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To measure exposure accurately, combine every account into one dated position list, calculate each holding’s portfolio weight, and look through every mutual fund and ETF to its underlying holdings. Classify China exposure by a company’s domicile or primary operations—not merely its trading venue—and classify AI exposure from documented business or revenue evidence. Add direct and fund-level amounts for the same issuer only once, then report China-only, AI-only and China-plus-AI overlap.
This process tells you what you own before you decide whether the concentration is acceptable. Holdings, classifications and fund weights change, so the result needs a valuation date and a repeatable update schedule.
What “exposure” means in this audit
Portfolio exposure is the percentage of the portfolio whose economic value is tied to a defined group of companies. For this audit, measure three related but different things:
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- Indirect exposure: an issuer you own through a mutual fund, ETF or managed account.
- Overlapping exposure: an issuer that qualifies for both your China and AI definitions.
Use total market value on one valuation date as the denominator. If the portfolio is worth $250,000, a $7,500 qualifying position represents 3% exposure. Keep direct positions separate from fund positions until the look-through calculation is complete; otherwise you cannot see where the percentage came from or detect duplicate ownership.
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Exposure measurement is not a rebalance instruction. Decide in advance what percentage, issuer concentration or risk characteristic would cause you to investigate or change a holding.
Step 1: Create one complete, dated position list
Gather every account
Export or transcribe positions from taxable brokerages, IRAs and other retirement plans, managed accounts, custodial accounts and any portfolio held outside your main broker. Include securities that seem unrelated to China or AI. A broad index fund can contain a qualifying issuer even when the issuer is absent from your direct trade history.
Record the fields needed for classification
| Field | What to record | Why it matters |
|---|---|---|
| Account | Brokerage, retirement or managed-account name | Shows where concentration sits and supports account-level reporting. |
| Ticker and issuer | Ticker, legal issuer name and share class | Prevents two listings or share classes from being counted as unrelated companies. |
| Security type | Common stock, ADR, ETF, mutual fund or other security | Determines whether you classify the holding directly or look through it. |
| Market value | Value in the portfolio currency | Provides the numerator for the weight calculation. |
| Reporting date | Date and, for funds, the holdings date | Weights and classifications are time-sensitive. |
Save the original statement or export with the same date as your worksheet. If one account reports at a different date, label that mismatch rather than silently combining stale and current values.
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Step 2: Calculate each position’s baseline weight
First total the market value of all positions. For every line, calculate:
Position weight = position market value ÷ total portfolio market value
Do not assign a fund’s underlying companies to the portfolio yet. At this stage, a $20,000 ETF is a 20% fund position in a $100,000 portfolio, even though its constituents will later be allocated among China, AI and other categories.
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Keep a separate subtotal for direct securities and for each fund. This makes it possible to state, for example, that 4.0% is direct China exposure and another 2.2% is obtained through funds, rather than presenting one unexplained 6.2% figure.
Step 3: Set a consistent China definition
A listing location is not the same as a company’s economic home. The SEC-filed methodology for the Themes China Generative Artificial Intelligence ETF defines a Chinese security as one issued by a company incorporated, domiciled or primarily operating in mainland China, Hong Kong or Macau, regardless of where its shares are listed or traded. You can use that as a practical rule, provided you apply it to every holding.
Classify by domicile or primary operations
- Mark a company as China exposure when its incorporation, domicile or primary operations meet your stated mainland-China, Hong Kong or Macau test.
- Record the listing venue separately: mainland exchange, Hong Kong exchange, U.S. exchange, or another venue.
- Count a U.S.-traded ADR as China exposure when the underlying issuer meets your rule. The U.S. listing changes the trading venue, not the issuer’s domicile.
- Document a reason for borderline cases, such as a company incorporated elsewhere but deriving its primary operations from China.
| Issuer record | Required entry |
|---|---|
| Legal issuer | Name used in the company’s filing or fund holdings file. |
| Incorporation and domicile | Country or territory stated in the filing. |
| Primary operations | Where the principal business is conducted, when relevant to your rule. |
| Listing venue | Exchange and instrument type, including ADR status. |
| China result | Yes, no or uncertain, with a short source note and date. |
Do not switch between a narrow “mainland-listed only” test and a broader “Chinese business anywhere” test during the same audit. If you want both views, publish two clearly named totals.
Step 4: Define AI exposure from evidence, not labels
“AI” is not a standardized security classification. Use a documented business or revenue connection. Relevant activities can include AI infrastructure and hardware, model training or provision, cloud services, software, data centers, networking, power and cooling, and platforms used to deploy AI applications.
Use an evidence hierarchy
| Evidence level | Acceptable support | How to report it |
|---|---|---|
| High | Company filing identifies AI revenue, an AI segment, or a measurable AI business; a fund methodology states a quantitative threshold. | Count under your stated rule and cite the filing date in your notes. |
| Medium | Company filings describe material AI products or infrastructure but do not disclose a separate revenue figure. | Count only if your policy allows business exposure; label the classification as qualitative. |
| Low | Marketing language, a ticker, a fund name or a general claim that the company benefits from AI. | Do not count without corroborating evidence. |
The DRGN filing describes a thematic score based on the proportion of company revenue derived from the generative-AI industry and a 50% revenue threshold for inclusion. That threshold is a methodology for that index, not a universal definition of AI exposure. You may adopt it for a strict screen, or use a broader documented-business test, but state which one you chose.
Regulators specifically warn against treating generated or promotional information as proof. A joint SEC, NASAA and FINRA alert says, “Do Not Rely Solely on AI-Generated Information in Making Investment Decisions,” and advises investors to “Confirm the authenticity of underlying sources and review multiple sources of information before making investment decisions.” SEC Chair Gary Gensler said public companies should have a reasonable basis for AI claims and disclose the risks they face. He also warned that “AI washing” by financial intermediaries or public companies may violate securities laws. Use filings, methodology documents and other primary records instead of a chatbot summary or a fund slogan.
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Step 5: Look through every fund and ETF
Collect current constituent data
For each mutual fund or ETF, obtain the latest holdings file, shareholder report and prospectus. Record the holdings date, not just the date you downloaded the file. Investor.gov notes that a fund or ETF is not necessarily diversified when it is narrowly focused and recommends checking top holdings even when several funds appear diversified. Several funds can own the same issuer.
Fund data may not line up with your portfolio valuation date. Keep the fund’s reported date next to each constituent weight and flag a material lag. If a fund publishes only its largest holdings, label the resulting estimate as incomplete rather than treating unlisted securities as zero.
Apply the look-through formula
For each issuer in a fund, calculate:
Look-through value = fund market value × issuer weight inside the fund
Then calculate the portfolio percentage:
Look-through portfolio weight = look-through value ÷ total portfolio market value
Repeat this for every fund that reports the issuer. Preserve the fund name, holdings date and internal weight so another person can reproduce the result.
Keep direct and indirect amounts separate until deduplication
Suppose you own $20,000 of a global ETF and its dated holdings file assigns 2% to an issuer. The indirect value is $400. If you also own $1,000 of that issuer directly, the issuer’s total exposure is $1,400, not two unrelated entries. The direct portion remains $1,000 and the fund portion remains $400 for reporting.
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Step 6: Deduplicate issuers and create the three exposure buckets
Build an issuer ledger with one row per legal issuer. Add every direct position and every look-through contribution to that row. Normalize tickers, share classes and ADRs to the same underlying issuer where appropriate. Do not add an issuer twice merely because it appears in two funds.
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|---|---|
| Issuer | Canonical legal entity used for aggregation. |
| Direct market value | Total value held outside funds. |
| Indirect market value | Sum of all fund look-through amounts. |
| Total market value | Direct plus indirect, counted once. |
| China flag and basis | Result of the domicile or primary-operations rule. |
| AI flag and evidence | Result of the documented-business or revenue rule. |
| Accounts and funds | Locations contributing to the total. |
Assign each issuer to one or more reporting sets:
- China only: China flag yes, AI flag no.
- AI only: AI flag yes, China flag no.
- China-plus-AI overlap: both flags yes.
The overlap is not an extra amount to add on top of China and AI totals. It is the intersection that explains how much of each total shares both characteristics.
Worked example with hypothetical numbers
The following illustration uses a $100,000 portfolio and invented holdings to show the arithmetic; it is not a recommendation or a statement about any real fund.
| Holding | Portfolio value | Relevant fund weight | Look-through value |
|---|---|---|---|
| Direct Chinese AI issuer A | $4,000 | — | — |
| Direct U.S. AI issuer B | $6,000 | — | — |
| Global ETF | $30,000 | Issuer A 2%; issuer C 4%; issuer D 1% | A $600; C $1,200; D $300 |
| China-focused ETF | $10,000 | Issuer C 8%; issuer D 5% | C $800; D $500 |
Issuer A totals $4,600 after combining the $4,000 direct position and $600 from the global ETF. Issuer C totals $2,000 from the two funds; issuer D totals $800. Assume A and C meet the China rule, A and B meet the AI rule, and C is not an AI issuer under your evidence policy.
China exposure is therefore A $4,600 plus C $2,000 plus D $800, or $7,400 (7.4%). AI exposure is A $4,600 plus B $6,000, or $10,600 (10.6%). China-plus-AI overlap is A’s $4,600 (4.6%). Issuer C’s two fund contributions are combined before reporting, so its $2,000 is not counted twice.
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A useful report has a summary table and a concentration table. Include the calculation date, the fund holdings dates and the definitions used.
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| Bucket | Total market value | Portfolio percentage | Direct | Indirect |
|---|---|---|---|---|
| China only | Calculated from issuer ledger | Total ÷ portfolio value | Direct contributions | Fund contributions |
| AI only | Calculated from issuer ledger | Total ÷ portfolio value | Direct contributions | Fund contributions |
| China-plus-AI overlap | Intersection of both flags | Total ÷ portfolio value | Direct contributions | Fund contributions |
| Concentration view | What to show |
|---|---|
| Largest issuer | Issuer name, total value, portfolio percentage and China/AI classification. |
| Largest fund contribution | Fund, issuer, internal weight, look-through value and holdings date. |
| Account concentration | China, AI and overlap percentages by brokerage, retirement or managed account. |
| Top-five aggregate | Sum of the five largest qualifying issuers, with direct and indirect portions. |
For a fund comparison, add methodology, rebalancing schedule, management fee and risk disclosures. For example, the Themes China Generative Artificial Intelligence ETF registration statement lists a 0.39% annual management fee. The index had 24 companies as of December 31, 2025, and its methodology uses a 50% revenue-based thematic exposure threshold. Those figures describe that specific product and date; they are not assumptions to apply to every AI or China fund.
Check hidden exposure in broad index funds
- List every fund, even one marketed as global, diversified or broad-market.
- Download the latest holdings file and note its “as of” date.
- Search the file for each issuer already marked China or AI.
- Search for additional issuers using your domicile and evidence rules, not only ticker names.
- Multiply the fund value by each internal weight.
- Repeat across all funds and merge the issuer rows.
- Compare the resulting look-through total with the fund’s stated sector or country description; investigate large differences.
A fund’s top-ten list is a useful first pass, but it is not a complete look-through. If the full holdings file is unavailable, report that limitation and avoid presenting a partial list as a precise percentage.
Understand the risks after measuring exposure
The DRGN prospectus warns that Chinese markets may involve greater volatility and political, information and pricing risks. China-focused and AI-focused funds can also be concentrated, sensitive to rapid technology changes and exposed to regulatory scrutiny. These are reasons to examine the evidence and concentration, not reasons to assume that any particular percentage is automatically unsuitable.
Separate factual classification from the decision that follows. Write a policy before reviewing the result, such as a maximum percentage for China, a maximum single-issuer weight, a limit on thematic funds, or a requirement that AI exposure meet a revenue threshold. Consider account location and tax consequences separately; the same economic exposure can have different practical effects in taxable and retirement accounts.
Set a maintenance schedule
Save a dated copy of the ledger and the holdings files used. Re-run the audit after material trades, when a fund publishes an updated holdings file or prospectus, after an index rebalance, and at a regular review interval you can maintain. Recheck issuers whose domicile, operations or AI revenue disclosures change.
Every report should state:
- Portfolio valuation date and currency.
- Each fund’s holdings date.
- China definition, including treatment of Hong Kong, Macau and ADRs.
- AI evidence rule, including any revenue threshold.
- Whether derivatives, cash or incomplete holdings data were excluded or treated specially.
- Largest issuer, largest fund contribution and account-level concentration.
A dated, reproducible ledger turns a vague question—“How much China or AI do I own?”—into a measurable answer that can be compared from one review to the next.
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