Momentum factor vs. traditional growth

SPMO vs VUG

Both funds get filed under “growth,” and both have done well. But one selects stocks on recent price behavior and the other on company fundamentals, and that difference shows up in the one column most comparisons leave out.

By Kevin WinmillUpdated 4 min read

#What this plan actually returned

These are real results, not estimates. We ran $10,000 up front plus $500 a month from September 9, 2016 to September 9, 2026 (10.0 years), with dividends reinvested, against actual daily closing prices for each fund.

Dollar-cost averaging backtest results for SPMO and VUG from 2016-09-09 to 2026-09-09
TickerInvestedFinal valueTotal returnAnn. returnWorst drop
SPMO$70,000$252,520+260.74%+21.42%-30.95%
VUG$70,000$203,385+190.55%+17.89%-35.61%

Ann. return is the internal rate of return (IRR), which accounts for how long each individual contribution was invested, so it is lower than the headline total return on a plan that kept adding money. Worst drop is the deepest peak-to-trough decline in the fund itself during this window, measured on daily closes.

Figures current as of . Results change as markets move.

Pre-tax and excluding brokerage commissions. See How It Works for the full methodology, or re-run this exact comparison with your own numbers.

Portfolio value over time: SPMO versus VUGPortfolio value over the full simulation for SPMO and VUG, with the dashed line showing total contributions to date. The gap between a line and the dashed line is that position's gain.$0$100K$200K$300K20182020202220242026
SPMOVUGMoney you put in
Portfolio value over the full simulation for SPMO and VUG, with the dashed line showing total contributions to date. The gap between a line and the dashed line is that position's gain.

#Reading the result

SPMO finished about $50,000 ahead on identical contributions, an annualized gap of roughly three and a half percentage points. That is a substantial margin, and momentum as a factor has a long documented history across markets and decades, so this is not purely an artifact of one lucky window.

The drawdown column is where it gets more interesting, and it runs against intuition. SPMO’s worst decline was about 31 percent; VUG’s was about 36 percent. The momentum fund, which most people would guess is the riskier of the two, had the shallower worst case in this window.

#Why the momentum fund fell less

The explanation is in the rebalancing schedule rather than in anything about the underlying companies. SPMO reconstitutes periodically based on trailing risk-adjusted price performance. When a group of stocks stops performing, the next reconstitution reduces or removes them. That is a mechanical trend-following behavior, and in a decline that develops over months rather than days, it can move the portfolio out of the worst performers partway through.

The dates support that reading. VUG’s worst window ran from November 19, 2021 to November 3, 2022, roughly a year of repricing in long-duration growth stocks as rates rose. SPMO’s worst window was the February to March 2020 crash, a five-week collapse that was over before any rebalance could respond. Momentum strategies tend to handle slow trends reasonably and fast shocks poorly, which is exactly the pattern here.

The corresponding weakness is a sharp V-shaped reversal. If a fund rebalances out of beaten-down stocks and those stocks then rebound hardest, the strategy sells low and buys whatever led on the way up. Momentum’s historically documented bad episodes are concentrated around exactly these sharp reversals off a market bottom.

#What each fund actually selects

SPMO(Invesco S&P 500 Momentum ETF) starts from the S&P 500 and keeps roughly the 100 stocks with the strongest risk-adjusted price momentum over a trailing lookback period, weighted by a combination of momentum score and market capitalization. The selection criterion is price behavior. It does not ask what a company earns or what it is worth.

VUG(Vanguard Growth ETF) tracks a large-cap growth index that classifies companies using fundamental measures: earnings growth, sales growth, and return on assets among them. It holds several hundred stocks and turns over far less, because a company’s fundamental classification changes slowly.

Their holdings overlap heavily at any given moment, since the largest US growth companies have also tended to have the strongest momentum. The difference is what happens when that stops being true: SPMO rotates out and VUG largely does not.

#The cost this backtest does not show

Momentum strategies trade far more than fundamental ones. Every reconstitution generates transactions, and transactions generate costs that are only partly captured in an expense ratio. More importantly for a taxable account, turnover inside a fund can generate capital gains distributions that you owe tax on in the year they occur, regardless of whether you sold anything.

This simulation is pre-tax and excludes brokerage commissions, which is stated in the methodology on How It Works. For a high-turnover strategy held in a taxable account, that omission favors SPMO in the table above by more than it favors VUG. In a tax-advantaged account the distinction largely disappears.

#What to test

  • Add VOO as a third ticker. Both of these funds should be measured against the plain index before being measured against each other.
  • Run a window ending in 2022 rather than today, so the period finishes in a drawdown instead of after a recovery. Factor strategies look very different depending on where you stop.
  • Note that SPMO's history is short. It launched in late 2015, so no window here includes 2008 or the dot-com period.
  • Compare the gains share versus contributions share for each, rather than only the ending balance.
Documented factor premiums have historically gone through long stretches of underperformance, sometimes a decade or more. A ten-year window in which momentum worked is not evidence that it will work over your particular holding period, and the 2000 to 2010 comparison shows what an extended adverse regime for growth-oriented strategies looks like.

Change the contribution amount, schedule, or date range and re-run this comparison against the same historical data.

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