Energy sector exchange-traded funds (ETFs) have drawn renewed attention amid evolving commodity dynamics and global supply considerations. First Trust Energy AlphaDEX Fund (FXN) and Vanguard Energy ETF (VDE) both deliver targeted exposure to U.S. energy equities yet pursue distinct strategies. They do not compete directly as identical products; instead, they offer alternative approaches to similar investor objectives of gaining energy sector participation. VDE emphasizes broad, low-cost market representation, while FXN applies a systematic factor model that may enhance or alter risk-return characteristics within the same underlying industry.
First Trust Energy AlphaDEX Fund (FXN) is an actively managed ETF that uses the proprietary AlphaDEX methodology to select and weight energy companies based on quantitative factors such as value, growth, and momentum. The fund focuses exclusively on the energy sector and typically maintains a more concentrated portfolio than broad market-cap benchmarks. It features an expense ratio of 0.63%. As a rules-based strategy, it rebalances periodically according to its factor model rather than strict market-capitalization weights. Key distinguishing features include the potential for factor-driven tilts that may lead to different performance patterns relative to traditional indexes, though it remains fully invested in energy equities listed on major U.S. exchanges.
Vanguard Energy ETF (VDE) is a passive ETF designed to track the performance of the MSCI U.S. Investable Market Energy 25/50 Index. The fund holds a diversified basket of large-, mid-, and small-capitalization U.S. energy companies, with approximately 113 holdings as of recent data. Top positions typically include Exxon Mobil Corp (XOM), Chevron Corp (CVX), and other major integrated and exploration firms. VDE maintains a low expense ratio of 0.09% and employs market-capitalization weighting with periodic rebalancing to match the index. Its structure provides comprehensive sector coverage across oil, gas, consumable fuels, and energy equipment and services, emphasizing broad representation rather than factor selection.
The U.S. energy sector encompasses upstream exploration and production, midstream infrastructure, downstream refining, and equipment providers. Macroeconomic drivers include global oil demand trends, geopolitical supply disruptions, domestic production levels, and the pace of energy transition policies. Capital flows into the sector often respond to commodity price cycles and earnings momentum among major producers. Regulatory developments around permitting, emissions standards, and infrastructure can influence investment activity, while interest rate environments affect financing costs for capital-intensive projects. Sector risks encompass commodity price volatility, regulatory shifts, and competition from alternative energy sources, creating an environment where both broad and factor-based ETFs can serve complementary roles depending on investor objectives.
In recent market cycles, energy ETFs have exhibited sensitivity to commodity price movements and earnings seasons of leading producers. VDE’s market-cap structure tends to deliver returns closely aligned with the overall sector, with relatively lower turnover and consistent exposure across cycles. FXN’s factor-based approach may result in differentiated performance during periods when value or momentum characteristics dominate within energy names, potentially leading to higher volatility or periods of outperformance relative to the broader index. Over recent weeks and months, positioning differences have manifested in how each fund captures sector rotation tied to macroeconomic signals such as inventory data or global demand forecasts. VDE generally offers smoother tracking of the energy benchmark, whereas FXN introduces an additional layer of systematic selection that can alter relative positioning in varying market regimes.
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. Visit the AI Screener to explore current opportunities in the energy sector and beyond.
Based on observable structural characteristics, Tickeron’s AI would currently assign a higher probability of preference to Vanguard Energy ETF (VDE). The fund’s substantially lower expense ratio, broader diversification across more than 100 holdings, and straightforward market-cap methodology provide advantages in cost efficiency and risk mitigation for most investors seeking energy exposure. While First Trust Energy AlphaDEX Fund (FXN) offers a differentiated factor-driven approach that could appeal in specific market conditions, VDE’s profile aligns more consistently with durable, long-term positioning within the sector.
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| FXN | VDE | FXN / VDE | |
| Gain YTD | 35.156 | 34.290 | 103% |
| Net Assets | 379M | 11.1B | 3% |
| Total Expense Ratio | 0.63 | 0.09 | 700% |
| Turnover | 50.00 | 11.00 | 455% |
| Yield | 1.62 | 2.40 | 68% |
| Fund Existence | 19 years | 22 years | - |
| FXN | VDE | |
|---|---|---|
| RSI ODDS (%) | 4 days ago 80% | 4 days ago 81% |
| Stochastic ODDS (%) | 4 days ago 87% | 4 days ago 82% |
| Momentum ODDS (%) | 4 days ago 90% | 4 days ago 90% |
| MACD ODDS (%) | 4 days ago 85% | 4 days ago 88% |
| TrendWeek ODDS (%) | 4 days ago 89% | 4 days ago 81% |
| TrendMonth ODDS (%) | 4 days ago 87% | 4 days ago 89% |
| Advances ODDS (%) | 4 days ago 90% | 4 days ago 90% |
| Declines ODDS (%) | 7 days ago 81% | 7 days ago 82% |
| BollingerBands ODDS (%) | 4 days ago 75% | 4 days ago 76% |
| Aroon ODDS (%) | 4 days ago 90% | 4 days ago 89% |
| 1 Day | |||
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A.I.dvisor indicates that over the last year, FXN has been closely correlated with OVV. These tickers have moved in lockstep 90% of the time. This A.I.-generated data suggests there is a high statistical probability that if FXN jumps, then OVV could also see price increases.
A.I.dvisor indicates that over the last year, VDE has been closely correlated with XOM. These tickers have moved in lockstep 90% of the time. This A.I.-generated data suggests there is a high statistical probability that if VDE jumps, then XOM could also see price increases.