Commodities: Gulf to Matola
01 Context & trade setup
Nearly two years ago, I made it to the final round of interviews at a small Emirati oil brokerage based in Monaco. I was applying for a finance graduate position. My background was in corporate finance and investment analysis, not physical trading. However, the role had caught my attention and I figured I would give it a shot.
I made 3 interviews until the final round which was a case study on Zoom. No preparation, no hints, only one hour on the clock. The brief: price a physical diesel cargo from the Arabian Gulf to Mozambique, then assess whether acquiring the storage terminal at the destination made financial sense. Simple enough in theory. In practice, I realised very quickly that this was testing a type of thinking I was not used to. Physical commodity trading is not about financial models in the traditional sense. It is about unit conversions, logistics costs, timing and counterparty risk, all of it happening at the same time.
I am writing this up not because I am a commodities expert. I am writing it because I found the exercise genuinely instructive. It gave me a very concrete view of how a physical trade actually works from end to end, which is something you rarely get explained clearly in one place. So let's go deep into the trade itself: 33,000 metric tons of 50ppm gasoil, bought FOB in the Arabian Gulf against the MOPAG index, sold DAP at the Matola terminal in Mozambique against CIF MED ULSD. The Excel file I had been given already contained quite a bit of information: market prices, conversion factors, cost items and the terminal's financials. So the work was less about finding the data and more about knowing what to do with it under time pressure.
A quick note on the incoterms for those who are not familiar. FOB (Free On Board) means the seller delivers the cargo onto the vessel at the loading port and from that point the risk transfers to the buyer. DAP (Delivered At Place) is the opposite end of the spectrum: the seller is responsible for delivering the cargo to the named destination, in this case Matola, covering all freight and risk along the way. The gap between those two incoterms is essentially where all the costs we will look at in section 03 live.
02 Unit conversions
This was the first thing that threw me. In most finance contexts you work in one currency and one referential. Here you are buying in dollars per barrel and selling in dollars per metric ton. Those are not the same thing and you cannot just ignore the gap.
To convert from one to the other you need the density of the product, which tells you how many barrels fit into one cubic meter and from there how many barrels make up one metric ton. The complication is that there are two densities at play: the paper density, which is the standard reference used for pricing, and the real density of the actual cargo that gets loaded onto the vessel. They are close but not identical, and on a 33,000 ton cargo even a small difference in density changes your numbers.
Key Conversion Factors
The logic goes like this: there are 6.2898 barrels in one cubic meter. Divide that by the real density of 0.83 tons per cubic meter and you get 7.578 barrels per metric ton. So to convert a price from $/bbl to $/tn, you simply multiply by 7.578.
03 Cost stack & breakeven
Once you have the buy price in the right unit, the next step is to figure out the total cost of getting the cargo from Bahrain to Matola. This is called the cost stack and it is the heart of the exercise. In physical trading, buying cheap is only half the story. You also need to land the cargo at a cost that still leaves you a margin on the other side.
Freight is by far the largest cost item at $1.75mm, but what surprised me was how fast the smaller items add up. Demurrage is the penalty charged when a vessel waits longer than planned at port. It came to $60,000 here because the ship waited three extra days at $20,000 a day sitting idle. Outturn loss is another one that is easy to overlook: some volume is always lost between loading and discharge through evaporation, measurement gaps, and handling. On this cargo it amounted to over $57,000. Nothing is free once you are dealing with physical commodities.
| Cost Item | Amount ($) | $/tn | Note |
|---|---|---|---|
| Freight | -1,750,000 | -53.03 | Main voyage cost |
| Demurrage | -60,000 | -1.82 | 3 days × $20,000/day |
| Port Costs | -50,000 | -1.52 | Discharge port |
| Insurance | -40,000 | -1.21 | Cargo insurance |
| Inspection (Load) | -10,000 | -0.30 | At origin |
| Inspection (Discharge) | -10,000 | -0.30 | At Matola |
| TS Delays | -40,000 | -1.21 | Transshipment |
| Outturn Loss | -57,036 | -1.73 | Evaporation and measurement |
| Total Costs | -2,017,036 | -61.12 | Landed cost per ton |
Total cost to land the cargo in Matola: just over $2mm, or $61.12 per ton. Add that to your converted buy price and you have your breakeven.
04 Return analysis
The sell side is CIF MED ULSD plus a $20/tn premium negotiated with the buyer. Using October CIF MED prices of around $959/tn, the all-in sell price lands at approximately $979/tn.
When I first saw that number I was a bit surprised. The margin works out to about $17 per ton on a trade where freight alone costs $53 per ton. You are moving over 33,000 tons of diesel across the Indian Ocean and your gross margin per ton is roughly the price of a sandwich in Monaco. But that is completely normal in physical commodity trading. Nobody makes money on one trade. You make money by doing a lot of trades, managing your cost base tightly, and not losing on the ones that go sideways. Volume is the whole game.
In absolute terms, $561k on a single cargo is not bad at all. The question is what it represents as a percentage return on the capital deployed, which is what the next section is about.
05 IRR calculation
The IRR part of the exercise introduces the time dimension. The assumptions are: you pay for the cargo and the freight on the day you load. The voyage takes 13 days. You get paid on arrival. All other costs such as port, inspection and insurance are also settled on arrival day.
So the cash flow structure is simple: one large outflow on Day 0, one net inflow on Day 13. When you annualise that over a 13-day window, the IRR number comes out looking almost absurdly high. This is where I had to stop and think during the interview, because the result felt wrong at first glance.
06 Terminal acquisition
The second half of the case was the part I found most interesting, probably because it was closer to the kind of analysis I was more used to in my studies and past professional experiences. The question was: is there an opportunity to acquire the Matola storage terminal? If yes, does it really make sense?
Before you can answer that, you need to know what you are actually buying. So the first task is to calculate the enterprise value, which is the standard starting point for any acquisition analysis.
Enterprise Value
EV is market cap minus cash plus debt. The terminal has a $40mm market cap, $7mm of cash on the balance sheet, and $22mm of debt. Straightforward.
Unit Economics at 40k cbm
The terminal has 40,000 cbm of storage capacity, rented out at $10 per cbm per month with operating costs of $3 per cbm per month. The economics are simple and predictable, which is typical of infrastructure assets like this. You are not going to see explosive growth but you are also not going to see wild swings. It is a steady, contracted cash flow business.
Should you finance with debt at 12%?
No, and the arithmetic makes it obvious. Annual EBITDA is $3.36mm. If you finance the $45mm acquisition with debt at 12% per year, your interest bill alone is $5.4mm annually. You would be paying more in interest than you are generating in operating profit from day one. That is not leverage, that is a slow bleed.
The terminal might still be worth acquiring, but with cheaper capital, an equity-heavy structure, or as a strategic asset that reduces your logistics costs on future trades into East Africa. The financial case as presented does not work at 12% debt.
07 What I learnt from this experience
The biggest thing this case taught me is that physical commodity trading is far more operational than I had assumed going in. Coming from a corporate finance background, I was used to thinking in terms of valuation, modelling, capital structure. Here the edge comes from somewhere else entirely: knowing your costs to the dollar, understanding your counterparties, managing your logistics, and being precise on the conversion factors that most people would round off without thinking.
The terminal question was a good reminder that the most durable returns in commodities often sit in the infrastructure layer rather than in the trades themselves. Owning the storage, the pipeline, the port access, that is where you build a real business rather than just a book of trades. A trader who controls the terminal in Matola is playing a fundamentally different game than one who has to call and negotiate access every time.
At the end, I did not get the job. I was highly motivated but I was probably not the right profile for it at the time. But I kept the case study because I thought it was one of the most well-constructed exercises I had come across. It tested real skills, not textbook knowledge, and it respected the candidate's ability to think through a problem without hand-holding.