Building a Custom Stock Index With Supply-Chain Risk Limits
August 15, 2026
Altsets
Research by Altsets Research
Add customer, supplier, and network exposure limits to conventional custom-index rules so sector, country, and position caps do not hide economic dependence between constituents.
Data used:Altsets Supply Chain Intelligence: 90k+ entities, 400k+ relationships, 20+ years of history.
Key findings
- A custom index can hold Micron and Nvidia as separate constituents even though Nvidia represents 17.62% of Micron revenue in the displayed relationship data, creating an indirect customer dependency that ordinary constituent weights do not describe.
- Portfolio weight multiplied by supplier-revenue exposure can form a first-order look-through measure for a constraint, but it should remain separate from direct issuer weight, stock beta, and expected return.
Cap supply-chain risk in a custom stock index by measuring each candidate's important customer and supplier links, aggregating repeated dependencies across constituents, and constraining or penalizing weights that concentrate the index around one external company. These limits supplement sector, country, and position-size constraints rather than replacing them.
The supplied Altsets data gives a simple example. Nvidia is associated with 17.62% of Micron revenue. If a custom index holds both Micron and Nvidia, those positions are not economically independent just because each has its own ticker and index weight. The Micron position contains a measurable customer relationship to another constituent.
A market-cap weight does not describe economic dependence
Traditional equity indices commonly weight companies by float-adjusted market capitalization, while other index designs can use equal weighting, caps, factors, or other systematic rules. Those methods determine how much influence each stock has on index performance. They do not automatically describe whether one constituent depends on another for revenue or whether several constituents share the same supplier.
A supply-chain overlay does not need to replace market-cap, equal-weight, or factor weighting. It can sit beside them as a separate risk constraint. The index can still start from a conventional universe and weighting method, then test whether the resulting holdings create hidden customer, supplier, or network concentration.
A first-order look-through measure can make the issue visible
Suppose Micron receives a 4% weight in a custom index. Multiplying the 4% portfolio weight by Micron's 17.62% mapped Nvidia revenue exposure gives 0.7048% as a first-order portfolio-weighted share of Micron's position linked to Nvidia customer revenue.
That derived number is not a stock beta, expected loss, or forecast. It is a look-through accounting measure that helps compare one holding's indirect commercial dependence with another holding's indirect dependence. The direct Nvidia index weight should remain a separate quantity rather than being casually added to 0.7048% and labeled total "Nvidia risk."
The index can impose more than one supply-chain limit
A useful custom benchmark can distinguish direct issuer concentration from indirect relationship concentration instead of compressing everything into one score.
| Constraint | What it controls | Example interpretation |
|---|---|---|
| Single-stock cap | Direct market exposure | No company exceeds a chosen index weight |
| Customer look-through cap | Revenue dependence inside suppliers | Limit portfolio-weighted revenue exposure to one customer |
| Shared-supplier cap | Common upstream dependency | Limit how many large positions depend on the same supplier |
| Network-cluster cap | Common economic cycle | Reduce simultaneous exposure to a tightly connected chain |
The thresholds themselves depend on the mandate. The important design decision is that each constraint measures a different object.
Supply-chain limits can change constituent weights without changing the stock universe
Imagine a growth-oriented index that already wants to own Micron and Nvidia. A supply-chain rule does not have to remove either company. It could simply reduce one weight when the indirect customer dependence pushes the portfolio beyond a chosen limit.
The same logic applies when several holdings share one customer. A sector-neutral portfolio can still contain multiple suppliers whose revenue depends on the same buyer. A customer look-through constraint can reduce that concentration while preserving the broader investment theme.
The overlay should use comparable denominators
Supplier revenue percentage is appropriate when the question is how much a customer matters to a supplier. Customer cost percentage answers the opposite question. Those values should not be mixed into one index formula as though they are interchangeable.
This matters because an index rule must be reproducible. If one stock is scored by supplier revenue exposure and another is scored by customer cost exposure, the resulting ranking can look precise while measuring two different things. The relationship-size versus relative-exposure guide explains why the denominator needs to stay attached to the metric.
Structural relationships can still create a constraint
Not every edge needs a percentage to affect index construction. If several holdings share the same structural customer or supplier, the index can flag the cluster for review even when some economic metrics are missing. Quantified relationships can then determine which overlaps deserve the strongest weight adjustment.
This is especially useful in portfolios where diversification is currently measured only by sector and country. The supply-chain diversification guide explains why those classifications can miss a common economic driver.
Rebalancing needs point-in-time relationship data
A custom index becomes a backtest as soon as historical performance is shown. That means the relationship state used at each rebalance must have been observable at that time. Current customer links cannot be projected backward into old index weights without creating look-ahead bias.
The same rule applies when a relationship changes magnitude or disappears. A supply-chain constraint should be recalculated from the snapshot available on the rebalance date. The point-in-time backtesting guide covers the historical-data requirement in more detail.
This creates a genuinely different benchmark
A sector-capped index asks whether too much capital sits in one industry. A country-capped index asks whether too much sits in one jurisdiction. A supply-chain-constrained index asks whether apparently separate companies depend on the same economic relationships.
Those approaches can coexist. The supply-chain version is useful precisely because it adds information that market capitalization, GICS classification, and country domicile were not designed to capture.
The Altsets documentation explains the interfaces available for programmatic relationship research. A visual workspace can help discover the shared nodes first, while an API is more appropriate when the same constraint has to be recalculated across an entire index at every rebalance.
For metric definitions and evidence limits, read the Altsets methodology. Browse Supply-Chain Data Use Cases for other portfolio and stock-selection applications.