Investors seeking clean energy exposure often compare thematic ETFs like PBW and QCLN to align portfolios with the transition to sustainable power sources. These funds do not compete directly but offer alternative strategies within the same broad sector, allowing investors to select based on preferences for diversification versus concentration. PBW and QCLN both track specialized indices focused on companies advancing renewable technologies, energy efficiency, and related innovations, making them relevant for those evaluating long-term thematic positioning amid evolving energy policies and technological advancements.
The Invesco WilderHill Clean Energy ETF (PBW) seeks to track the performance of the WilderHill Clean Energy Index. The fund employs a passive strategy with a modified equal-weight methodology across its holdings. As of recent data, PBW contains approximately 69 holdings. Sector allocations typically include industrials at about 44%, information technology near 22%, materials around 17%, and smaller weights in consumer discretionary, energy, and utilities. The expense ratio is 0.64%. The index is rebalanced and reconstituted quarterly. Distinguishing features include its focus on U.S.-listed companies involved in clean energy innovation, energy efficiency, and related technologies, providing diversified exposure without heavy concentration in any single holding.
The First Trust NASDAQ Clean Edge Green Energy Index Fund (QCLN) aims to replicate the NASDAQ Clean Edge Green Energy Index. This passive ETF uses a market-capitalization-weighted approach. Recent holdings total around 53 securities. Sector breakdowns generally feature technology at approximately 48%, industrials near 25%, consumer cyclical around 10%, and additional allocations to utilities and basic materials. The expense ratio stands at 0.59%. The fund rebalances periodically in line with its underlying index. Key characteristics encompass exposure to manufacturers, developers, and installers in renewable electricity generation, energy storage, advanced materials, and energy intelligence, resulting in a more concentrated profile tilted toward semiconductor and clean technology leaders.
The clean energy sector continues to evolve amid policy support for renewables, advancements in battery storage and solar technologies, and shifting capital flows toward sustainable infrastructure. Macroeconomic drivers include interest rate environments affecting project financing, commodity price fluctuations impacting material costs, and regulatory developments around emissions standards. Sector risks encompass supply chain constraints, technological obsolescence, and competition from traditional energy sources. Both PBW and QCLN benefit from broader trends in decarbonization while facing volatility tied to earnings cycles in key sub-sectors such as solar equipment and electric vehicles.
In recent market cycles, PBW’s broader industrial and materials tilt has contributed to differentiated performance relative to QCLN’s technology-heavy positioning. QCLN’s concentration in semiconductors and related components has aligned it more closely with electronics and electric vehicle demand trends, potentially amplifying gains during favorable periods but increasing sensitivity to sector-specific rotations. PBW’s equal-weight methodology supports more balanced exposure across holdings, which may moderate volatility compared to QCLN’s market-cap approach. Relative positioning reflects how each fund captures distinct aspects of clean energy growth, with PBW offering wider diversification and QCLN emphasizing high-growth technology sub-themes.
Tickeron’s AI Screener is an AI-powered stock and ETF discovery tool that helps traders and investors filter the market based on technical patterns, fundamentals, trends, volatility, and AI-driven signals. Users can scan thousands of stocks and ETFs using customizable filters such as industry, market capitalization, technical indicators, price patterns, and performance metrics. The screener helps identify trade ideas, trending stocks, breakout candidates, and market opportunities more efficiently than manual screening. Explore opportunities with the AI Screener.
Based on observable structural factors, Tickeron’s AI would likely favor QCLN at present due to its lower expense ratio, more concentrated exposure to high-momentum technology sub-sectors, and alignment with prevailing semiconductor and clean energy equipment trends. PBW offers advantages in diversification and industrial balance that may appeal under different market conditions. This assessment draws from cost efficiency, sector momentum, and risk exposure profiles without constituting investment advice.
The information on this webpage is provided for general informational and educational purposes only and is not intended as investment advice, a recommendation to purchase or sell any security, or an offer or solicitation related to investments. It does not consider your personal financial situation, goals, or risk profile, and all investing carries inherent risks, including the possibility of losing your entire investment. For more details, please review our full disclaimer.
| PBW | QCLN | PBW / QCLN | |
| Gain YTD | 35.890 | 37.195 | 96% |
| Net Assets | 560M | 895M | 63% |
| Total Expense Ratio | 0.64 | 0.59 | 108% |
| Turnover | 62.00 | 23.00 | 270% |
| Yield | 0.60 | 0.15 | 395% |
| Fund Existence | 21 years | 19 years | - |
| PBW | QCLN | |
|---|---|---|
| RSI ODDS (%) | 2 days ago 86% | 2 days ago 90% |
| Stochastic ODDS (%) | 2 days ago 84% | 2 days ago 89% |
| Momentum ODDS (%) | 2 days ago 90% | 2 days ago 90% |
| MACD ODDS (%) | 2 days ago 87% | 2 days ago 85% |
| TrendWeek ODDS (%) | 2 days ago 88% | 2 days ago 89% |
| TrendMonth ODDS (%) | 2 days ago 89% | 2 days ago 90% |
| Advances ODDS (%) | 9 days ago 90% | 2 days ago 90% |
| Declines ODDS (%) | 7 days ago 90% | 7 days ago 90% |
| BollingerBands ODDS (%) | 2 days ago 90% | 2 days ago 90% |
| Aroon ODDS (%) | 2 days ago 90% | 2 days ago 90% |
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% | -0.19% | ||
| ENVX - PBW | 68% Closely correlated | -0.42% | ||
| ACHR - PBW | 67% Closely correlated | -2.51% | ||
| QS - PBW | 66% Closely correlated | -5.35% | ||
| BLDP - PBW | 66% Loosely correlated | -1.14% | ||
| SLDP - PBW | 65% Loosely correlated | -2.44% | ||
More | ||||