A view about an industry does not have to be a bet that every company in it will rise. If one group benefits from a change while another bears the cost, a long-short portfolio can express that difference. The Freeport Index organizes research into baskets built around such arguments.
The two sides of a theme
Consider spending on AI infrastructure. The same purchase is revenue to a supplier and investment expenditure to a buyer. One possible thesis is that scarce inputs give suppliers pricing power while buyers struggle to earn an adequate return on their investment.
That is an argument to test, rather than an accounting identity guaranteeing a profitable trade. Buyers could earn very high returns from the capacity they acquire. Suppliers could lose their scarcity, or their share prices could already assume unusually strong margins. The relative price of the two groups matters alongside the business mechanism.
The Index page presents the themes, positions, and opposing cases together. Its six published baskets contain 60 names. Each basket should be read as a particular set of exposures, rather than a label for an entire industry.
Gross and net exposure
The published aggregate targets 100% long exposure and 50% short exposure. Individual published weights are rounded, so their displayed sums can differ slightly from those targets. On a hypothetical $100 capital base, that means $100 of longs and $50 of shorts. Gross exposure adds the absolute amounts: $150, or 150%. Net exposure subtracts the shorts from the longs: $50, or 50%.
If both sides rise 10%, the longs gain $10 and the shorts lose $5, producing a $5 gain before costs. If the longs fall 10% while the shorts rise 10%, the portfolio loses $15. The 50% net figure therefore does not describe the most that can be lost.
Nor does net dollar exposure measure every market sensitivity. Two groups can have different betas, currencies, or reactions to interest rates. Offsetting dollar amounts can leave substantial exposure to a common factor, as the hedging guide explains.
Research and implementation
The published methodology defines how the Index is constructed. Its performance chart is a hypothetical historical simulation, with return and risk statistics calculated over the selected dates. Implementing a similar view requires additional choices: the instruments available, short borrow or perpetual funding, spreads, collateral, and rebalancing. Some reference assets may be difficult to trade at a published mark.
Weights also change as prices move. A basket that begins with the intended exposure can drift, and its legs may fill at different times. Basket execution explains that transition from a target portfolio to actual positions.
The useful unit of research is the complete argument: why the long side should outperform the short side at their current prices, which assumptions make that possible, and what observation would show that those assumptions failed. The Index makes those arguments explicit enough to examine.
Read a basket from argument to exposure
Start with the proposed business change, then identify why the long side should benefit more than the short side at the prices being considered. Read the opposing case before looking at the return chart. This gives the chart a proposition to evaluate.
Next, inspect the holdings and weights. Ask which companies dominate the outcome and which risks are repeated across themes. A diversified list of names can still concentrate on one investment cycle, currency, or financing condition.
Finally, choose a common date window when comparing the basket, the aggregate Index, and benchmarks. Read the historical-simulation and cost assumptions alongside the return. If you want to express a similar idea in an account, calculate it again using instruments, funding, borrow, and execution available to you. The published basket supplies an inspectable research argument; the actual trade still needs its own implementation.