Why Supply-Chain Exposure Percentages Are Not Stock Betas
September 2, 2026
Altsets
Research by Altsets Research
Keep commercial exposure, operating scenarios, financial-statement sensitivity, and stock-return sensitivity as separate analytical layers instead of treating a relationship percentage as a market beta.
Data used:Altsets Supply Chain Intelligence: 90k+ entities, 400k+ relationships, 20+ years of history.
Key findings
- Nvidia is associated with 17.62% of Micron revenue and 27.88% of SK Hynix revenue in the displayed data, but those percentages measure commercial concentration rather than stock-return covariance.
- Turning relationship exposure into a market thesis requires separate assumptions for operating pass-through, margins, earnings, expectations, valuation, and market behavior.
A supply-chain exposure percentage is not a stock beta. Altsets associates Nvidia with 17.62% of Micron revenue. That does not mean a 10% move in Nvidia stock should produce a 1.762% move in Micron stock.
It also does not mean a 10% change in Nvidia demand will automatically move Micron revenue by 1.762%. The 17.62% figure describes the economic importance of a customer relationship. Share-price sensitivity is a different object.
The relationship percentage has a business denominator
Supplier revenue percentage asks: What share of the supplier's revenue is associated with this customer relationship?
For Micron to Nvidia, the displayed value is 17.62%. For SK Hynix to Nvidia, the displayed supplier-revenue value is 27.88%. Those percentages can help compare customer dependence.
They do not measure covariance between two stocks. They do not include investor expectations. They do not encode valuation.
A stock price reacts to information, not just revenue exposure
Suppose Nvidia announces demand that is 10% higher than expected. Micron's stock reaction can depend on whether investors already expected the increase, which Micron products benefit, pricing, gross margin, available capacity, contract terms, capital spending, competing customer demand, valuation, and broader market conditions. Two suppliers with similar Nvidia revenue exposure can therefore have very different stock reactions. The relationship percentage is an operating input, not a return coefficient.
Even operating sensitivity needs assumptions
A simple first-order scenario can multiply customer revenue exposure by an assumed demand change. That can be useful. For example, if one assumes a 10% change in Nvidia-linked Micron revenue and holds everything else constant, 17.62% multiplied by 10% gives a 1.762% first-order total-revenue sensitivity.
That is a scenario. It assumes proportional pass-through. It says nothing directly about Micron's stock price. The customer-mix sensitivity guide shows how to use this kind of math without calling it a forecast.
Profit sensitivity can differ from revenue sensitivity
Revenue does not translate one-for-one into earnings. The affected product can have higher or lower gross margin than the company average. Fixed costs can create operating leverage.
Capacity constraints can limit incremental volume. Pricing can move independently from units. A long-term contract can dampen price changes.
The resulting earnings effect can therefore be larger or smaller than the revenue effect. Again, none of that is contained in the 17.62% relationship percentage.
Stock beta answers a statistical market question
In finance, beta normally describes how a security's returns move relative to another return series or market benchmark. That requires historical return data and a statistical method. A customer-exposure percentage is derived from the economics of a commercial relationship.
The two metrics can be related economically without being interchangeable mathematically. Calling customer exposure a stock beta would merge fundamentally different denominators.
Shared-customer exposure is not a hedge ratio either
SK Hynix and Micron both have meaningful mapped Nvidia exposure. That can make them interesting candidates for relative-value research. It does not mean the ratio of 27.88% to 17.62% tells an investor how many shares of one stock to hedge with the other.
A hedge ratio depends on price behavior, volatility, factor exposure, currency, valuation, and the specific risk being hedged. The shared-customer relative-value guide keeps those ideas separate.
The percentage is still highly useful
Rejecting the beta interpretation does not make the relationship metric weak. It makes the metric more precise. Supplier revenue percentage can help answer:
- Which supplier is more dependent on the same customer?
- Which company deserves closer monitoring after a customer event?
- Which customer relationships are material enough for scenario analysis?
- Which portfolio holdings share a demand source?
- Which supplier may have greater customer concentration?
Those are valuable investment questions. They are simply not stock-return equations.
Public product evidence can improve the operating interpretation
Micron has publicly discussed HBM4 shipments and next-generation memory demand. SK Hynix has a named multi-year Nvidia memory partnership. Those public facts can strengthen the case that Nvidia demand matters to both suppliers.
They still do not convert company-wide relationship percentages into stock betas or product-market shares. Public context should refine the economic story without changing the definition of the metric.
A clean evidence ladder
When using relationship data in a market thesis, separate four layers. Relationship exposure is the customer or supplier percentage measured by the data. An operating scenario adds an explicit assumption about how demand, price, or cost changes.
The financial translation estimates the resulting revenue, margin, earnings, or cash-flow impact. The market reaction is an estimate or observation of how the stock price responds. Each layer requires additional assumptions or evidence. Skipping layers creates false precision.
A repeatable exposure-to-market workflow
- Start with the relationship percentage.
- Define the operating shock.
- State the pass-through assumption.
- Translate the operating effect into financial statements.
- Add valuation and expectations.
- Analyze market sensitivity separately.
- Never label the relationship percentage itself as beta or hedge ratio.
- Backtest market behavior only with point-in-time relationship data.
The relationship-size versus relative-exposure guide explains what the core relationship metrics actually measure. For definitions and methodology, read the Altsets methodology. Browse Supply-Chain Data Use Cases for analyses that use exposure without turning it into a stock-price prediction.