IVW, QQQM, and SPMO represent complementary approaches to large-cap U.S. growth investing. While each emphasizes technology and innovation leaders, they diverge in index construction: IVW selects growth stocks from the S&P 500, QQQM replicates the NASDAQ-100, and SPMO overlays momentum scoring on S&P 500 constituents. These differences produce varying levels of concentration, sector exposure, and factor sensitivity. Investors evaluating these exchange-traded funds (ETFs) seek clarity on how structural choices influence diversification, cost, and positioning across market cycles.
The iShares S&P 500 Growth ETF (IVW) seeks to track the S&P 500 Growth Index, which identifies large-cap companies exhibiting strong growth characteristics based on earnings and revenue metrics. The fund holds approximately 147 securities, with the top 10 holdings typically accounting for around 50-60% of assets. Prominent positions often include technology leaders such as NVDA, MSFT, and AAPL. Sector allocation is heavily weighted toward Information Technology (approximately 49-51%), followed by Communication Services and Consumer Discretionary. IVW maintains a passive structure with an expense ratio of 0.18%. Rebalancing aligns with the underlying index methodology, providing consistent exposure to growth-oriented large-cap equities.
The Invesco NASDAQ 100 ETF (QQQM) is designed to track the NASDAQ-100 Index, providing exposure to the 100 largest non-financial companies listed on the Nasdaq exchange. The ETF holds approximately 103 securities, with the top 10 holdings representing roughly 45-50% of the portfolio. Key holdings frequently feature NVDA, MSFT, AMZN, and META. Sector breakdown shows dominant exposure to Technology (around 54-64%), Consumer Discretionary, and Communication Services. QQQM employs a passive, market-capitalization-weighted approach with quarterly rebalancing and reconstitution. Its expense ratio stands at 0.15%, reflecting cost-efficient access to mega-cap growth names.
The Invesco S&P 500® Momentum ETF (SPMO) tracks the S&P 500 Momentum Index, which selects the top 100 S&P 500 constituents demonstrating the strongest price momentum, weighted by a combination of market capitalization and momentum score. The fund typically maintains around 100 holdings, with the top 10 often comprising approximately 50% of assets. Holdings emphasize recent outperformers across sectors, frequently including technology and select industrial or financial names. Sector allocation shifts with momentum trends but commonly features elevated Information Technology exposure alongside Industrials and Communication Services. SPMO uses a passive smart-beta strategy with semi-annual rebalancing. The expense ratio is 0.13%, the lowest among the three ETFs.
The ETFs operate within the large-cap growth segment of the U.S. equity market, dominated by technology, communication services, and consumer discretionary sectors. Macroeconomic drivers include interest-rate trajectories, corporate earnings growth in artificial intelligence and cloud computing, and capital allocation toward innovative companies. Regulatory developments around technology platforms and geopolitical tensions affecting supply chains influence sector sentiment. Earnings trends among mega-cap holdings continue to shape investor focus on profitability and valuation multiples. Broader market cycles determine the relative appeal of growth versus value styles, while sector risks such as regulatory scrutiny and competitive disruption remain persistent considerations for these strategies.
In recent months and market cycles, the three ETFs have exhibited correlated yet differentiated behavior driven by their underlying exposures. QQQM’s concentration in the NASDAQ-100 has produced heightened sensitivity to mega-cap technology performance. IVW’s growth-factor screening from the broader S&P 500 has delivered more balanced participation across growth names. SPMO’s momentum overlay has introduced greater variability in sector weights, potentially amplifying upside during strong-trending periods while increasing drawdown risk when momentum reverses. Relative volatility differences stem from holdings concentration and rebalancing frequency. All three have shown resilience in innovation-driven rallies but may diverge during rotations toward value or defensive sectors. Structural distinctions in index selection explain why momentum-focused SPMO can lead or lag pure growth or broad NASDAQ exposure depending on prevailing market trends.
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.
Based on structural strength, diversification profile, cost efficiency, momentum stability, and risk-adjusted positioning, Tickeron’s AI would currently assign a probabilistic edge to SPMO. Its lowest expense ratio, focused momentum methodology, and adaptive sector exposure provide a compelling combination for investors seeking systematic participation in trending large-cap equities while maintaining competitive costs relative to peers.
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| IVW | QQQM | SPMO | |
| Gain YTD | 9.192 | 15.420 | 23.975 |
| Net Assets | 73.5B | 94.5B | 19.4B |
| Total Expense Ratio | 0.18 | 0.15 | 0.13 |
| Turnover | 31.00 | 6.00 | 44.00 |
| Yield | 0.35 | 0.42 | 0.67 |
| Fund Existence | 26 years | 6 years | 11 years |
| IVW | QQQM | SPMO | |
|---|---|---|---|
| RSI ODDS (%) | 2 days ago 62% | 2 days ago 64% | 2 days ago 74% |
| Stochastic ODDS (%) | 2 days ago 89% | 2 days ago 90% | 2 days ago 85% |
| Momentum ODDS (%) | 2 days ago 76% | 2 days ago 74% | 2 days ago 80% |
| MACD ODDS (%) | 2 days ago 71% | 2 days ago 78% | 2 days ago 77% |
| TrendWeek ODDS (%) | 2 days ago 77% | 2 days ago 80% | 2 days ago 79% |
| TrendMonth ODDS (%) | 2 days ago 87% | 2 days ago 88% | 2 days ago 83% |
| Advances ODDS (%) | 10 days ago 86% | 9 days ago 87% | 8 days ago 83% |
| Declines ODDS (%) | 6 days ago 77% | 6 days ago 80% | 6 days ago 75% |
| BollingerBands ODDS (%) | 2 days ago 72% | 2 days ago 73% | 2 days ago 79% |
| Aroon ODDS (%) | 2 days ago 90% | 2 days ago 90% | 2 days ago 85% |
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% | -0.25% | ||
| LRCX - SPMO | 71% Closely correlated | +0.84% | ||
| AVGO - SPMO | 67% Closely correlated | -1.12% | ||
| KLAC - SPMO | 67% Closely correlated | +1.49% | ||
| ETN - SPMO | 65% Loosely correlated | -0.35% | ||
| AMAT - SPMO | 64% Loosely correlated | +1.43% | ||
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