US ETF · FF6 US RETURNS IN USD

VUG — Vanguard Growth ETF

Fund overlap 2004-Feb → 2026-Mar (266 months) · Backtest basis 1963-Jul → 2026-Apr (754 months) · Adj. R² 0.971 · AUM US$195,610M · MER 0.03%
Structural context first: age and backtest basis explain how much live history is available versus how far the winning factor model can be replayed. Then fit, scale, cost, valuation, and payoff metrics show whether this is a clean, investable expression of the exposure it claims to deliver.
Age
22.2 years
2004-Feb → 2026-Mar
Long live record
Backtest Basis
62.8 years
1963-Jul → 2026-Apr
Full long-run factor record
Adj. R²
0.971
Very high model fit
AUM
US$195.6B
Very large live fund
MER
0.03%
Very low cost
Dividend valuation
355
Rich
355
80 90 100 110 120+
1.88% Current recurring yield
100 = median · below 100 inexpensive · above 100 rich Dividend valuation scale
Backtested Rel. Sharpe
0.76×
Weak risk-adjusted edge
R
0.5 1.0 1.3 1.8
Relative to a plain market benchmark. 1.0 = market-like risk-adjusted return; above 1.0 clears the market hurdle.
Smart-β Net
-1.33%
Negative value-add
S
-3% 0% 2.5% 4.5%
Annualized non-market factor contribution plus alpha. Above 0% means the smart-beta sleeve added value over plain market exposure.

What VUG Is

VUG (Vanguard Growth ETF) from Vanguard is a US equity ETF with $195.6B in assets, regressed on the FF6 US over 266 months. The fund tilts away from value (hml) (β=-0.27). Backtested-simulation excess return is +4.96% annualized; the in-sample realized excess was +9.65%.

Why VUG Ranks This Way

  • Backtested relative Sharpe is 0.76, below the market's 1.00 benchmark.
  • Realized relative Sharpe is 1.03 over the fund's 266-month live sample.
  • Strongest non-market tilts point away from value (hml) (β=-0.27) and away from investment (cma) (β=-0.13).
  • Dividend valuation looks rich at 355 versus a 100 median baseline.
Best-fit classification
US Equity FF6 US Regression basis: USD Adj. R² 0.971 Fit window: 266M Backtest basis: 754M

This fund is classified as US Equity because that factor set produced the strongest accepted fit. Backtested figures use the winning model's full factor history (1963-Jul → 2026-Apr, 754 months), while the betas themselves are estimated over the fund-overlap window (266 months).

Factor return decomposition
Each bar = βi × factor return, geometrically annualized. Summary rows are computed from the combined monthly series they name.
Model: FF6 US
Sharpe — Backtested Sim.
0.272
Rel. to market: 0.759
Sharpe — Realized
0.592
Rel. to market: 1.032
How are these computed?

Currency basis: returns and factor contributions on this page are in USD. Fama-French US 6-factor set (Ken French data library, monthly, USD basis).

Classification winner: FF6 US with Adj. R² 0.971.

Factor context panel: each non-market row compares the current fund with stronger-fit public peers using FF6 US. Beta mode shows raw loadings, percentile mode ranks the fund within the positive-exposure subset, and the linked ticker points to the strongest peer in that factor.

Backtested Sim. applies VUG's regression betas to the full factor history (1963-Jul → 2026-Apr, 754 months). Individual factor bars show separately annualized sleeves, while the subtotal rows are computed from the combined monthly non-market and smart-beta series directly. The Sharpe uses VUG's realized in-sample volatility as the denominator — a deliberately conservative choice, since fixed-loading factor returns are smoother than what any real fund actually delivers.

Realized applies the same betas to the factor returns observed during VUG's lifetime only (2004-Feb → 2026-Mar). The Sharpe is the fund's actual excess return over its actual volatility. Full methodology →

Factor exposure context
Each non-market row compares this fund with stronger-fit public peers using FF6 US. Toggle between raw factor beta and percentile rank within the same positive-exposure peer set.
Compared against 342 funds using FF6 US
Peer filter: Equity · AUM floor · 24M+ history · Adj. R² > 0.80 · |βmkt−1| < 0.25 · Non-Mkt > 0
Default view is percentile rank. Switch to β scale when you want the raw loading magnitude.
SMB
-0.30
0
0.23
0.45
0.68
0.90
0
20
40
60
80
90
100
0
2
4
6
8
10
12
β -0.11
rank n/a
t -4.8
Current fund: non-positive loading · Top decile begins at β +0.88 · Leader: RZV
HML
-0.30
0
0.23
0.45
0.68
0.90
0
20
40
60
80
90
100
0
2
4
6
8
10
12
β -0.27
rank n/a
t -12.7
Current fund: non-positive loading · Top decile begins at β +0.41 · Leader: KBWB
RMW
-0.30
0
0.23
0.45
0.68
0.90
0
20
40
60
80
90
100
0
2
4
6
8
10
12
β +0.00
0th pct
t +0.1
Current fund: 0th percentile of positive peers · Top decile begins at β +0.29 · Leader: DSMC
CMA
-0.30
0
0.23
0.45
0.68
0.90
0
20
40
60
80
90
100
0
2
4
6
8
10
12
β -0.13
rank n/a
t -4.1
Current fund: non-positive loading · Top decile begins at β +0.22 · Leader: RWJ
UMD
-0.30
0
0.23
0.45
0.68
0.90
0
20
40
60
80
90
100
0
2
4
6
8
10
12
β -0.01
rank n/a
t -0.6
Current fund: non-positive loading · Top decile begins at β +0.17 · Leader: MTUM
Factor exposures
Factor β t-stat Backtested % Realized %
Size (SMB) -0.107 -4.84 -0.24% +0.01%
Value (HML) -0.273 -12.73 -1.01% -0.02%
Profitability (RMW) 0.004 0.15 +0.01% +0.02%
Investment (CMA) -0.134 -4.12 -0.40% +0.02%
Momentum (UMD) -0.007 -0.57 -0.05% -0.01%
Non-Market Factor Contribution · combined non-market series -1.70% -0.01%
Alpha (intercept) — 0.61 +0.37%
Smart-Beta Net · combined non-market series + alpha -1.33% +0.36%
+ Mkt-RF contribution · market 1.073 83.91 +6.48% +9.19%
= Total excess return +4.96% +9.65%
+ Rf base (%) 4.44% → 9.40% total 1.68% → 11.33% total
Fund snapshot
Issuer
Vanguard
Asset class
Equity
Inception
2004-01-26
Dividend yield
1.88%
Div CAGR
4.45%
Dividend valuation
355 (100=median)
Embed this chart

Use this iframe URL on Discourse forums (e.g. Rational Reminder Community) or any site that allows iframe embeds. For X, Reddit, or Slack, paste the fund page URL directly — the social card image is auto-generated for this fund. 

<iframe src="https://verifiedbeta.com/embed/us/VUG/waterfall/" width="720" height="540" style="border:0;" loading="lazy"></iframe>

These funds share the same statistically significant, material FF6 non-market factor set as VUG. Broad-market funds are excluded unless they have verified factor exposure.

IWF
iShares Russell 1000 Growth ETF
HML shape 100 · level 97
Compare VUG vs IWF
97
Near substitute
ILCG
iShares Morningstar Growth ETF
HML shape 99 · level 91
Compare VUG vs ILCG
92
Near substitute
QQQM
Invesco NASDAQ 100 ETF
HML shape 98 · level 90
Compare VUG vs QQQM
90
Near substitute
VGT
Vanguard Information Technology ETF
HML shape 95 · level 87
Compare VUG vs VGT
87
Verified similar
ONEQ
Fidelity Nasdaq Composite Index ETF
HML shape 86 · level 86
Compare VUG vs ONEQ
86
Verified similar
FELG
Fidelity Enhanced Large Cap Growth ETF
HML shape 96 · level 80
Compare VUG vs FELG
83
Verified similar
View full VUG similarity cluster
All US Leaders US Universe Methodology

FAQ

What does this VUG ETF page measure?

This page evaluates VUG using factor regressions, relative Sharpe, valuation, and peer context. It is designed for ETF due diligence rather than quote tracking.

Why can Backtested Sim. and Realized differ?

Both views use the same estimated betas. The difference is the return window: Backtested Sim. applies them to the full factor history, while Realized applies them only during the fund's live sample.

Why might a high-return fund still look weak here?

A fund can post strong raw returns and still look unattractive on this screen if its non-market factor capture is weak, its implementation drag is high, or its volatility-adjusted return profile is weaker than the market.

How should US investors use this page?

Use it as a starting point for ETF selection: check whether the fund's live behavior, valuation, and peer context line up with the story the product label implies.

Research disclaimer

Factor decomposition shows what VUG's historical betas would have earned under each scenario — not a forecast, not investment advice. Backtested simulation assumes loadings stay fixed across the long sample, which is unrealistic for any real-world fund. Use this as one input to ETF due diligence, not a substitute for it.

Important context

VerifiedBeta publishes educational ETF research, not personalized investment advice, portfolio management, or security recommendations. Funds that screen well here can still be unsuitable for your objectives, taxes, liquidity needs, or constraints. Review fund documents, methodology assumptions, and your own circumstances before acting. See the full disclaimer.