Global X Thematic Model Portfolio
A systematic approach to allocating across structural investment themes.
A disciplined framework for thematic allocation
The Global X Thematic Model Portfolio is a hypothetical model portfolio that demonstrates a systematic allocation process across the Global X thematic ETF range. The portfolio is not an investable product, does not involve actual capital, and all performance shown is simulated. Holdings, weights, portfolio changes and performance are published on this page and updated at each rebalance.
Thematic ETFs provide targeted exposure to structural growth areas including artificial intelligence, semiconductors, defence technology and infrastructure. Allocating across these themes introduces a distinct set of decisions: which exposures to hold, how to size them, and when to adjust as market leadership rotates. The Thematic Model Portfolio illustrates a disciplined, rules-based framework for making these decisions.
Theme selection
A broad market-data model scores and ranks the eligible thematic ETF universe.
Risk-aware sizing
Inverse volatility weighting adjusts position sizes according to recent market risk.
Governance review
Global X Investment Committee oversight validates each rebalance before publication.
Machine learning expertise, paired with Global X thematic oversight
The portfolio is developed in partnership with WealthSpot LLC, a New York-based investment management firm specialising in the application of machine learning to portfolio construction. WealthSpot provides the selection model that scores and ranks the ETF universe. Global X provides the thematic ETF universe and oversees the portfolio through its Investment Committee, which reviews and validates each rebalance prior to publication.
WealthSpot
Selection model, scoring and ranking
Global X
ETF universe, governance and publication
Three stages, applied consistently at every rebalance
The portfolio is constructed through a three-stage process applied consistently at each rebalance.
Scoring
WealthSpot's model evaluates each ETF in the thematic universe using a broad set of market data inputs, including price and volatility characteristics. These inputs are assessed in combination rather than in isolation, and each ETF is assigned a score.
Selection
The highest-scoring ETFs are selected for inclusion, up to a defined maximum number of holdings. This maintains concentration in the strongest-scoring themes while limiting dependence on any individual exposure.
Weighting
Selected ETFs are weighted using an inverse volatility methodology. Exposures with lower recent volatility receive proportionally larger weights, and exposures with higher recent volatility receive smaller weights.
The same methodology governs every rebalance. Portfolio changes are published on this page at each update, accompanied by commentary on the composition of the portfolio and the drivers of any changes.
Current portfolio
View the latest holdings, weights and simulated performance, updated at each rebalance.
Holdings and weights
Index ticker | ETF ticker | ETF name | 27 Feb 2026 weight | 31 Mar 2026 weight | Weight diff (%p) |
|---|---|---|---|---|---|
IPAVE INDEX | Global X US Infrastructure Development ETF | 19.40% | 19.37% | -0.03 | |
IAIQ INDEX | Global X Artificial Intelligence ETF | 17.87% | 18.56% | +0.69 | |
NYFANG INDEX | Global X FANG+ ETF | 17.84% | 18.17% | +0.33 | |
IBUGT INDEX | Global X Cybersecurity ETF | 12.71% | 13.79% | +1.08 | |
GXCT20HN INDEX | Global X China Tech ETF | 12.68% | 13.49% | +0.82 |
Performance
Illustrative dummy data for design purposes only. All performance displayed for the model portfolio is simulated and does not represent actual investment returns. Past performance is not a reliable indicator of future performance.
Hypothetical results derived from simulation, not actual trading. Returns are calculated on index levels reduced by each fund's expense ratio, not on the funds themselves. Net of a 0.2% one-way transaction cost and a 0.3% annual management fee assumption; the benchmark bears no management fee. Past performance is not a reliable indicator of future performance. Full methodology and simulation assumptions available on request.
When interpreting the performance of this portfolio you should take into consideration the limitations inherent in model portfolio performance.
The paper portfolio was launched on DD/MM/YYYY. Returns prior to this period are simulated. Returns for periods greater than one year are annualised.
Investment Committee
Each model rebalance is reviewed and validated By the GlobalX Investment Committee before publication.
Billy Leung
Senior Investment Strategist
Chris Wolak
Head of Portfolio Management