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
13.6 years
2013-Feb → 2026-Sep
Long live record
Backtest Basis
63.2 years
1963-Jul → 2026-Aug
Full long-run factor record
Adj. R²
0.910
Strong model fit
AUM
US$0.2B
Emerging scale
MER
0.12%
Very low cost
Dividend valuation
117
Moderately rich
117
80 90 100 110 120+
2.39% Trailing 12-month yield
100 = median · below 100 inexpensive · above 100 rich Dividend valuation scale
Backtested Rel. Sharpe
1.36×
Decisive 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
+4.28%
Strong 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 SMLV Is

SMLV (State Street SPDR US Small Cap Low Volatility Index ETF) from SPDR is a US equity ETF with $0.2B in assets, regressed on the FF6 US over 162 months. The fund tilts toward size (smb) (β=0.79); tilts toward value (hml) (β=0.37); tilts toward profitability (rmw) (β=0.23). Backtested-simulation excess return is +9.51% annualized; the in-sample realized excess was +9.04%.

Why SMLV Ranks This Way

  • Backtested relative Sharpe is 1.36, above the market's 1.00 benchmark.
  • Realized relative Sharpe is 0.60 over the fund's 162-month live sample.
  • Strongest non-market tilts point toward size (smb) (β=0.79) and toward value (hml) (β=0.37).
  • Dividend valuation is 17% richer than its historical median (117 on the 100 scale).
Best-fit classification
US Equity FF6 US Regression basis: USD Adj. R² 0.910 Fit window: 162M 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 (162 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.
0.592
Rel. to market: 1.363
Sharpe — Realized
0.518
Rel. to market: 0.605
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 0.910.

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 SMLV'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 SMLV'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 SMLV's lifetime only (2013-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 +0.79
80th pct
t +15.0
Current fund: 80th 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 +0.37
86th pct
t +7.4
Current fund: 86th 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 +0.23
83rd pct
t +4.0
Current fund: 83rd 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 -0.04
rank n/a
t -0.6
Current fund: non-positive loading · 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 +0.08
58th pct
t +2.2
Current fund: 58th percentile of positive peers · Top decile begins at β +0.19 · Leader: MTUM
Factor exposures
Factor β t-stat Backtested % Realized %
Size (SMB) 0.791 15.05 +1.44% -1.58%
Value (HML) 0.369 7.42 +1.24% -0.30%
Profitability (RMW) 0.228 3.97 +0.67% +0.45%
Investment (CMA) -0.045 -0.62 -0.13% +0.04%
Momentum (UMD) 0.079 2.20 +0.56% +0.21%
Non-Market Factor Contribution · combined non-market series +3.88% -1.22%
Alpha (intercept) — 0.26 +0.39%
Smart-Beta Net · combined non-market series + alpha +4.28% -0.83%
+ Mkt-RF contribution · market 0.811 26.23 +5.18% +10.34%
= Total excess return +9.51% +9.04%
+ Rf base (%) 4.44% → 13.95% total 1.74% → 10.77% total
Fund snapshot
Issuer
SPDR
Asset class
Equity
Inception
2013-02-20
Trailing 12-month yield
2.39%
Div CAGR
2.66%
Dividend valuation
117 (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/SMLV/waterfall/" width="720" height="540" style="border:0;" loading="lazy"></iframe>

Matches share at least one verified factor exposure with SMLV. 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.

SMDV
SMB HML RMW Modeled factor tracking error 0.92%/yr · longer factor history 1.04%/yr · 36 months through 2026-08
Compare SMLV vs SMDV
93
Very close factor fit
DES
SMB HML RMW Modeled factor tracking error 1.09%/yr · longer factor history 1.14%/yr · 36 months through 2026-08
Compare SMLV vs DES
92
Very close factor fit
CSB
SMB HML RMW Modeled factor tracking error 2.37%/yr · longer factor history 2.22%/yr · 36 months through 2026-08
Compare SMLV vs CSB
84
Factor-similar
XSVM
SMB HML Modeled factor tracking error 2.17%/yr · longer factor history 2.51%/yr · 36 months through 2026-08
Compare SMLV vs XSVM
83
Factor-similar
View full SMLV similarity cluster
All US Leaders US Universe Methodology

FAQ

What does this SMLV ETF page measure?

This page evaluates SMLV 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 SMLV'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.