Investors seeking targeted exposure to cyclical or growth-oriented themes often compare specialized ETFs such as the U.S. Global Jets ETF (JETS) and the Invesco WilderHill Clean Energy ETF (PBW). These funds do not compete directly; instead, they represent distinct strategies—one centered on aviation recovery and operations, the other on clean energy transition and technological innovation. The comparison helps clarify how differing index methodologies, concentration levels, and sector tilts influence risk profiles and positioning amid evolving macroeconomic conditions, energy markets, and policy environments.
The U.S. Global Jets ETF (JETS) is a passively managed, thematic ETF that seeks to track the U.S. Global Jets Index. The index comprises companies engaged in the global airline industry, including passenger and cargo carriers, aircraft manufacturers, and airport operators. The fund typically holds 50-57 securities, with the top 10 holdings accounting for roughly 68% of assets. Leading positions include Delta Air Lines Inc. (DAL), American Airlines Group Inc. (AAL), United Airlines Holdings Inc. (UAL), Southwest Airlines Co. (LUV), and several smaller carriers. Sector exposure is heavily skewed toward transportation (approximately 80%) and electronic technology. The expense ratio is 0.60%. The ETF is non-diversified and rebalanced periodically according to index rules, emphasizing liquidity and market-capitalization weighting within its narrow universe.
The Invesco WilderHill Clean Energy ETF (PBW) is a passively managed, thematic ETF designed to track the WilderHill Clean Energy Index. The index focuses on companies involved in renewable energy generation, energy efficiency, energy storage, and related clean technologies. The fund holds approximately 69-71 securities, with the top 10 positions representing about 25% of assets, promoting broader diversification within the theme. Representative holdings include firms such as Hyliion Holdings Corp. (HYLN) and FuelCell Energy Inc. (FCEL). Sector allocations emphasize industrials (32-45%), information technology (22-27%), and materials. The expense ratio is 0.64%. The index undergoes quarterly rebalancing and reconstitution to maintain alignment with evolving clean energy criteria.
Both ETFs operate in sectors influenced by macroeconomic variables, regulatory developments, and technological shifts. The airline industry underlying JETS responds to fuel price fluctuations, global travel demand, supply-chain dynamics, and geopolitical events affecting aviation. The clean energy space supporting PBW is shaped by government incentives for renewables, advancements in battery and hydrogen technologies, corporate sustainability commitments, and transitions away from fossil fuels. Capital flows into both themes have varied with interest-rate expectations, commodity trends, and policy priorities, creating distinct risk exposures for each fund.
In recent market cycles, JETS has demonstrated sensitivity to airline earnings trends, fuel-cost volatility, and post-pandemic travel recovery patterns, often exhibiting pronounced swings during economic expansions or contractions. PBW has shown responsiveness to clean-energy policy announcements, technology breakthroughs, and shifts in investor sentiment toward sustainability, with performance influenced by broader growth-stock rotations. Relative volatility remains elevated for both compared with broad equity benchmarks, though PBW’s wider holdings base may moderate concentration-driven moves relative to JETS. Sector momentum and interest-rate environments continue to drive differential positioning between the two thematic exposures.
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Based on observable structural factors including lower expense ratio, established index methodology, and concentrated yet liquid exposure to a recovering cyclical sector, Tickeron’s AI would currently assign a modestly higher probabilistic preference to the U.S. Global Jets ETF (JETS) for investors seeking aviation-themed allocation, while acknowledging PBW’s appeal for those prioritizing clean-energy diversification and policy-driven growth.
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Disclaimers and Limitations| JETS | PBW | JETS / PBW | |
| Gain YTD | 11.079 | 28.308 | 39% |
| Net Assets | 891M | 560M | 159% |
| Total Expense Ratio | 0.60 | 0.64 | 94% |
| Turnover | 38.00 | 62.00 | 61% |
| Yield | 0.79 | 0.60 | 132% |
| Fund Existence | 11 years | 21 years | - |
| JETS | PBW | |
|---|---|---|
| RSI ODDS (%) | 1 day ago 83% | 1 day ago 86% |
| Stochastic ODDS (%) | 1 day ago 79% | 1 day ago 90% |
| Momentum ODDS (%) | 1 day ago 87% | 1 day ago 90% |
| MACD ODDS (%) | 1 day ago 90% | 1 day ago 85% |
| TrendWeek ODDS (%) | 1 day ago 89% | 1 day ago 90% |
| TrendMonth ODDS (%) | 1 day ago 90% | 1 day ago 90% |
| Advances ODDS (%) | 8 days ago 87% | 9 days ago 90% |
| Declines ODDS (%) | 16 days ago 90% | 1 day ago 90% |
| BollingerBands ODDS (%) | 1 day ago 90% | 1 day ago 89% |
| Aroon ODDS (%) | 1 day ago 90% | 1 day ago 90% |
A.I.dvisor indicates that over the last year, JETS has been closely correlated with DAL. These tickers have moved in lockstep 90% of the time. This A.I.-generated data suggests there is a high statistical probability that if JETS jumps, then DAL could also see price increases.
| Ticker / NAME | Correlation To JETS | 1D Price Change % | ||
|---|---|---|---|---|
| JETS | 100% | +0.65% | ||
| DAL - JETS | 90% Closely correlated | +0.93% | ||
| AAL - JETS | 89% Closely correlated | +0.37% | ||
| UAL - JETS | 89% Closely correlated | +2.42% | ||
| ALGT - JETS | 85% Closely correlated | +1.27% | ||
| LUV - JETS | 83% Closely correlated | +1.73% | ||
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A.I.dvisor indicates that over the last year, PBW has been closely correlated with ENVX. These tickers have moved in lockstep 68% of the time. This A.I.-generated data suggests there is a high statistical probability that if PBW jumps, then ENVX could also see price increases.
| Ticker / NAME | Correlation To PBW | 1D Price Change % | ||
|---|---|---|---|---|
| PBW | 100% | -5.58% | ||
| ENVX - PBW | 68% Closely correlated | -10.35% | ||
| ACHR - PBW | 67% Closely correlated | -3.31% | ||
| QS - PBW | 66% Closely correlated | -2.50% | ||
| BLDP - PBW | 66% Loosely correlated | -3.47% | ||
| SLDP - PBW | 65% Loosely correlated | -2.50% | ||
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