How Options Traders Can Use Supply-Chain Data Before Earnings
August 6, 2026
Altsets
Research by Altsets Research
Use customer and supplier exposure to build a secondary earnings watchlist, then evaluate volatility, liquidity, timing, and direction separately in the options market.
Data used:Altsets Supply Chain Intelligence: 90k+ entities, 400k+ relationships, 20+ years of history.
Key findings
- SK Hynix at 27.88% and Micron at 17.62% of supplier revenue associated with Nvidia provide a relationship-based way to prioritize secondary underlyings around a Nvidia earnings event.
- Supply-chain data selects economically linked names but does not replace implied-volatility, liquidity, expiration, or directional analysis.
Supply-chain data can help an options trader decide which secondary stocks deserve attention around another company's earnings. It does not tell the trader which option to buy. The useful step comes earlier: narrowing a huge market into counterparties with measurable economic exposure to the reporting company.
Nvidia provides a clear example. Altsets estimates SK Hynix has 27.88% of supplier revenue associated with Nvidia, while Micron Technology has 17.62% associated with Nvidia. If Nvidia reports before those suppliers, the relationship data gives an options trader a reason to put SK Hynix and Micron on the post-earnings research list. That is a candidate-selection signal, not a direction or volatility forecast.
Start with the event calendar
Options trading is time-sensitive. The first input is therefore the catalyst calendar: earnings date, guidance update, investor day, product event, regulatory decision, and major customer report. Supply-chain data is then used to find economically exposed companies around that event. Without the event timing, a relationship percentage is just background information.
Rank counterparties by the direction that matches the event
If the event begins at a customer and the question is which suppliers may react, supplier revenue percentage is the relevant first screen. In the Nvidia example: SK Hynix: 27.88% of supplier revenue and Micron Technology: 17.62%. Those percentages indicate that Nvidia is economically meaningful to both suppliers in the displayed data. An options trader can use that information to decide which names deserve deeper volatility and pricing work after Nvidia reports.
Do not convert exposure into a directional trade
A large supplier-revenue percentage does not imply the supplier's stock will move in the same direction as the customer. The customer's report can contain mixed signals. A revenue beat can come with weaker future demand.
A supplier may already have guided conservatively. The relationship may be relevant to only one product segment. The options market may already price a large move.
Supply-chain data identifies economic linkage. Direction still requires a thesis.
The next filter belongs to the options market
After the supply-chain screen produces a shortlist, an options trader still needs separate market data. That can include implied volatility, term structure, skew, expected move, liquidity, bid-ask spread, open interest, earnings dates for the secondary company, and time remaining to expiration. Altsets does not replace those inputs. It helps decide where to spend the options-research effort.
Reporting order can create a useful window
The most interesting setup occurs when the customer reports before an exposed supplier. The sequence can look like:
- customer reports;
- investor evaluates what changed;
- exposed suppliers are ranked by revenue concentration;
- supplier-specific context is checked;
- options pricing is evaluated before the supplier's own earnings.
This can create a research window between two earnings events. The window may be hours, days, or weeks. The relationship data is valuable because it identifies the companies where the first report may contain economically relevant information for the second.
Use negative and positive events symmetrically
The method should not be limited to downside hedging. A customer raising capital spending or demand guidance can create positive read-through questions. A customer cutting production can create negative ones.
An options trader may ultimately express the view with calls, puts, spreads, volatility trades, or no trade at all. The supply-chain screen should remain neutral about the instrument.
Avoid double-counting the same event
Several mapped suppliers can share exposure to the same customer. Treating each relationship as an independent signal can exaggerate conviction. SK Hynix and Micron both have Nvidia exposure.
That means a Nvidia earnings event can create two separate secondary names, but both originate from the same underlying catalyst. A portfolio of options positions across both names may therefore contain hidden event concentration. This is exactly the kind of overlap supply-chain data can help make visible.
Structural edges can expand the watchlist, but not the conviction
A graph may show additional customer or supplier relationships without economic percentages. Those edges can still create candidates. But a structural-only relationship should not be given the same confidence as a quantified 27.88% or 17.62% supplier-revenue exposure. The missing-metrics guide explains how to keep those evidence levels separate.
A repeatable options research workflow
- Identify the catalyst company and event date.
- Map direct suppliers and customers.
- Rank counterparties using the directional percentage that matches the event.
- Check whether the event affects the relevant product or business line.
- Compare reporting dates.
- Build a short list of secondary underlyings.
- Evaluate implied volatility, liquidity, skew, and expiration separately.
- Define the directional thesis.
- Account for shared-event concentration across multiple positions.
- Skip the trade when the relationship is interesting but the options setup is poor.
The customer read-through guide explains the fundamental relationship logic. The earnings-propagation guide explains how the signal can move through more than one company. This article narrows that process to the workflow an options trader actually needs before choosing a contract.
For relationship metric definitions and limitations, read the Altsets supply-chain data methodology. Browse Supply-Chain Data Use Cases for other investing workflows.