Analyst Overlap and Supply-Chain Overlap Are Not the Same Network
September 14, 2026
Altsets
Research by Altsets Research
Analyst coverage measures shared information attention. Supply-chain data measures economic dependence. Combining both can test whether a connected-company signal reflects a real commercial path, an attention network, or both.
Data used:Altsets Supply Chain Intelligence: 90k+ entities, 400k+ relationships, 20+ years of history.
Key findings
- The supplied Nvidia relationships define a real economic network because Nvidia represents 17.62% of Micron revenue and 27.88% of SK Hynix revenue in the displayed data.
- Research on shared analyst coverage finds that information-attention networks can explain several momentum spillover effects, making analyst overlap an important competing explanation rather than a substitute for economic relationship data.
Analyst overlap and supply-chain overlap measure different things. Analyst coverage tells you which companies are being processed by the same information intermediaries. Supply-chain data tells you which companies are connected by real economic dependence. When both networks point to the same pair, the investor can ask whether information is likely to travel quickly. When the economic link exists without much shared attention, the relationship can become a more interesting place to test for underprocessed information.
Nvidia, Micron, and SK Hynix create the economic network first
The supplied Altsets data shows Nvidia as a major customer of both Micron and SK Hynix. Nvidia represents 17.62% of Micron revenue and 27.88% of SK Hynix revenue in the displayed relationships. That is the economic network. It exists because the companies do business with one another, not because analysts happen to cover them.
An analyst network asks a different question: are the same analysts following the connected firms, and therefore likely to process information from both sides? Recent research finds that analysts who follow both a supplier and its customer can produce more accurate supplier forecasts, with the likelihood of joint coverage increasing alongside the strength of the economic tie.
Shared analyst coverage can be a competing explanation for return spillovers
This distinction becomes important in quantitative research. Cohen and Frazzini documented return predictability across customer-supplier relationships. Later NBER research on shared analyst coverage found that a connected-stock momentum factor based on common analyst coverage could subsume several previously documented momentum spillover effects, including customer-related effects.
That does not make supply-chain data irrelevant. It changes the question. If a customer-supplier signal disappears after controlling for shared analyst attention, the researcher has evidence that information-processing structure may explain the return pattern. If an economic relationship remains informative even after analyst-network controls, the supply-chain path is harder to dismiss as merely an attention artifact.
The most interesting pairs may be economically close but informationally far apart
A heavily followed pair can transmit information quickly because many analysts, investors, and models already watch both companies. A supplier with a major customer but little shared analyst coverage may have a different information environment.
That creates a useful two-dimensional screen. One axis measures economic connection using supplier revenue share, customer cost share, relationship size, or structural evidence. The other measures information overlap using analyst coverage. A relationship can be economically strong and informationally crowded, economically strong and relatively underfollowed, or weak on both dimensions.
The investor should not assume the underfollowed quadrant contains alpha. It is simply a better-defined hypothesis. The supply-chain graph says the companies have a reason to matter to one another. The analyst network says how many professional information intermediaries are already likely to connect the dots.
This also changes how an investor reads analyst revisions
If an analyst follows Nvidia and Micron, that analyst has direct access to both sides of an economically important relationship. Research on supply-chain analyst coverage finds that following a supplier's customer is associated with improved supplier forecast accuracy after customer earnings announcements. That supports the idea that the customer information is useful, while also showing that sophisticated intermediaries can absorb some of the signal.
The investment edge therefore may not be the existence of the relationship. It can be knowing which relationships are economically important before deciding whose revisions, reports, or attention patterns deserve comparison.
The conclusion is that economic networks and information networks should be kept separate
Supply-chain data answers who depends on whom. Analyst coverage answers who is being jointly processed by the same information intermediaries. Those networks can overlap, but they are not substitutes. Combining them creates a sharper research question: does a known economic relationship still produce useful information after accounting for how much professional attention already connects the two companies?
The customer analyst-revisions guide explains how analyst expectations can be paired with relationship data. The causal spillover guide explains why alternative explanations need to be controlled before a return pattern is called a supply-chain effect.
For relationship definitions and evidence limits, read the Altsets methodology.