US ETF · FF6 US RETURNS IN USD

VFVA — Vanguard U.S. Value Factor ETF

Fund overlap 2018-Mar → 2026-Aug (102 months) · Backtest basis 1963-Jul → 2026-Aug (758 months) · Adj. R² 0.975 · AUM US$785M · MER 0.13%
The cards separate the fund's live record from the longer factor history used for the backtest, then show model fit, cost, valuation, and risk-adjusted results.
Age
8.6 years
2018-Feb → 2026-Sep
Established live fund
Backtest Basis
63.2 years
1963-Jul → 2026-Aug
Full long-run factor record
Adj. R²
0.975
Very high model fit
AUM
US$0.8B
Mid-sized live fund
MER
0.13%
Very low cost
Dividend valuation
118
Moderately rich
118
80 90 100 110 120+
1.85% Trailing 12-month yield
100 = median · below 100 inexpensive · above 100 rich Dividend valuation scale
Backtested Rel. Sharpe
0.87×
Below market hurdle
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
+1.57%
Positive 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.
Implementation: Core equity. No deterministic enhanced-income or derivative-income mandate detected.

What VFVA Is

VFVA (Vanguard U.S. Value Factor ETF) from Vanguard is a US equity ETF with $0.8B in assets, regressed on the FF6 US over 102 months. The fund tilts toward size (smb) (β=0.48); tilts toward value (hml) (β=0.51); tilts away from momentum (umd) (β=-0.17). Backtested-simulation excess return is +8.01% annualized; the in-sample realized excess was +8.88%.

Why VFVA Ranks This Way

  • Backtested relative Sharpe is 0.87, below the market's 1.00 benchmark.
  • Realized relative Sharpe is 0.57 over the fund's 102-month live sample.
  • Strongest non-market tilts point toward value (hml) (β=0.51) and toward size (smb) (β=0.48).
  • Dividend valuation is 18% richer than its historical median (118 on the 100 scale).
Best-fit classification
US Equity FF6 US Regression basis: USD Adj. R² 0.975 Fit window: 102M Backtest basis: 758M

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-Aug, 758 months), while the betas themselves are estimated over the fund-overlap window (102 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.
0.440
Rel. to market: 0.871
Sharpe — Realized
0.387
Rel. to market: 0.571
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 0.975.

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 VFVA's regression betas to the full factor history (1963-Jul → 2026-Aug, 758 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 VFVA'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 VFVA's lifetime only (2018-Mar → 2026-Aug). 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 334 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
0.24
0.47
0.71
0.95
0
20
40
60
80
90
100
0
2
4
6
8
10
12
β +0.48
57th pct
t +10.8
Current fund: 57th percentile of positive peers · Top decile begins at β +0.88 · Leader: AVSC
HML
-0.30
0
0.24
0.47
0.71
0.95
0
20
40
60
80
90
100
0
2
4
6
8
10
12
β +0.51
94th pct
t +13.3
Current fund: 94th percentile of positive peers · Top decile begins at β +0.41 · Leader: KBWB
RMW
-0.30
0
0.24
0.47
0.71
0.95
0
20
40
60
80
90
100
0
2
4
6
8
10
12
β +0.15
58th pct
t +3.4
Current fund: 58th percentile of positive peers · Top decile begins at β +0.27 · Leader: QVAL
CMA
-0.30
0
0.24
0.47
0.71
0.95
0
20
40
60
80
90
100
0
2
4
6
8
10
12
β +0.13
58th pct
t +2.2
Current fund: 58th percentile of positive peers · Top decile begins at β +0.23 · Leader: RWJ
UMD
-0.30
0
0.24
0.47
0.71
0.95
0
20
40
60
80
90
100
0
2
4
6
8
10
12
β -0.17
rank n/a
t -5.7
Current fund: non-positive loading · Top decile begins at β +0.19 · Leader: MTUM
Factor exposures
Factor β t-stat Backtested % Realized %
Size (SMB) 0.480 10.80 +0.95% -1.07%
Value (HML) 0.512 13.28 +1.68% -0.40%
Profitability (RMW) 0.147 3.35 +0.44% +0.33%
Investment (CMA) 0.126 2.22 +0.36% +0.04%
Momentum (UMD) -0.167 -5.74 -1.22% -0.36%
Non-Market Factor Contribution · combined non-market series +2.16% -1.73%
Alpha (intercept) — -0.45 -0.58%
Smart-Beta Net · combined non-market series + alpha +1.57% -2.30%
+ Mkt-RF contribution · market 1.037 43.27 +6.37% +11.90%
= Total excess return +8.01% +8.88%
+ Rf base (%) 4.44% → 12.44% total 2.62% → 11.51% total
Fund snapshot
Issuer
Vanguard
Asset class
Equity
Inception
2018-02-13
Trailing 12-month yield
1.85%
Div CAGR
10.02%
Dividend valuation
118 (100=median)
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Matches share at least one verified factor exposure with VFVA. They are ranked by modeled factor tracking error: the annualized volatility of their factor-return difference, not a return gap or forecast. Both funds use the same 36-month fitting window; a longer factor-volatility check also limits each match to 3% annualized. How matching works.

FNK
First Trust Mid Cap Value AlphaDEX Fund
SMB HML UMD Modeled factor tracking error 2.42%/yr · longer factor history 2.50%/yr · 36 months through 2026-08
Compare VFVA vs FNK
83
Factor-similar
XMVM
Invesco S&P MidCap Value with Momentum ETF
SMB HML Modeled factor tracking error 2.81%/yr · longer factor history 2.84%/yr · 36 months through 2026-08
Compare VFVA vs XMVM
81
Factor-similar
FXO
First Trust Financials AlphaDEX Fund
HML Modeled factor tracking error 2.87%/yr · longer factor history 2.93%/yr · 36 months through 2026-08
Compare VFVA vs FXO
80
Factor-similar
View full VFVA similarity cluster
All US Leaders US Universe Methodology

FAQ

What does this VFVA ETF page measure?

This page evaluates VFVA 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 match its stated strategy.

Research disclaimer

Factor decomposition shows what VFVA'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.