Investors seeking large-cap growth exposure often compare SCHG and VONG due to their overlapping mandates and strong historical alignment with technology-driven market leadership. These ETFs do not compete directly with one another but serve as close alternatives within the same growth equity segment, allowing investors to evaluate trade-offs in cost, concentration, and index methodology. In the current environment of rapid innovation in artificial intelligence and semiconductors, both funds provide targeted access to high-growth companies, making them relevant for portfolios emphasizing long-term capital appreciation over broad market beta.
The Schwab U.S. Large-Cap Growth ETF (SCHG) is a passively managed fund that seeks to track the performance of the Dow Jones U.S. Large-Cap Growth Total Stock Market Index. This index selects growth-oriented stocks from approximately the largest 750 U.S. companies by market capitalization. As of recent data, the ETF holds 196 securities with an expense ratio of 0.04%. Top holdings typically include major technology names such as NVIDIA, Microsoft, and Apple, resulting in significant technology sector weighting alongside healthcare and consumer discretionary. The fund employs a market-capitalization-weighted approach with periodic rebalancing to maintain index alignment. Its structure emphasizes cost efficiency and liquidity, distinguishing it through one of the lowest expense ratios in the large-cap growth category.
The Vanguard Russell 1000 Growth ETF (VONG) is a passively managed fund designed to track the Russell 1000 Growth Index, which measures the performance of large- and mid-cap U.S. growth stocks. The ETF currently holds approximately 396 securities and carries an expense ratio of 0.06%. Its holdings feature substantial overlap with SCHG in mega-cap growth leaders, including heavy positions in NVIDIA, Apple, and Microsoft. Sector allocations mirror those of peers with dominant exposure to technology, followed by healthcare and industrials. VONG uses a rules-based, market-cap-weighted methodology with quarterly rebalancing. The fund’s broader holdings count provides slightly greater diversification within the growth segment while maintaining competitive costs and high trading liquidity.
The large-cap growth segment remains heavily influenced by advancements in artificial intelligence, cloud computing, and semiconductor technology. Macroeconomic factors such as interest rate expectations and corporate earnings growth in the technology sector continue to shape capital flows into growth-oriented strategies. Regulatory developments around data privacy and antitrust scrutiny of dominant tech platforms introduce measured risks, while sustained innovation cycles support ongoing sector momentum. Both ETFs benefit from these thematic tailwinds but face potential headwinds from valuation compression or shifts in investor sentiment toward value or defensive sectors during economic uncertainty.
In recent market cycles, both ETFs have demonstrated strong sensitivity to technology earnings reports and broader growth sentiment. SCHG’s more concentrated structure has at times amplified returns during periods of mega-cap outperformance, while VONG’s wider holdings have provided modest buffering during rotations away from the largest names. Relative positioning shows both funds benefiting from favorable interest rate environments that support growth valuations, though differences in index construction lead to subtle variations in volatility profiles. Over broader timeframes, performance divergence remains modest and primarily attributable to sector weighting nuances rather than fundamental strategy differences.
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Based on observable factors including structural strength, lower expense ratio, and competitive diversification profile, Tickeron’s AI would currently assign a modest probabilistic preference to SCHG for cost-conscious investors seeking efficient large-cap growth exposure. Its tighter expense structure and concentrated holdings may align well with sustained technology sector momentum, though VONG remains a strong alternative for those prioritizing broader index coverage. This assessment reflects relative positioning rather than a definitive recommendation.
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| SCHG | VONG | SCHG / VONG | |
| Gain YTD | 9.935 | 3.803 | 261% |
| Net Assets | 63.2B | 51.6B | 122% |
| Total Expense Ratio | 0.04 | 0.06 | 67% |
| Turnover | 27.00 | 10.00 | 270% |
| Yield | 0.39 | 0.48 | 81% |
| Fund Existence | 17 years | 16 years | - |
| SCHG | VONG | |
|---|---|---|
| RSI ODDS (%) | 4 days ago 78% | 4 days ago 90% |
| Stochastic ODDS (%) | 4 days ago 84% | 4 days ago 81% |
| Momentum ODDS (%) | 4 days ago 79% | 4 days ago 84% |
| MACD ODDS (%) | 4 days ago 84% | 4 days ago 83% |
| TrendWeek ODDS (%) | 4 days ago 85% | 4 days ago 85% |
| TrendMonth ODDS (%) | 4 days ago 87% | 4 days ago 87% |
| Advances ODDS (%) | 28 days ago 84% | 19 days ago 83% |
| Declines ODDS (%) | 14 days ago 79% | 12 days ago 82% |
| BollingerBands ODDS (%) | 4 days ago 81% | 4 days ago 86% |
| Aroon ODDS (%) | 4 days ago 90% | 4 days ago 81% |
| 1 Day | |||
|---|---|---|---|
| ETFs / NAME | Price $ | Chg $ | Chg % |
| MAYU | 34.86 | N/A | N/A |
| AllianzIM US Equity Buffer15 Unc May ETF | |||
| TTXU | 34.26 | -0.22 | -0.65% |
| Direxion Daily TecTop 5 Bull 2X ETF | |||
| DFIS | 37.62 | -0.25 | -0.66% |
| Dimensional International Small Cap ETF | |||
| USSG | 72.31 | -0.51 | -0.71% |
| Xtrackers MSCI USA Selection Eq ETF | |||
| GLRY | 38.94 | -0.75 | -1.89% |
| Inspire Growth ETF | |||
A.I.dvisor indicates that over the last year, VONG has been closely correlated with NVDA. These tickers have moved in lockstep 74% of the time. This A.I.-generated data suggests there is a high statistical probability that if VONG jumps, then NVDA could also see price increases.
| Ticker / NAME | Correlation To VONG | 1D Price Change % | ||
|---|---|---|---|---|
| VONG | 100% | -0.97% | ||
| NVDA - VONG | 74% Closely correlated | -4.57% | ||
| LRCX - VONG | 65% Loosely correlated | -5.24% | ||
| AVGO - VONG | 64% Loosely correlated | -0.74% | ||
| TSLA - VONG | 64% Loosely correlated | -1.71% | ||
| SOFI - VONG | 63% Loosely correlated | -5.84% | ||
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