Comparing SCHG and VONG is timely amid sustained investor interest in large-cap growth strategies. Both ETFs target U.S. large-cap growth equities, competing directly for allocations seeking capital appreciation from technology leaders and innovative sectors. While they overlap significantly in holdings and sector exposure, subtle differences in index methodology, diversification, and costs offer alternatives for optimizing growth portfolios. In the current environment of AI-driven capital flows and moderating interest rates, these funds highlight structural nuances in pursuing similar investor goals of long-term outperformance versus broader benchmarks.
The Schwab U.S. Large-Cap Growth ETF (SCHG) is a passive ETF that seeks to track the Dow Jones U.S. Large-Cap Growth Total Stock Market Index, comprising the largest 750 U.S. companies classified as growth based on factors like projected earnings growth. It holds approximately 198 stocks, providing focused exposure to large-cap growth. Top holdings include NVDA (11%), AAPL (10%), MSFT (8%), AMZN (5%), and Alphabet classes around 4% each. Sector allocations emphasize technology (44%), communication services (16%), and consumer discretionary (13%), with health care at 9%. The expense ratio is a low 0.04%, and portfolio turnover stands at 15%. As a structurally efficient, non-leveraged fund listed on NYSE Arca, SCHG offers high liquidity with a 0.03% median bid-ask spread.
The Vanguard Russell 1000 Growth ETF (VONG) passively tracks the Russell 1000 Growth Index, measuring large-capitalization U.S. growth stocks from the Russell 1000 universe. It maintains around 391 holdings for broader diversification. Top holdings feature NVDA (12.7%), AAPL (10.8%), MSFT (9.2%), AMZN (4.8%), and AVGO (4.6%). Sector weights are led by technology (60%), consumer discretionary (18%), industrials (9%), and health care (8%). With an expense ratio of 0.06% and low turnover of 10%, VONG employs full replication on Nasdaq, ensuring tight tracking. Its structure supports excellent liquidity, evidenced by a 0.01% median bid-ask spread.
The large-cap growth sector, dominated by technology and AI innovators, faces a dynamic environment in 2026. Massive capital expenditures by hyperscalers—projected over $500 billion—fuel AI infrastructure, data centers, and semiconductors, driving productivity gains and earnings growth. Capital flows concentrate in mega-cap names like NVDA and MSFT, supported by moderating inflation and potential interest rate stabilization. Sector catalysts include AI adoption broadening beyond chatbots to complex applications, alongside policy incentives for business investment. Risks encompass elevated valuations, capex monetization challenges, and geopolitical tensions affecting supply chains. Macro shifts, such as steady U.S. GDP growth and fiscal stimulus, bolster the backdrop for growth-oriented exposures.
In recent weeks and months, SCHG and VONG have exhibited closely aligned performance, reflecting shared exposure to large-cap growth drivers. Year-to-date through early 2026, both declined around 5%, with VONG slightly outperforming at -4.4% versus SCHG's -5.3%, amid tech sector volatility from AI capex concerns. Over longer cycles, they delivered similar returns, such as 18-20% over the prior year, tied to earnings strength in top holdings and sector rotation toward AI beneficiaries. Volatility profiles are comparable, with betas near 1.18-1.19 and max drawdowns in the mid-30% range over five years. SCHG's relative positioning benefits from lower costs in prolonged uptrends, while VONG's broader holdings may offer marginally better resilience during rotations away from mega-caps, influenced by interest rate expectations and commodity trends impacting tech infrastructure.
Tickeron’s Trending AI Robots page showcases the platform's strongest AI-powered trading bots under prevailing market conditions. Tickeron provides hundreds of AI bots scanning thousands of tickers across various timeframes, strategies, and performance metrics like win rates and profit factors. The curated trending section highlights top performers adapting to volatility in sectors like technology and growth equities. These bots employ pattern recognition, trend following, and mean reversion tactics, offering investors data-driven signals without emotional bias. Explore the page to identify bots aligned with large-cap growth trends or broader market rotations, and consider integrating them for enhanced decision-making in dynamic environments.
Tickeron’s AI currently favors SCHG due to its superior cost efficiency (0.04% expense ratio), strong trend consistency in large-cap growth cycles, and balanced sector momentum. While VONG offers greater diversification, SCHG's lower fees and focused exposure to high-conviction growth names position it probabilistically better for capturing AI-driven upside amid stable macro conditions, assuming continued tech leadership.
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| SCHG | VONG | SCHG / VONG | |
| Gain YTD | -6.537 | -5.729 | 114% |
| Net Assets | 50.6B | 44.9B | 113% |
| Total Expense Ratio | 0.04 | 0.06 | 67% |
| Turnover | 27.00 | 10.00 | 270% |
| Yield | 0.43 | 0.51 | 85% |
| Fund Existence | 16 years | 16 years | - |
| SCHG | VONG | |
|---|---|---|
| RSI ODDS (%) | 1 day ago 88% | 1 day ago 81% |
| Stochastic ODDS (%) | 1 day ago 76% | 1 day ago 75% |
| Momentum ODDS (%) | 1 day ago 84% | 1 day ago 83% |
| MACD ODDS (%) | 1 day ago 82% | 1 day ago 74% |
| TrendWeek ODDS (%) | 1 day ago 85% | 1 day ago 85% |
| TrendMonth ODDS (%) | 1 day ago 85% | 1 day ago 85% |
| Advances ODDS (%) | 1 day ago 84% | 1 day ago 84% |
| Declines ODDS (%) | 11 days ago 79% | 11 days ago 81% |
| BollingerBands ODDS (%) | 1 day ago 88% | 1 day ago 85% |
| Aroon ODDS (%) | 1 day ago 87% | 1 day ago 86% |
| 1 Day | |||
|---|---|---|---|
| ETFs / NAME | Price $ | Chg $ | Chg % |
| IBRN | 34.10 | 0.31 | +0.92% |
| iShares Neuroscience and Healthcare ETF | |||
| PQJA | 29.28 | 0.15 | +0.51% |
| PGIM NASDAQ-100 BUFFER 12 ETF - JANUARY | |||
| ESGG | 209.72 | 0.70 | +0.33% |
| FlexShares STOXX Glbl ESG Select ETF | |||
| EAGG | 47.65 | 0.03 | +0.06% |
| iShares ESG U.S. Aggregate Bond ETF | |||
| IBD | 23.93 | N/A | +0.02% |
| Inspire Corporate Bond ETF | |||
A.I.dvisor indicates that over the last year, SCHG has been closely correlated with NVDA. These tickers have moved in lockstep 83% of the time. This A.I.-generated data suggests there is a high statistical probability that if SCHG jumps, then NVDA could also see price increases.
| Ticker / NAME | Correlation To SCHG | 1D Price Change % | ||
|---|---|---|---|---|
| SCHG | 100% | +0.33% | ||
| NVDA - SCHG | 83% Closely correlated | +1.01% | ||
| AMZN - SCHG | 75% Closely correlated | +5.60% | ||
| IBKR - SCHG | 74% Closely correlated | -0.57% | ||
| AVGO - SCHG | 73% Closely correlated | +1.22% | ||
| AAPL - SCHG | 73% Closely correlated | +0.61% | ||
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A.I.dvisor indicates that over the last year, VONG has been closely correlated with NVDA. These tickers have moved in lockstep 84% 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% | +0.53% | ||
| NVDA - VONG | 84% Closely correlated | +1.01% | ||
| MS - VONG | 76% Closely correlated | +1.22% | ||
| GS - VONG | 75% Closely correlated | -0.22% | ||
| AVGO - VONG | 75% Closely correlated | +1.22% | ||
| AMZN - VONG | 74% Closely correlated | +5.60% | ||
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