How to Check a Small-Cap Fund’s Portfolio Overlap and Concentration Risk

To see whether your small-cap funds are really diversifying you, use dated holdings files, normalize each security to a common issuer identifier, and weight every position by the dollars you have in each fund. Then measure overlap at the security, issuer, sector and industry levels, and calculate concentration inside each fund and in your combined portfolio. A fund’s label alone cannot reveal duplicated positions or the risk created when several funds own the same volatile small-cap companies.

What portfolio overlap and concentration mean

Portfolio overlap is the amount of the same exposure held through two or more funds. The exposure can be defined narrowly as the identical security, more broadly as the same issuing company, or economically as companies that depend on the same industry or business driver. Your result is only meaningful if you state which definition you used.

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Concentration risk is the size of a portfolio’s exposure to a small number of holdings, issuers, sectors or industries. A fund can own hundreds of stocks and still be concentrated if its largest 10 positions dominate assets or if many holdings belong to one industry. FINRA warns that “Simply holding only funds doesn’t shield you from concentration risk.”

Small-cap stocks are generally less established and can be more volatile and less liquid than larger companies. If two funds duplicate a small-cap position, a market decline, company-specific problem or liquidity shock can affect more of your portfolio than the fund names suggest.

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1. Collect holdings with the correct date

Start with each fund’s latest complete holdings file, not a marketing fact sheet. Download it from the fund issuer or from the U.S. Securities and Exchange Commission’s Form N-PORT data. Form N-PORT is the monthly portfolio-holdings report for registered management investment companies and qualifying exchange-traded funds; the SEC provides downloadable datasets. Record the portfolio date shown in every file because holdings change after the reporting date.

Record these fields

• Fund name, ticker, share class and legal identifier.
• Portfolio date and the date you downloaded the file.
• Security name, ticker, CUSIP, ISIN or another identifier supplied by the file.
• Shares or principal amount, market value and portfolio percentage.
• Issuer name, sector, industry, market-cap or style classification when supplied.
• Benchmark, expense ratio, turnover and liquidity information for the comparison stage.

Do not combine holdings from different dates without labeling the mismatch. A fund that reports at month-end can buy or sell a position before another fund’s file is published. Your calculation is a dated risk snapshot, not a real-time statement of ownership.

2. Decide what counts as the same exposure

Choose an overlap rule before you calculate anything. Use one rule for the primary result and, if useful, show broader definitions separately.

Same-security overlap is the cleanest and most reproducible test. Same-issuer overlap is usually more useful when one fund holds multiple share classes or when ticker symbols have changed. Economic relationships require judgment, so report the classification source and avoid presenting them as exact duplicate ownership.

3. Normalize identifiers before matching

Raw ticker matching is unreliable. Tickers can change, the same company can have multiple share classes, and names can differ because of punctuation, abbreviations or corporate actions.

1. Prefer a stable identifier. Use CUSIP, ISIN or the identifier supplied by the issuer or filing. Keep the original ticker for display, but match on the stable field when available.
2. Map ticker changes. Use the issuer name and identifier history to connect an old ticker with its current security. Do not assume that two identical tickers in different markets represent the same company.
3. Group share classes deliberately. Keep separate share classes for a same-security analysis; group them under one issuer for a company-risk analysis.
4. Resolve spelling variants. Standardize capitalization, punctuation and legal suffixes, then verify that the identifiers refer to the same issuer.
5. Document exceptions. Keep a mapping sheet showing the original value, normalized identifier, issuer and the reason for any manual change.

Exclude cash, derivatives and index instruments from a simple stock-overlap report unless you have a method for looking through them. A futures contract or swap can create economic exposure without appearing as a duplicated common-stock line item.

4. Weight overlap by your actual fund allocations

Counting repeated tickers treats a 0.05% position the same as a 6% position. Instead, multiply each fund’s weight in your personal portfolio by that fund’s weight in the security.

Portfolio contribution = your fund allocation × the fund’s security weight.

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If Fund A is 60% of your portfolio and holds Stock X at 4%, Stock X contributes 2.4% to your total portfolio (0.60 × 0.04). If Fund B is 25% of your portfolio and holds the same stock at 3%, it contributes another 0.75%. Your combined exposure to Stock X is therefore 3.15% before considering any direct holding.

This dollar-weighted approach is the same logic used by Morningstar’s Stock Intersection analysis, which identifies the largest stocks concentrated across a portfolio and attributes each stock’s total contribution across funds. In one Morningstar example, Microsoft’s combined contribution is 3.98% based on holdings in two funds.

5. Calculate overlap at several levels

Security and issuer overlap

Create one row for each normalized security and sum its portfolio contributions across funds. Sort the result from largest to smallest. The top rows show where duplicated ownership matters financially, rather than merely where two files contain the same name.

For issuer overlap, group all normalized securities belonging to the same company before summing. This catches cases in which one fund owns one share class and another owns a different class. Report both the issuer’s combined percentage and the funds supplying it.

Pairwise fund overlap

For each fund pair, calculate the percentage of Fund A’s assets that also appears in Fund B and the percentage of Fund B’s assets that appears in Fund A. These directional figures can differ when one fund is broad and the other is narrow. Also report the dollar-weighted overlap in your own portfolio, because a small allocation to a highly overlapping fund may matter less than a large allocation to a moderately overlapping fund.

Sector and industry overlap

Aggregate each fund’s holdings by sector and industry, then repeat the aggregation after applying your personal fund allocations. Two funds can have similar technology weights while owning different companies, or different technology weights while both owning large technology-adjacent businesses. Sector exposure and stock exposure answer different questions and should not be substituted for one another.

6. Measure concentration inside each fund

Top-10 concentration

Add the percentages of the 10 largest holdings. Morningstar defines top-10 concentration as the aggregate percentage of assets in those 10 positions. A higher figure means more of the fund depends on a small group of securities, even if the fund has many smaller positions.

Largest single issuer

Record the biggest security weight and the biggest issuer weight. The issuer measure should combine share classes and other securities from the same company. A fund may have no unusually large individual line item but still have a large company exposure after those lines are grouped.

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Sector and industry weights

List the largest sector and industry percentages. Industry concentration is often more informative than broad-sector concentration for small-cap funds because several industries can sit inside one sector while facing different competitive and regulatory risks.

Herfindahl-Hirschman Index

The HHI is the sum of squared holding weights. Use decimal weights in the calculation: HHI = Σ(weight × weight). If a fund has four equal positions of 25%, its HHI is 0.25 (0.0625 × 4). If it has 100 equally weighted positions, the HHI is 0.01. Larger values indicate greater concentration because large positions receive disproportionate weight when squared.

Calculate HHI separately for individual securities, issuers, sectors and industries when your data supports it. Do not compare an issuer HHI with a sector HHI as if they were the same measure; the grouping changes the meaning. Morningstar’s methodology uses squared weights and interprets larger values as greater concentration.

7. Recalculate concentration after combining funds

Run the same top-10, largest-issuer, sector and HHI tests on your combined portfolio. A fund can look diversified by itself but create a large position when paired with another fund or a direct stock.

For each normalized holding, add all portfolio contributions from every fund and direct position. Sort the combined list and calculate the metrics from those combined weights. Then repeat the process after grouping by issuer, sector and industry. This reveals whether your apparent diversification is only diversification of fund wrappers.

8. Decide whether a second small-cap fund adds diversification

Do not decide from “value,” “growth” or “small-cap” labels. Compare what the second fund actually changes in your total portfolio.

The second fund adds more diversification when it lowers meaningful issuer, industry or style concentration without simply replacing one set of similar small-cap risks with another. A lower stock-overlap percentage alone is not enough if both funds are concentrated in the same industry or respond to the same economic driver.

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A spreadsheet is sufficient for a household portfolio if the files are manageable and you keep the source dates.

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1. Create an Inputs sheet. Enter each fund, your allocation percentage, holdings date and source file name. Add direct securities as funds with a 100% holding weight.
2. Create a Holdings sheet. Paste one row per holding with fund, normalized identifier, issuer, sector, industry, fund weight and portfolio date.
3. Add the contribution column. Use a formula equivalent to =FundAllocation*FundWeight. Confirm that each fund’s holdings add to approximately 100%, allowing for cash and reporting conventions.
4. Build a security pivot table. Use normalized identifier as the row, issuer as a label and contribution as the value. Sort descending to find duplicated exposures.
5. Build an issuer pivot table. Group by issuer and sum contribution. This is your company-level overlap list.
6. Build sector and industry pivots. Use the same contribution field, not raw fund weights, so the results reflect your dollars.
7. Calculate top-10 concentration. Sort each fund and the combined portfolio by contribution or fund weight, then sum the first 10 rows.
8. Calculate HHI. For each chosen grouping, square every weight and sum the squares. Keep the unit and grouping in the worksheet title.
9. Add a change column. Compare the current result with the prior dated file, noting new positions, sales, ticker changes and allocation changes.

Keep a separate mapping tab for identifier corrections and a notes column for classifications that required judgment. That audit trail makes the result reproducible when a ticker or issuer name changes.

10. Worked illustrative example

The following numbers are illustrative, not a forecast or a claim about any particular fund. Suppose you own 50% of Fund A, 30% of Fund B and 20% of Fund C. After normalization, the largest combined contributions are:

Issuer 1 is the first review priority because it is the largest repeated company exposure, not because it appears in the most funds. You would next check whether the four issuers sit in the same industry, whether the combined top 10 has become unusually large, and whether Fund C changed the portfolio’s style or benchmark exposure. The example demonstrates the method; it does not establish a safe or unsafe percentage.

11. Interpret the numbers without false precision

There is no universal overlap percentage at which a portfolio becomes unacceptable. The appropriate level depends on your mandate, total assets, other accounts, time horizon, liquidity needs and tolerance for company-specific and sector-specific losses. Use the metrics to identify exposures that deserve a decision, not as an automatic buy or sell signal.

Morningstar’s methodology notes that higher idiosyncratic risk is not always compensated by higher returns and that lower concentration is preferable for investors trying to avoid security-specific and sector-specific risks. That is a risk preference, not a promise that a less concentrated portfolio will outperform.

• High same-security overlap with low sector overlap suggests duplicated companies but different industry exposure elsewhere.
• Low stock overlap with high industry overlap suggests the funds own different companies exposed to a common economic cycle.
• High top-10 concentration and high issuer HHI indicate dependence on a few companies.
• High sector HHI with moderate issuer overlap indicates a broad set of companies making one large sector bet.
• Low overlap can still leave substantial small-cap volatility, liquidity risk or style risk if both funds use similar mandates.

12. Common errors and how to correct them

Using the latest factsheet as if it were current

Factsheets may summarize a previous month or quarter. Use the portfolio date in the holdings file and state it beside every result.

Counting tickers instead of dollars

Repeated names do not show economic importance. Apply your fund allocations and each fund’s holding weight before ranking overlap.

Matching names without identifiers

Different share classes, renamed companies and ticker reuse can create false matches or missed matches. Normalize identifiers and keep your mapping notes.

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Calling sector overlap stock overlap

Two funds can share a sector while owning different issuers. Report sector, industry and security results in separate columns.

Ignoring direct holdings

A stock held outside the funds can turn a modest fund overlap into a large total position. Add direct securities to the same contribution table.

Treating HHI as a complete risk score

HHI describes distribution of weights, not valuation, liquidity, leverage, correlation or expected return. Pair it with issuer, sector, style and liquidity checks.

Assuming filings are real time

Holdings can change between reporting dates. Label the analysis as of the file date and avoid claiming it represents today’s exact positions.

13. Set a monitoring rule

Save the date, files, identifier map and calculations each time you run the review. Re-run when any of these events occurs:

• A fund publishes a new holdings file or Form N-PORT report.
• You add, sell or materially resize a fund or direct stock.
• A fund announces a major rebalance, merger, benchmark change or style change.
• A ticker, share class or issuer identity changes.
• You are considering another small-cap position.

Compare the new and prior tables rather than relying on memory. Investigate large changes in top-10 share, issuer contribution, sector HHI or style exposure, and write down whether the change came from trading, price movement, a classification change or your own allocation.

What this analysis can and cannot tell you

This process tells you where your current reported exposures overlap and how unevenly they are distributed. It can reveal duplicated issuers that fund labels hide, show whether a proposed fund changes your sector or style mix, and identify positions to review with your broader financial plan.

It cannot predict a specific loss from a given overlap percentage, guarantee diversification during a market shock or replace an assessment of taxes, liquidity, risk capacity and investment objectives. Treat the output as a repeatable risk screen built from dated holdings, not as a return forecast.

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