Thru May 1, 2026
Introduction: The Kaleidoscope Thematic Equity Model Portfolio
The Kaleidoscope Thematic Equity Model Portfolio is the core thematic allocation framework behind ETFThemes.com. It is designed to provide investors with a structured, diversified lens for participating in the long-term forces reshaping the global economy through liquid thematic ETFs.
The model is built as a passive, rules-based allocation rather than a tactical trading portfolio. Its objective is to capture secular growth across multiple independent innovation cycles while maintaining disciplined exposure control across changing macro regimes. The portfolio is reviewed through a consistent attribution framework, allowing investors to evaluate which themes are leading, which are lagging, and how market leadership is rotating over time.
At its foundation, the model allocates across 25 liquid thematic ETFs organized into four broad macro-sensitive pillars:
| Thematic Pillar | Strategic Role in the Portfolio |
| Commodities | Captures resource scarcity, inflation sensitivity, electrification demand, metals, mining, and real-asset exposure. |
| Industrial | Provides exposure to infrastructure, automation, advanced manufacturing, energy-system modernization, and reshoring themes. |
| Technology | Represents the portfolio’s largest structural-growth allocation, including AI, semiconductors, cloud, cybersecurity, fintech, digital assets, and internet platforms. |
| Consumer | Reflects housing-linked demand, mobility, digital leisure, experiential spending, and evolving consumption patterns. |
The model’s broad thematic architecture is intended to reduce reliance on any single market narrative. Commodities may lead during periods of inflation pressure or geopolitical stress. Industrial themes may benefit from infrastructure spending, reshoring, and energy-transition investment. Technology themes tend to respond most strongly to liquidity, AI capital spending, and risk appetite. Consumer themes connect the portfolio to household balance sheets, confidence, housing, and discretionary spending cycles.
The portfolio uses a quarterly rebalance discipline to keep exposures aligned with their intended structural roles. Extended themes are trimmed, lagging exposures are reset toward target weights, and concentration risk is controlled. This approach allows the model to participate in thematic leadership rotation without relying on short-term market timing.
The monthly attribution report below uses this framework to evaluate recent performance across the model’s ETF holdings, thematic sleeves, and benchmark-relative return profile. In this sense, attribution is not just a performance review — it is also a real-time signal of where thematic investors are finding leadership, where risk is being repriced, and which macro forces are currently being rewarded in ETF markets.
Overview
The Kaleidoscope Thematic Equity Model Portfolio delivered a strong trailing-month rebound as of May 1, rising +11.33% versus +9.98% for the SPY benchmark, producing +130 bps of active outperformance. The improvement marks a sharp reversal from the April report, when the model had modestly underperformed over the prior month.
Year-to-date, the model is now up +10.35% versus +5.97% for SPY, representing +451 bps of active outperformance. The attribution profile has shifted meaningfully: April’s leadership was heavily commodity-driven, while the May 1 update shows Technology Themes as the dominant short-term attribution engine, especially across AI, semiconductors, blockchain, cloud, and fintech exposure.
Performance Summary
ETF attribution totals may differ slightly from active return due to compounding interaction across ETFs, as noted in the CSV.
| Period | Model | BMK (SPY) | Active | Sum ETF Attribution |
| MTD | +0.67% | +0.28% | +0.40% | +0.40% |
| 1W | +0.31% | +0.94% | -0.60% | -0.59% |
| 1M | +11.33% | +9.98% | +1.30% | +1.35% |
| 3M | +5.32% | +4.43% | +1.19% | +1.40% |
| QTD | +12.60% | +10.81% | +1.69% | +1.74% |
| YTD | +10.35% | +5.97% | +4.51% | +4.73% |
Theme-Level Attribution
| Period | Commodities | Industrial | Technology | Consumer | Sum ETF Attribution |
| MTD | -0.17% | -0.06% | +0.68% | -0.05% | +0.40% |
| 1W | -0.44% | +0.00% | -0.05% | -0.08% | -0.59% |
| 1M | -1.36% | -0.25% | +3.01% | -0.05% | +1.35% |
| QTD | -1.17% | -0.15% | +3.09% | -0.05% | +1.74% |
| YTD | +1.84% | +1.63% | +1.21% | +0.06% | +4.73% |
May Month-to-Date Performance
MTD: +0.67% vs. +0.28% BMK | Active: +0.40%
May opened with positive active performance, led almost entirely by Technology Themes. Cloud, AI, crypto-adjacent, fintech, cybersecurity, and internet exposure collectively offset weakness across commodities and consumer-linked holdings. The first-session attribution profile suggests investors were rewarding higher-beta growth themes at the start of the month, while real assets and housing-related exposure lagged.
MTD ETF Attribution Leaders and Detractors
| Top Contributor | Theme | Attribution | Top Detractor | Theme | Attribution |
| SKYY | Technology | +0.23% | NANR | Commodities | -0.06% |
| AIQ | Technology | +0.15% | ITB | Consumer | -0.05% |
| GBTC | Technology | +0.12% | XBI | Technology | -0.04% |
| ARKF | Technology | +0.09% | GDX | Commodities | -0.04% |
| CIBR | Technology | +0.08% | ARKX | Industrial | -0.03% |
| FDN | Technology | +0.04% | URA | Commodities | -0.03% |
1-Week Performance
1W: +0.31% vs. +0.94% BMK | Active: -0.60%
The model underperformed over the trailing week despite positive absolute performance. The primary drag came from Commodities Themes, especially gold miners and copper exposure, while Consumer and select speculative technology holdings also weighed on relative results. Technology attribution was mixed: AI, cloud, and cybersecurity were constructive, but blockchain, fintech, biotech, and internet themes offset much of the benefit.
1-Week ETF Attribution Leaders and Detractors
| Top Contributor | Theme | Attribution | Top Detractor | Theme | Attribution |
| AIQ | Technology | +0.23% | GDX | Commodities | -0.22% |
| SKYY | Technology | +0.20% | BKCH | Technology | -0.18% |
| DRIV | Consumer | +0.13% | ITB | Consumer | -0.16% |
| CIBR | Technology | +0.07% | ARKF | Technology | -0.14% |
| GRID | Industrial | +0.04% | XBI | Technology | -0.14% |
| TAN | Industrial | +0.02% | COPX | Commodities | -0.14% |
1-Month Performance
1M: +11.33% vs. +9.98% BMK | Active: +1.30%
The trailing-month result is the strongest part of the May update. The model’s +130 bps of active outperformance was driven by a decisive rotation back into higher-beta Technology Themes. Blockchain equities, AI, semiconductors, cloud infrastructure, and fintech were the biggest positive contributors.
Commodities, which had been the model’s key source of defense and alpha earlier in the year, detracted over the trailing month. Natural resources, gold miners, copper producers, and midstream energy exposure all weighed on attribution. This suggests the market’s near-term leadership broadened away from inflation hedges and toward growth-sensitive thematic exposures.
1-Month ETF Attribution Leaders and Detractors
| Top Contributor | Theme | Attribution | Top Detractor | Theme | Attribution |
| BKCH | Technology | +1.13% | NANR | Commodities | -0.52% |
| AIQ | Technology | +0.94% | GDX | Commodities | -0.49% |
| SMH | Technology | +0.94% | XBI | Technology | -0.37% |
| DRIV | Consumer | +0.35% | KWEB | Technology | -0.36% |
| GBTC | Technology | +0.25% | MLPX | Commodities | -0.24% |
| SKYY | Technology | +0.17% | IGF | Industrial | -0.23% |
Quarter-to-Date Performance
QTD: +12.60% vs. +10.81% BMK | Active: +1.69%
Quarter-to-date attribution is similar to the trailing-month profile, with Technology Themes providing almost all of the positive active return. The model’s QTD outperformance is being driven by the same high-beta growth complex: blockchain, semiconductors, AI, fintech, and selective cloud exposure.
The QTD weakness in Commodities and Industrial Themes does not invalidate their role in the model, but it does show that the near-term market has shifted from defensive inflation hedges toward a more risk-on growth narrative.
Year-to-Date Performance
YTD: +10.35% vs. +5.97% BMK | Active: +4.51%
Year-to-date, the model remains ahead of SPY by a substantial margin. Unlike the trailing-month result, the YTD attribution profile is more balanced. Commodities and Industrial Themes remain important contributors, while Technology Themes have moved back into positive territory after prior weakness.
The key message is that the model’s diversified thematic structure has worked across two different market regimes: first through real assets, commodities, and infrastructure leadership, and more recently through the rebound in AI, semiconductors, and blockchain exposure.
YTD ETF Attribution Leaders and Detractors
| Top Contributor | Theme | Attribution | Top Detractor | Theme | Attribution |
| SMH | Technology | +1.66% | KWEB | Technology | -0.95% |
| BKCH | Technology | +1.34% | ARKF | Technology | -0.68% |
| NANR | Commodities | +0.93% | GBTC | Technology | -0.41% |
| AIQ | Technology | +0.67% | CIBR | Technology | -0.37% |
| DRIV | Consumer | +0.62% | SKYY | Technology | -0.36% |
| URA | Commodities | +0.59% | ESPO | Consumer | -0.32% |
Portfolio Positioning
The model remains close to its rebalance targets. Technology remains the dominant sleeve at roughly 60% of the portfolio, while Commodities and Industrial Themes are each near 15%, and Consumer Themes remain near 10%. No sleeve has drifted materially from its target allocation.
| Sleeve | Rebalance Weight | Current Weight | Drift |
| Commodities | 15.00% | 14.90% | -0.10% |
| Industrial | 15.00% | 14.97% | -0.03% |
| Technology | 60.00% | 60.18% | +0.18% |
| Consumer | 10.00% | 9.96% | -0.04% |
Largest ETF Weight Drifts
| ETF | Theme | Rebalance Weight | Current Weight | Drift |
| GBTC | Technology | 5.00% | 4.91% | -0.09% |
| CIBR | Technology | 5.00% | 5.08% | +0.08% |
| SKYY | Technology | 5.00% | 5.07% | +0.07% |
| FDN | Technology | 5.00% | 5.07% | +0.07% |
| TAN | Industrial | 2.00% | 1.95% | -0.05% |
| COPX | Commodities | 3.00% | 2.95% | -0.05% |
| BKCH | Technology | 5.00% | 5.05% | +0.05% |
| GDX | Commodities | 3.00% | 2.96% | -0.04% |
Key Takeaways: What the May Attribution Signals
The May attribution update shows a portfolio benefiting from a renewed risk-on rotation, but with leadership that looks more selective than broad-based. Technology Themes have reasserted themselves as the dominant source of short-term alpha, especially where exposures are tied to AI infrastructure, semiconductors, blockchain, and cloud platforms.
Commodities are no longer the near-term engine of attribution. After driving much of the model’s earlier YTD resilience, natural resources, gold miners, copper, and midstream energy detracted over the trailing month. This suggests the market has temporarily moved away from inflation-protection leadership and toward growth-sensitive exposures.
The model’s YTD profile remains healthy because the sources of alpha are now diversified across regimes. Commodities and Industrial Themes still carry positive YTD attribution, while Technology has recovered enough to become a meaningful contributor again. That mix is constructive: the portfolio is no longer relying on a single macro factor.
The weakest signal remains within the speculative and globally exposed parts of Technology. Chinese internet, fintech, crypto-adjacent exposure on a YTD basis, and parts of biotech continue to show uneven attribution, suggesting investors are still differentiating between profitable AI infrastructure leadership and more rate-sensitive long-duration growth themes.
In aggregate, the May update frames the Kaleidoscope Model as a thematic portfolio that has transitioned from a defensive real-asset-led attribution profile toward a more growth-led rebound. The strongest forward signal is that AI, semiconductors, blockchain, and cloud are again being rewarded, while commodities and defensive real-asset exposures may need a renewed inflation or geopolitical catalyst to regain near-term leadership.
Disclaimer: This report is provided for informational purposes only and does not constitute investment advice, a recommendation, or an offer to buy or sell any security, ETF, strategy, or investment product. The information presented should not be relied upon as the sole basis for any investment decision.
Performance and attribution data are presented for analytical and educational purposes and may be based on model portfolio assumptions, index or ETF return data, and internal calculations. Past performance is not indicative of future results. Actual investor results may differ due to fees, expenses, trading costs, taxes, timing, implementation differences, and other factors.
The attribution analysis included in this report is not GIPS compliant and should not be interpreted as a presentation prepared in accordance with the Global Investment Performance Standards
