OpenAI

What it captures

Direct exposure to Henry Hub natural gas spot prices through front-month futures, tracking the primary marginal fuel for US electricity generation in data center regions.

What it misses

Does not capture regional basis differentials or the electricity conversion spread; misses hedging, PPAs, or renewable energy offsets; suffers from contango roll costs in normal market conditions.

Why the price could fall

May be harmed if natural gas prices spike — the same driver that elevates electricity costs in US regions where the subject relies on gas-fired power for compute infrastructure, compressing unit economics on inference and training.

Materiality: medium · Confidence: medium · Short term (0–12 months)

Expense ratio 0.012% Holding weights are shown only when published by the issuer — the exposure may be material or incidental; check the fund’s current holdings.

What it captures

Natural gas is a primary fuel for electricity generation in US data center regions, directly affecting the marginal cost of power for training runs and inference workloads at multi-megawatt scale.

What it misses

Does not capture coal, nuclear, hydro, or renewable generation mix variation across data center locations; misses long-term power purchase agreements that may lock in fixed rates.

Why the price could fall

May be harmed if natural gas prices surge — the same driver that raises electricity costs in gas-dependent US power grids where the subject operates data centers, compressing margins on compute-intensive training and inference.

Materiality: medium · Confidence: medium · Short term (0–12 months)

What it captures

Concentrated exposure to publicly traded companies focused on generative AI technologies including LLM platforms, chip makers, and cloud providers directly relevant to OpenAI's supply chain and competitive landscape.

What it misses

No direct OpenAI equity exposure; fund holdings are public proxies rather than pure-play LLM application layer peers.

Materiality: high · Confidence: high · Medium term (1–3 years)

Expense ratio 0.75% Holding weights are shown only when published by the issuer — the exposure may be material or incidental; check the fund’s current holdings.

What it captures

Thematic exposure to companies generating revenue from AI technologies including natural language processing, machine learning platforms, and AI-enabled software — direct overlap with OpenAI's product categories.

What it misses

No OpenAI equity holding; captures public AI software and platform companies rather than pure-play LLM application layer.

Materiality: medium · Confidence: high · Medium term (1–3 years)

Expense ratio 0.45% Holding weights are shown only when published by the issuer — the exposure may be material or incidental; check the fund’s current holdings.

What it captures

Broad exposure to publicly traded AI software, semiconductor, and cloud infrastructure companies that form the ecosystem OpenAI relies on and competes within.

What it misses

Does not hold OpenAI directly; includes many non-LLM AI businesses with limited economic overlap to generative AI business models.

Materiality: medium · Confidence: medium · Medium term (1–3 years)

Expense ratio 0.68% Holding weights are shown only when published by the issuer — the exposure may be material or incidental; check the fund’s current holdings.

What it captures

Diversified credit exposure to investment-grade corporate debt including technology sector issuers (Microsoft, NVIDIA, Amazon, Oracle) whose credit quality correlates with AI infrastructure investment cycle.

What it misses

Does not isolate OpenAI-specific ecosystem exposure; broadly diversified across sectors with technology comprising roughly 20-25% of portfolio, diluting AI-related credit sensitivity.

Why the price could fall

May be harmed if rising interest rates or recession fears drive broad credit spread widening across investment-grade universe, overwhelming positive fundamental trends in AI-exposed technology credits.

Materiality: low · Confidence: medium · Medium term (1–3 years)

Expense ratio 0.14% Holding weights are shown only when published by the issuer — the exposure may be material or incidental; check the fund’s current holdings.

What it captures

Global exposure to AI hardware, software, and enabling technologies including semiconductor, data infrastructure, and automation platforms overlapping OpenAI's upstream dependencies.

What it misses

Includes robotics and industrial AI with limited connection to LLM economics; diluted exposure to generative AI specifically.

Materiality: low · Confidence: medium · Long term (3+ years)

Expense ratio 0.68% Holding weights are shown only when published by the issuer — the exposure may be material or incidental; check the fund’s current holdings.

What it captures

Exposure to US-listed AI and robotics companies including cloud platforms, semiconductor makers, and software firms participating in AI infrastructure and application markets.

What it misses

Robotics focus dilutes LLM-specific exposure; lacks direct access to OpenAI or comparable private LLM application players.

Materiality: low · Confidence: medium · Long term (3+ years)

Expense ratio 0.65% Holding weights are shown only when published by the issuer — the exposure may be material or incidental; check the fund’s current holdings.

What it captures

Broad commodity basket including energy (WTI crude, heating oil, natural gas) and metals used in data center construction and chip manufacturing, providing aggregated input cost exposure.

What it misses

Diluted signal due to agricultural commodities and non-relevant exposures; does not isolate electricity or semiconductor-specific material costs; rebalances reduce precision.

Why the price could fall

May be harmed if broad commodity inflation elevates energy and industrial input costs — the same drivers that pressure data center power expenses and semiconductor fabrication costs affecting the subject's infrastructure stack.

Materiality: low · Confidence: low · Medium term (1–3 years)

Expense ratio 0.87% Holding weights are shown only when published by the issuer — the exposure may be material or incidental; check the fund’s current holdings.

What it captures

WTI crude oil price exposure, which indirectly affects electricity generation costs in oil-dependent grids and is a proxy for broader energy inflation impacting data center operating expenses.

What it misses

US electricity generation is dominated by natural gas, coal, nuclear, and renewables — oil accounts for less than 1% of grid power; overstates the direct relationship to data center electricity costs.

Why the price could fall

May be harmed if oil prices surge — a general energy inflation signal that correlates with broader power cost pressures, though the direct link to data center electricity is weak given oil's minimal role in US grid generation.

Materiality: low · Confidence: low · Medium term (1–3 years)

Expense ratio 0.79% Holding weights are shown only when published by the issuer — the exposure may be material or incidental; check the fund’s current holdings.