Which of My Stocks Depend on the Same Supplier?
August 11, 2026
Altsets
Research by Altsets Research
Reverse-map the supplier sets of portfolio holdings to find common upstream companies that can create hidden concentration across otherwise unrelated stocks.
Data used:Altsets Supply Chain Intelligence: 90k+ entities, 400k+ relationships, 20+ years of history.
Key findings
- A portfolio-level supplier overlap screen reverses each holding's upstream relationship set so the same resolved supplier can be identified across multiple holdings even when the stocks have different sectors or tickers.
- Quantified cost exposure, structural-only edges, and operational replaceability should remain separate because a shared supplier can be economically trivial, economically material, or difficult to replace for different reasons.
Two stocks can look unrelated and still depend on the same supplier. That shared supplier can become a hidden portfolio concentration because one operational, regulatory, or capacity problem can reach several holdings at once.
The investing workflow is straightforward in concept: retrieve the supplier set for every holding, resolve identical suppliers to the same company entity, and then reverse the map so each supplier shows every portfolio company that depends on it. The hard part is preserving enough relationship evidence to distinguish a meaningful shared dependency from a weak or purely structural connection.
This is different from shared-customer concentration
The existing shared-customer portfolio guide asks whether several holdings depend on the same source of demand. Shared-supplier analysis asks the opposite question: whether several holdings rely on the same upstream company.
Those two risks can behave very differently. Shared customers can make several suppliers sensitive to the same demand slowdown, while a shared supplier can make several customers sensitive to the same capacity problem, product issue, regulation, or price increase.
Start by expanding each holding upstream
Micron provides a useful example of the first step because the supplied Altsets network includes upstream relationships with ASML, Lam Research, Applied Materials, KLA, and Shin-Etsu Chemical. That supplier set belongs to one portfolio holding.
A portfolio analysis repeats the same retrieval for every other holding, then groups relationships by resolved supplier entity. If ASML, KLA, or another supplier appears under several holdings, the overlap becomes visible immediately even if the customer companies sit in different sectors or countries.
Entity resolution matters more than ticker matching
A global supplier can have multiple securities, local listings, depositary receipts, subsidiaries, or historical names. If the portfolio process groups relationships only by ticker string, the same economic supplier can appear as several unrelated nodes.
The supplier overlap should therefore be calculated at the durable company-entity level first. Security identifiers are useful later for market data and investability, but the economic dependency belongs to the company.
Quantified overlap deserves a higher priority than structural overlap
A shared supplier can appear in the graph without an economic metric on every edge. That is still useful because it reveals a potential common dependency, but the portfolio should not assign invented weights to missing values.
Where cost percentages are available, the investor can compare how important the supplier appears to each holding. Where they are missing, the relationship can remain a lower-confidence flag until filings, supplier lists, product evidence, or additional data clarifies the dependency.
The portfolio question is not "who uses this supplier?"
The useful question is whether the shared supplier creates a concentration large enough to matter to the investor. A supplier can serve two holdings but represent a trivial input for both, while another supplier can be operationally difficult to replace even if its cost share is modest.
That is why shared-supplier screening should feed a research queue rather than a binary risk score. The financial materiality versus operational criticality guide explains why cost share and replacement difficulty are separate questions.
Shared suppliers can reveal hidden correlation before prices do
Traditional portfolio tools measure correlation from historical returns. A common supplier is different because it describes an economic connection that can exist even when the stocks have not moved together historically.
That does not mean the stocks will suddenly become perfectly correlated. It means the portfolio contains a common path through which one future event could affect both holdings. Dependency awareness is therefore complementary to historical correlation rather than a replacement for it.
This can change which new stock actually diversifies the portfolio
Suppose an investor is choosing between two new holdings with similar expected returns and valuations. If one candidate depends on suppliers already shared across several portfolio companies while the other brings a meaningfully different upstream network, the second candidate can provide diversification that a sector label alone would not reveal.
That is one practical way to use supply-chain data for safer stock selection. The network is not only a tool for finding risk after the portfolio is built; it can influence which stock is added in the first place.
A shared-supplier screen should stay simple
The strongest first version does not need a complex composite score. It needs a reliable company-resolution layer, a supplier set for each holding, evidence labels for quantified and structural edges, and a way to rank suppliers by how many important positions depend on them.
An API is useful once the portfolio becomes large because the same reverse-index operation can be repeated across every holding and rebalance date. A visual workspace is useful for inspecting the overlap after the candidate supplier has been found.
For portfolio-level diversification concepts, read the supply-chain diversification guide. For missing relationship metrics, read the missing-metrics guide. The Altsets documentation covers the available research interfaces, and the Altsets methodology explains relationship direction and evidence limits.