How a CTRM supports a trading desk's day-to-day work: capturing and managing a crude oil trade, calculating P&L, tracking physical exposure, and handling the pricing formulas that dominate physical commodity markets.
A CTRM captures a crude oil trade's full terms at the point of deal, grade, quantity, pricing basis such as dated Brent or WTI plus or minus a differential, laycan or delivery window, Incoterms and counterparty, then carries that trade through logistics (nominations, vessel scheduling, load and discharge), pricing, P&L and risk reporting, and finally invoicing and settlement.
Because crude trades are frequently priced against a floating benchmark over a pricing period rather than a fixed price at deal date, the system needs to track exposure to that benchmark until pricing is finalised, then true up P&L once the actual average price is known. See CTRM by Commodity for how crude's requirements compare with other commodities.
A CTRM calculates P&L by combining realised P&L, the locked-in gain or loss on trades that have been fully priced and settled, with unrealised, mark-to-market P&L on positions still open against current market prices. The calculation draws on trade capture data (quantity, price or formula, cost adjustments such as freight, storage, quality and demurrage), plus live or end-of-day market prices and curves, and rolls up from individual trades to desk, portfolio and book level.
Good CTRM P&L reporting also breaks the total down by driver, price movement, volume, cost adjustments, so traders and risk managers can see what actually moved the number, not just the final figure.
A CTRM tracks physical exposure by netting open buy and sell positions across a commodity, location and time period to show a firm's net physical position at any point, distinct from its financial (paper) hedging position. This lets risk managers see total exposure across both physical and financial legs together, which matters because a firm's true risk is the combination of both, not either in isolation.
Many physical commodity trades are not priced at a single fixed number but against a formula, for example a benchmark index plus or minus a differential, averaged over a specified pricing period. A CTRM needs to hold that formula as structured data, not free text, so it can automatically apply published index prices as they are set each day, calculate the running average, and true up the trade's final price and P&L once the pricing period closes.
This matters for both crude and refined products (Brent, WTI, Platts assessments) and for metals and concentrates (LME cash or three-month settlements), and a system that only handles fixed prices will struggle with the formula-pricing that dominates physical commodity markets.
Amphora's Symphony platform models formula-based pricing, physical exposure and P&L natively across crude oil, refined products, biofuels, coal, ore, LNG, metals, concentrates, agriculture and freight, on the same single-branch architecture.
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