: The Operational Challenge of Physical Commodities
In standard accounting, assets only change quantity when you trade them. In the physical world, 1,000 barrels of oil can be measured as 1,001 because the temperature rose. This "phantom" volume illustrates the core challenge of physical assets: capturing the analog realities of the real world into the digital world of investment data and a financial ledger. This is a problem when you have physical possession of those barrels as an investment.
The strategic pivot to commodities
The challenge matters because multiple forces have driven an increasing number of hedge funds to trade or consider physically trading commodities. Global and regional challenges have driven high levels of macro volatility. Markets expect similar forces to continue. One consequence of these market forces has been an increase in volatility in commodity prices. This trend makes direct commodity trading more attractive to hedge funds.
Market infrastructure plays a further role in hedge funds’ desire to trade directly in physicals. Formal trading on exchanges often comes with regulatory limits on positions and exposures. To make big bets, funds seek out a less restrictive alternative, like the physical space where they can hold as much as they want of assets such as gas, power, or oil.
Finally, physicals create opportunities to capture different mispricing than listed exchanges lack. Funds may want to move beyond derivatives or exchange-traded commodities (ETCs) to capture physical mispricing. Physical things are unpredictable in ways from storage and transportation, to leaks or expansion, to pricing differences across vendors.
The operational divide: translating logistics to accounting
But while physicals have been financialized, they have not been mainstreamed into financial platforms. The challenges live in the market infrastructure and the data ecosystem that supports it.
Typical commodity markets have a very mature market infrastructure and data ecosystem, such as global exchanges like CME, ICE, NYMEX, and COMEX. In instruments traded there, there are lot sizes and position limits. Reconciliations with counterparties are straightforward. Furthermore, systems can provide robust reporting, as well as alerts before expiry to ensure clients trade out before ending up with an actual physical delivery.
Physicals, in contrast, do not have this same maturity. It’s also difficult to translate into a firm’s balance sheet or a fund’s NAV. The unique characteristics of physicals lie behind this challenge: types, units, grades, locations, and storage bring up questions that don’t show up on financial statements. For example, with crude oil, crude quality and carbon intensity create categories like “light sweet, medium sour, and heavy sweet,” with Platts listing 120 different streams based on their characteristics.i
To obtain real-time data, funds rely on a Commodity Trading Risk Management System (CTRM) to manage the complex lifecycle of buying, selling, and moving physical and financial commodities. They also identify, measure, and mitigate associated risks like price volatility, credit exposure, and logistics issues. These factors do not model easily in a hedge fund’s P&L or NAV.
The practical answer is a clear boundary between the operational system and the accounting system. Instead, central accounting systems should worry about only bare minimum data ingestion. Fund administrators receive basic position and quantity data inputs just for booking the trade. The pieces that translate for accounting tend to be limited to the location, the commodity, the commodity type, its grade (or equivalent for other types), the currency, and the quantity.
The clear boundary: from CTRM to NAV
Essentially, the problem to solve is a division of labor.
- The CTRM owns operational truth. It tracks the physical lifecycle end-to-end: movements, storage realities, day-to-day risk, and the messy edge cases that show up in the real world.
- The ledger owns financial truth. It needs a stable representation of exposure so the fund can strike NAV and close books.
Data is handed off between these worlds via a controlled interface and with a consistent schema. That minimal schema includes location, commodity and type, grade (for oil), currency, quantity, and units. Those fields help tell the financial story for the position across time, even when the physical story underneath it changes.
The data reality: leakage, expansion, and valuation
These operational differences highlight that listed assets and physicals live in entirely different data ecosystems. Hedge funds can struggle to come to terms with those differences and their impact.
The "shadow of a shadow" operating model
For hedge funds, the only pragmatic choice is adopting an internal “shadow of a shadow” operating model instead of pursuing detailed IBOR or expecting to shadow the fund administrator fully.
Doing so means decoupling day-to-day details of managing the portfolio and risk management from financial accounting. Accounting and reference data systems cannot do a job they were not designed to do. They are generally ill-equipped to handle physicals because of their unique traits. CTRMs can handle front office data like risk and lifecycle events and deliver enough data to strike an entire fund’s NAV. It is a one-way handoff.
Another consideration is the choice of entity. Depending on strategic decisions, operational workflows, and data infrastructure, sometimes it makes more sense to embed this shadow of a shadow approach by rolling it up into a hybrid fund where clients or managers want access to physicals, and sometimes a dedicated legal entity only doing commodities makes it easier to manage at the firm level. However, that doesn’t eliminate firm-level NAV and P&L, which will need to ingest minimum viable data for some positions.
Market maturity and future outlook
Interest in physical commodities is now emerging as a data-driven and diversified asset class. But, for investment operations around directly investible assets, they have a long way to go. The market of third-party logistics agents, data vendors, auditors, and similar providers is significantly less mature, with little integration and standardization across counterparties and locations. Fund accounting providers have made the best of the situation, but it remains an early stage minimum viable solution.
Potentially, a traditional end-to-end solution will never exist. Expecting data “ready to eat” might not be realistic. A more modern approach to data management that does not ask for it to be cooked prior to delivery may be the best way to address these fundamental challenges between two data ecosystems.
Authored By
Krishna Agarwal
Krishna Agarwal is Senior Vice President at Arcesium India, leading 150+ professionals in end-to-end hedge fund operations across accounting, reconciliation, and reporting. He is a financial operations leader with 20+ years of experience specializing in strategic transformation, automation, and scalable solutions for global alternative investment management clients.
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