Investors seeking amplified exposure to U.S. equity themes often evaluate leveraged exchange-traded funds (ETFs) for tactical positioning. HIBL, QLD, and SOXL each apply daily leverage to established indexes but differ in scope, multiplier, and sector focus. HIBL and SOXL employ 3x leverage while QLD uses 2x, and their underlying indexes range from high-beta S&P 500 constituents to Nasdaq-100 technology leaders and semiconductor specialists. This comparison highlights structural distinctions that affect diversification, cost, and sensitivity to market cycles.
HIBL seeks daily investment results, before fees and expenses, of 300% of the S&P 500 High Beta Index. The index selects the 100 S&P 500 stocks with the highest beta over the prior 12 months. The ETF typically holds around 100 positions through swaps and other derivatives, with top holdings concentrated in volatile large-cap names across technology and other growth sectors. Its expense ratio stands at approximately 0.98%. As a passive, leveraged product from Direxion, HIBL rebalances daily and suits short-term tactical strategies rather than buy-and-hold approaches.
QLD aims for daily results equal to 200% of the Nasdaq-100 Index before fees and expenses. The Nasdaq-100 comprises 100 large non-financial companies listed on Nasdaq, heavily weighted toward technology. The fund achieves leverage primarily through total return swaps and maintains roughly 100 effective exposures. Its net expense ratio is 0.95%. Issued by ProShares since 2006, QLD offers leveraged broad-tech exposure with daily rebalancing, positioning it as a tactical tool for investors monitoring Nasdaq-100 movements.
SOXL targets 300% of the daily performance of the NYSE Semiconductor Index, which tracks approximately 30 U.S.-listed semiconductor companies. The ETF uses swaps and futures for leverage and holds a concentrated portfolio focused on chip manufacturers and related firms. Its expense ratio is 0.75%. From Direxion since 2010, SOXL applies daily rebalancing to a narrow thematic index, emphasizing semiconductor industry dynamics over broader market participation.
Leveraged equity ETFs operate within the technology and semiconductor sectors, which benefit from ongoing innovation in artificial intelligence, data centers, and advanced computing. Capital flows into these areas reflect sustained corporate and consumer demand for semiconductors and high-growth technology platforms. Macroeconomic factors such as interest rate policies, supply chain resilience, and global trade dynamics influence earnings trends among major holdings. Regulatory developments around technology competition and export controls add sector-specific risks, while broader equity market volatility amplifies the effects of daily leverage across these products.
In recent market cycles, the 3x structure of HIBL and SOXL has produced greater sensitivity to underlying index moves compared with QLD’s 2x multiplier, leading to more pronounced drawdowns during downturns and amplified gains in uptrends. HIBL’s high-beta selection introduces additional volatility relative to the broader Nasdaq-100 tracked by QLD. SOXL’s semiconductor concentration heightens exposure to industry-specific cycles, such as chip demand fluctuations. Daily rebalancing in all three funds creates compounding differences over multi-day periods, favoring shorter holding horizons and explaining relative performance divergence based on leverage level and index breadth.
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. Investors seeking data-driven insights into leveraged products like HIBL, QLD, and SOXL may find the platform useful for refining screening criteria.
Based on observable structural characteristics, Tickeron’s AI would currently assign a higher probability of favorable positioning to QLD. Its 2x leverage offers a balance between amplification and reduced volatility relative to 3x products, while the Nasdaq-100’s breadth provides better diversification than SOXL’s semiconductor concentration and HIBL’s high-beta selection. Lower relative drawdown potential and established liquidity further support this probabilistic assessment for tactical applications.
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| HIBL | QLD | SOXL | |
|---|---|---|---|
| RSI ODDS (%) | N/A | 2 days ago 88% | 2 days ago 90% |
| Stochastic ODDS (%) | 2 days ago 90% | 2 days ago 90% | 2 days ago 90% |
| Momentum ODDS (%) | 2 days ago 90% | 2 days ago 90% | 2 days ago 89% |
| MACD ODDS (%) | 2 days ago 90% | 2 days ago 90% | 2 days ago 90% |
| TrendWeek ODDS (%) | 2 days ago 90% | 2 days ago 89% | 2 days ago 90% |
| TrendMonth ODDS (%) | 2 days ago 90% | 2 days ago 90% | 2 days ago 90% |
| Advances ODDS (%) | 8 days ago 90% | 8 days ago 89% | 9 days ago 90% |
| Declines ODDS (%) | 6 days ago 88% | 6 days ago 86% | 2 days ago 90% |
| BollingerBands ODDS (%) | N/A | 2 days ago 90% | 2 days ago 90% |
| Aroon ODDS (%) | 2 days ago 87% | 2 days ago 89% | 2 days ago 90% |
A.I.dvisor indicates that over the last year, HIBL has been closely correlated with ETN. These tickers have moved in lockstep 74% of the time. This A.I.-generated data suggests there is a high statistical probability that if HIBL jumps, then ETN could also see price increases.
| Ticker / NAME | Correlation To HIBL | 1D Price Change % | ||
|---|---|---|---|---|
| HIBL | 100% | -5.77% | ||
| ETN - HIBL | 74% Closely correlated | -0.69% | ||
| BLK - HIBL | 73% Closely correlated | +0.14% | ||
| CAT - HIBL | 70% Closely correlated | -0.14% | ||
| FBIN - HIBL | 70% Closely correlated | -1.10% | ||
| KEYS - HIBL | 68% Closely correlated | -1.32% | ||
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A.I.dvisor indicates that over the last year, QLD has been loosely correlated with SWKS. These tickers have moved in lockstep 61% of the time. This A.I.-generated data suggests there is some statistical probability that if QLD jumps, then SWKS could also see price increases.
| Ticker / NAME | Correlation To QLD | 1D Price Change % | ||
|---|---|---|---|---|
| QLD | 100% | -1.36% | ||
| SWKS - QLD | 61% Loosely correlated | -2.16% | ||
| ZM - QLD | 56% Loosely correlated | +0.20% | ||
| CEG - QLD | 54% Loosely correlated | -1.40% | ||
| DOCU - QLD | 41% Loosely correlated | -0.15% | ||
| ALGN - QLD | 39% Loosely correlated | -1.60% | ||
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A.I.dvisor indicates that over the last year, SOXL has been closely correlated with ENTG. These tickers have moved in lockstep 83% of the time. This A.I.-generated data suggests there is a high statistical probability that if SOXL jumps, then ENTG could also see price increases.
| Ticker / NAME | Correlation To SOXL | 1D Price Change % | ||
|---|---|---|---|---|
| SOXL | 100% | -8.13% | ||
| ENTG - SOXL | 83% Closely correlated | -3.49% | ||
| MKSI - SOXL | 82% Closely correlated | -5.52% | ||
| ONTO - SOXL | 82% Closely correlated | -7.06% | ||
| ASX - SOXL | 82% Closely correlated | +2.37% | ||
| TSM - SOXL | 81% Closely correlated | -1.98% | ||
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