Fund index
MTUM
16 articles on this site analyse MTUM — 5 of them head-on.
Measured concentration
as of 2026-04-30MTUM reports 128 positions, but the weights make it behave like about 40.3 equally weighted ones. Computed by this site from the fund's SEC Form N-PORT filing — see what this measure does not tell you and the full table.
Most often compared against
4Measures applied to it
8All articles
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The Hidden Cost of Turnover: How Rebalancing and Reconstitution Erode Factor-ETF Returns
Factor ETFs carry a cost the expense ratio never shows: the trading friction of periodic reconstitution and rebalancing, which is absorbed inside net asset...
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Momentum Crashes: The Rare, Violent Drawdowns Hiding Inside MTUM
MTUM has compounded at 16.3% over ten years, but its risk is negatively skewed: the danger sits in rare, sharp reversals rather than in day-to-day...
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Momentum Crashes, Explained: Why the Most Crowded Trades Unwind Fastest
Momentum earns a long-run premium but carries deep negative skew: the strategy's worst days cluster together and arrive precisely when a crowded trade...
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OMFL vs FCTR: Dynamic Multi-Factor — Rules-Based Rotation vs AI Optimization
Both funds rotate factor exposure by rule, not by forecast — but OMFL blends several factors against a macro-regime signal while FCTR makes a near-binary...
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USMV vs SPLV: Two Approaches to Low-Volatility Investing — Which Defense Holds Up?
USMV (optimizer-based minimum variance) and SPLV (simple lowest-volatility ranking) sound similar but are built differently — and the construction gap, not...
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VGT vs QQQ: Tech Sector vs Nasdaq-100 — How Different Are They Really?
VGT is a pure GICS Information Technology sector fund; QQQ is the Nasdaq-100, a multi-sector index that excludes some of the names most people assume are...
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How Factor Loadings Drift: Watching MTUM, QUAL, and SIZE Over Five Years
The three iShares single-factor ETFs all carry the same 0.15% fee, but their realized 5Y CAGRs differ by 6.0 percentage points — that gap is mostly about...
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AMOM Explained: How AI Weights Momentum Differently from MTUM
MTUM is a $24B rules-based momentum factor ETF charging 0.15%. AMOM is a $30M AI-overlay product charging 0.75%. The construction philosophies are...
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AIEQ Review: 7 Years of Live AI-Managed ETF — What Actually Worked
After more than eight years of live trading, AIEQ has trailed SPY by roughly 700 basis points per year on a 5Y annualized basis, while running 5.3 points...
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VOO vs. AMOM: Can AI Momentum Outperform the S&P 500? (2026 Analysis)
Over the trailing five years, VOO compounded at 13.1% per year versus AMOM at 9.6% — with roughly 40% more volatility and a maximum drawdown nearly twice as...
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The Master Class: How to Use Claude (Anthropic) to Backtest Your Own ETF Strategy
Claude can write the Python and run the math, but it cannot tell you whether your test design is honest. Most retail backtests fail at design, not at code....
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Best AI-Managed ETFs for 2026: A Deep Dive into AIEQ and AMOM
AIEQ (Amplify AI Powered Equity) and AMOM (QRAFT AI-Enhanced Momentum) both charge 0.75% — roughly 25 times the cost of a broad-market index ETF — for an...
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VOO vs. MTUM vs. QUAL: Which Smart Beta ETF Wins Based on Historical Backtests?
Over the trailing 5 years, plain VOO (13.1% CAGR) beat both MTUM (11.5%) and QUAL (11.4%) — the factor premium did not show up in this window. Over 10...
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The Master Guide to Evidence-Based ETF Portfolios: Using AI to Optimize Allocation (2026)
"AI-driven portfolio optimization" mostly solves a problem long-horizon investors don't actually have. Real-time tilting at retail frequency tends to cost...
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VOO vs. MTUM vs. QUAL: Which Smart Beta ETF Wins Numerically? (Backtest Analysis)
Over the trailing five years, the cap-weighted S&P 500 (VOO) actually outperformed both factor ETFs on raw return — 13.1% CAGR versus MTUM's 11.5% and...
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Why "Factor Investing" Still Works: Applying Fama-French Models in the AI Era
The Fama-French factors weren't a trading edge that AI could arbitrage away — they were compensation for risks investors still won't bear cheerfully, plus...
Mentions are detected across the full text of every article, so an appearance may be a passing comparison rather than the subject. Nothing here is a recommendation to buy or sell — see the disclaimer.