Investors evaluating large-cap U.S. equity strategies often compare factor-based ETFs to align portfolios with specific market characteristics. The iShares S&P 500 Growth ETF (IVW) and Invesco S&P 500 Momentum ETF (SPMO) both draw from the S&P 500 but apply different selection methodologies—one centered on growth fundamentals and the other on price momentum. They do not compete directly but instead offer alternative approaches to capturing performance drivers within the same broad market segment, helping investors fine-tune exposure to prevailing economic and market conditions.
The iShares S&P 500 Growth ETF (IVW) seeks to track the S&P 500 Growth Index, which selects large-cap U.S. stocks exhibiting above-average earnings and revenue growth. The fund is passively managed and typically holds between 140 and 220 securities. Top holdings commonly include major technology and growth companies such as NVIDIA Corp, Microsoft Corp, and Apple Inc. Sector exposure is heavily weighted toward Information Technology (around 51%), followed by Communication Services (approximately 17%) and Consumer Discretionary (about 9%). IVW maintains an expense ratio of 0.18% and rebalances in line with its underlying index methodology, providing transparent, rules-based access to growth-oriented large-cap equities.
The Invesco S&P 500 Momentum ETF (SPMO) tracks the S&P 500 Momentum Index, which identifies stocks with the highest momentum scores based on recent price performance. Passively managed, the ETF holds 100 securities. Holdings are concentrated, with top positions frequently featuring names like NVIDIA Corp, Broadcom Inc., and Meta Platforms Inc. Sector breakdown typically features Information Technology near 49%, Industrials around 14%, and Communication Services near 10%. SPMO carries a competitive expense ratio of 0.13% and follows a semi-annual rebalancing schedule aligned with its index, delivering systematic exposure to the momentum factor within large-cap U.S. equities.
Both ETFs operate within the large-cap U.S. equity market, where technology leadership, earnings growth cycles, and momentum persistence influence returns. Macroeconomic factors such as interest rate expectations, corporate earnings trends, and sector rotation between growth and cyclical areas shape the environment. Regulatory developments around technology and artificial intelligence continue to support innovation-driven segments, while broader capital flows into factor strategies reflect investor demand for systematic approaches. Risks include potential reversals in momentum or growth leadership during shifts in economic conditions or valuation adjustments.
In recent market cycles, IVW has benefited from sustained strength in growth-oriented technology names, delivering exposure aligned with earnings expansion in high-growth sectors. SPMO has captured periods of strong price trends, often showing distinct behavior during momentum-driven rallies or rotations toward cyclical industrials. Relative positioning highlights IVW’s broader diversification versus SPMO’s concentrated, trend-focused approach. Volatility differences arise from the underlying factors, with momentum strategies potentially exhibiting sharper shifts during trend changes compared to the more stable growth characteristics emphasized by IVW.
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 the AI Screener to enhance your research process.
Based on observable structural factors, Tickeron’s AI would currently assign a modest preference to the Invesco S&P 500 Momentum ETF (SPMO) due to its lower expense ratio, concentrated holdings profile, and alignment with momentum trends observed across recent market cycles. The combination of cost efficiency and factor consistency provides a probabilistic edge in environments favoring trend persistence, though both ETFs remain suitable depending on an investor’s specific factor allocation objectives.
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| IVW | SPMO | IVW / SPMO | |
| Gain YTD | 9.119 | 26.556 | 34% |
| Net Assets | 71.3B | 19.4B | 368% |
| Total Expense Ratio | 0.18 | 0.13 | 138% |
| Turnover | 31.00 | 44.00 | 70% |
| Yield | 0.35 | 0.67 | 52% |
| Fund Existence | 26 years | 11 years | - |
| IVW | SPMO | |
|---|---|---|
| RSI ODDS (%) | 2 days ago 66% | 2 days ago 74% |
| Stochastic ODDS (%) | 2 days ago 89% | 2 days ago 76% |
| Momentum ODDS (%) | 2 days ago 76% | 2 days ago 76% |
| MACD ODDS (%) | 2 days ago 82% | 2 days ago 77% |
| TrendWeek ODDS (%) | 2 days ago 77% | 2 days ago 79% |
| TrendMonth ODDS (%) | 2 days ago 85% | 2 days ago 83% |
| Advances ODDS (%) | 11 days ago 86% | 9 days ago 83% |
| Declines ODDS (%) | 2 days ago 77% | 2 days ago 75% |
| BollingerBands ODDS (%) | 2 days ago 90% | 2 days ago 84% |
| Aroon ODDS (%) | 2 days ago 90% | 2 days ago 85% |
| 1 Day | |||
|---|---|---|---|
| ETFs / NAME | Price $ | Chg $ | Chg % |
| MRAL | 69.39 | 8.56 | +14.07% |
| GraniteShares 2x Long MARA Daily ETF | |||
| BITU | 9.66 | 0.49 | +5.34% |
| ProShares Ultra Bitcoin ETF | |||
| VIOO | 131.54 | 3.22 | +2.51% |
| Vanguard S&P Small-Cap 600 ETF | |||
| WWJD | 39.13 | 0.93 | +2.43% |
| Inspire International ETF | |||
| RSPR | 37.13 | -0.13 | -0.34% |
| Invesco S&P 500® Equal Wt Real Estt ETF | |||
A.I.dvisor indicates that over the last year, IVW has been closely correlated with NVDA. These tickers have moved in lockstep 76% of the time. This A.I.-generated data suggests there is a high statistical probability that if IVW jumps, then NVDA could also see price increases.
| Ticker / NAME | Correlation To IVW | 1D Price Change % | ||
|---|---|---|---|---|
| IVW | 100% | +2.24% | ||
| NVDA - IVW | 76% Closely correlated | +2.22% | ||
| RVTY - IVW | 68% Closely correlated | +0.23% | ||
| LRCX - IVW | 67% Closely correlated | +12.65% | ||
| AVGO - IVW | 66% Loosely correlated | +3.62% | ||
| TER - IVW | 63% Loosely correlated | +9.73% | ||
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A.I.dvisor indicates that over the last year, SPMO has been closely correlated with LRCX. These tickers have moved in lockstep 71% of the time. This A.I.-generated data suggests there is a high statistical probability that if SPMO jumps, then LRCX could also see price increases.
| Ticker / NAME | Correlation To SPMO | 1D Price Change % | ||
|---|---|---|---|---|
| SPMO | 100% | +4.80% | ||
| LRCX - SPMO | 71% Closely correlated | +12.65% | ||
| AVGO - SPMO | 67% Closely correlated | +3.62% | ||
| KLAC - SPMO | 67% Closely correlated | +12.92% | ||
| ETN - SPMO | 65% Loosely correlated | +4.84% | ||
| AMAT - SPMO | 64% Loosely correlated | +11.19% | ||
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