GET DAILY SIGNALSJMOM vs SPMO: Broad vs. Concentrated Approaches to U.S. Momentum
Key Takeaways
- JMOM tracks the JPMorgan U.S. Momentum Factor Index, holding roughly 280–300 U.S. large- and mid-cap stocks, while SPMO tracks the S&P 500 Momentum Index with approximately 100 of the highest-momentum names in the S&P 500.
- SPMO is far more concentrated, with its top 10 holdings often representing more than half of assets, whereas JMOM spreads weight across a much broader, more diversified portfolio.
- Both funds are heavily exposed to information technology and semiconductors, but SPMO carries a materially higher single-stock concentration in names such as MU and NVDA.
- Costs are nearly identical — JMOM charges 0.12% versus SPMO at 0.13% — so expense ratio is not a decisive differentiator.
- SPMO offers significantly deeper liquidity and a much larger asset base, which can translate to tighter bid-ask spreads for institutional and active traders.
- Tickeron AI Verdict: SPMO is the favored ticker, reflecting its larger scale, stronger liquidity, and concentrated alignment with the market's most persistent momentum leaders.
Introduction
Momentum investing has been one of the defining themes of recent market cycles, as capital has repeatedly concentrated in a narrow group of large-cap technology and semiconductor leaders. Against that backdrop, JMOM and SPMO represent two of the most accessible ways to capture U.S. large-cap momentum in a single exchange-traded fund. They are direct competitors targeting the same investor objective — owning stocks with the strongest relative price strength — but they pursue that goal with very different construction methods. JMOM offers broad factor-based diversification, while SPMO takes a more concentrated, index-driven approach. This ETF comparison examines how their structural differences translate into distinct sector exposure, risk profiles, and relative positioning.
A Closer Look at JMOM
JMOM is a passively managed factor ETF that tracks the JPMorgan U.S. Momentum Factor Index. It seeks to hold U.S. equities selected for positive momentum characteristics, generally numbering between roughly 280 and 300 holdings. This breadth gives the fund a large-cap tilt while retaining a modest allocation to mid-cap names. The portfolio is weighted using an optimized market-capitalization approach rather than pure momentum score, which moderates single-stock risk. I also checked this using Tickeron’s AI Screener to see how the holdings compare across the sector.
Technology is the dominant sector exposure, historically in the high-30% range, followed by industrials, financial services, and healthcare. Representative top holdings have included AMD, MU, AAPL, MSFT, GOOGL, NVDA, AVGO, and JNJ. The expense ratio is 0.12%, among the lowest in the factor category. Because no single position dominates, JMOM behaves more like a diversified large-cap growth strategy with a momentum screen than a pure high-conviction momentum fund.
A Closer Look at SPMO
SPMO is a passively managed ETF tracking the S&P 500 Momentum Index, which selects roughly 100 stocks from the S&P 500 with the highest momentum scores and weights them accordingly. This results in a much more concentrated portfolio: the top 10 holdings frequently account for more than half of total assets. The index is rebalanced on a semiannual schedule, allowing winners to accumulate weight between rebalance dates.
Information technology typically represents around half of the fund's assets, with pronounced concentration in semiconductor and memory-chip names. Top holdings have included MU, NVDA, AVGO, AAPL, GOOGL, AMD, JNJ, INTC, and LRCX. The expense ratio is 0.13%, and the fund's asset base — in the tens of billions of dollars — is far larger than JMOM's, supporting robust secondary-market liquidity.
Industry and Thematic Backdrop
Both funds sit squarely in the path of the artificial intelligence and semiconductor investment cycle that has driven U.S. equity leadership in recent market cycles. Demand for memory, accelerated computing, and AI infrastructure has powered earnings growth at many of the top holdings shared by JMOM and SPMO, sustaining the momentum factor itself. Broader macro drivers — including interest rate expectations, capital spending on data centers, and the resilience of mega-cap balance sheets — continue to shape the performance of these portfolios.
The principal risk is concentration. When a narrow group of high-momentum names drives returns, drawdowns can be sharp if sentiment shifts, earnings disappoint, or rotation broadens into value and small-cap segments. Regulatory scrutiny of large technology platforms and periodic supply-chain volatility in semiconductors are additional sector risks that affect both ETFs, though SPMO's tighter focus magnifies their impact.
Performance and Positioning Comparison
In recent weeks and months, both funds have benefited from the continued leadership of large-cap technology, but their relative positioning has differed. SPMO's concentrated, momentum-weighted construction has allowed it to capture a larger share of gains when the strongest names lead, while also exhibiting higher volatility during pullbacks. JMOM's broader, diversified approach has tended to produce smoother returns with less single-name risk, at the cost of diluted exposure to the market's biggest momentum winners. From what I see in the data, this distinction matters most when leadership narrows or broadens.
From a sector rotation perspective, both ETFs are highly sensitive to shifts between growth and value, and to changes in long-term interest rate expectations that influence the valuation of technology names. SPMO's heavier semiconductor concentration ties it more closely to the AI spending cycle, whereas JMOM's wider footprint — including greater representation in industrials and financials — provides somewhat more balance when leadership broadens. This relative positioning is the core distinction for investors weighing pure momentum conviction against diversification.
Integrating AI Tools into My ETF Research
I often turn to Tickeron’s AI Screener when comparing ETFs like these to quickly filter holdings by momentum signals, sector exposure, and liquidity metrics. It helps surface comparable ideas without manual effort and supports more informed decisions on concentration versus diversification. The tool has become a regular part of how I evaluate factor-based strategies in the current environment.
Disclaimer
The information on this webpage is provided for general informational and educational purposes only and is not intended as investment advice, a recommendation to purchase or sell any security, or an offer or solicitation related to investments. It does not consider your personal financial situation, goals, or risk profile, and all investing carries inherent risks, including the possibility of losing your entire investment. For more details, please review our full disclaimer.
Contributor
Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has extensive experience as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as the CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years developing his proprietary trading and quantitative algorithms (now Tickeron’s A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors via an easy-to-use interface.
SPMO in downward trend: price dove below 50-day moving average on October 12, 2026
SPMO moved below its 50-day moving average on October 12, 2026 date and that indicates a change from an upward trend to a downward trend. In 36 of 43 similar past instances, the stock price decreased further within the following month. The odds of a continued downward trend are 84%.
Technical Analysis (Indicators)
Bearish Trend Analysis
The Momentum Indicator moved below the 0 level on October 08, 2026. You may want to consider selling the stock, shorting the stock, or exploring put options on SPMO as a result. In 73 of 89 cases where the Momentum Indicator fell below 0, the stock fell further within the subsequent month. The odds of a continued downward trend are 82%.
The Moving Average Convergence Divergence Histogram (MACD) for SPMO turned negative on October 09, 2026. This could be a sign that the stock is set to turn lower in the coming weeks. Traders may want to sell the stock or buy put options. Tickeron's A.I.dvisor looked at 51 similar instances when the indicator turned negative. In 41 of the 51 cases the stock turned lower in the days that followed. This puts the odds of success at 80%.
The 10-day moving average for SPMO crossed bearishly below the 50-day moving average on October 16, 2026. This indicates that the trend has shifted lower and could be considered a sell signal. In 16 of 20 past instances when the 10-day crossed below the 50-day, the stock continued to move higher over the following month. The odds of a continued downward trend are 80%.
Following a 3-day decline, the stock is projected to fall further. Considering past instances where SPMO declined for three days, the price rose further in 50 of 62 cases within the following month. The odds of a continued downward trend are 77%.
The Aroon Indicator for SPMO entered a downward trend on October 30, 2026. This could indicate a strong downward move is ahead for the stock. Traders may want to consider selling the stock or buying put options.
Bullish Trend Analysis
The RSI Indicator points to a transition from a downward trend to an upward trend -- in cases where SPMO's RSI Oscillator exited the oversold zone, 22 of 24 resulted in an increase in price. Tickeron's analysis proposes that the odds of a continued upward trend are 90%.
The Stochastic Oscillator suggests the stock price trend may be in a reversal from a downward trend to an upward trend. 46 of 56 cases where SPMO's Stochastic Oscillator exited the oversold zone resulted in an increase in price. Tickeron's analysis proposes that the odds of a continued upward trend are 82%.
Following a +3.09% 3-day Advance, the price is estimated to grow further. Considering data from situations where SPMO advanced for three days, in 309 of 378 cases, the price rose further within the following month. The odds of a continued upward trend are 82%.
SPMO may jump back above the lower band and head toward the middle band. Traders may consider buying the stock or exploring call options.
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