USVM — VictoryShares US Small Mid Cap Value Momentum ETF factor decomposition

Factor return decomposition

Each bar = β_i × factor return, geometrically annualized.

Sharpe — Backtested Sim.

0.463

Rel. to market: 1.042

Sharpe — Realized

0.365

Rel. to market: 0.546

How are these computed?

Currency basis: returns and factor contributions on this page are in USD. Fama-French (Ken French data library, 1964→present)

Backtested Sim. applies USVM's regression betas to the full factor history (geometric mean per factor, annualized). The Sharpe uses USVM'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 USVM's lifetime only (2017-Nov → 2026-Feb). The Sharpe is the fund's actual excess return over its actual volatility. Full methodology →

Factor exposures

Factor	β	t-stat	Backtested %	Realized %
Size (SMB)	0.769	15.47	+1.38%	-2.47%
Value (HML)	0.213	4.96	+0.73%	-0.22%
Profitability (RMW)	0.148	2.59	+0.47%	+0.62%
Investment (CMA)	-0.012	-0.20	-0.04%	-0.01%
Momentum (UMD)	0.144	4.12	+1.01%	+0.34%
Factor-Beta subtotal · non-market			+3.56%	-1.73%
Alpha (intercept)	—	-0.76	-1.17%
Smart-Beta Net · Factor-Beta + Alpha			+2.39%	-2.89%
+ Mkt-RF contribution · market	0.979	36.66	+5.96%	+11.01%
= Total excess return			+8.35%	+7.49%
+ Rf base (%)			4.44% → 12.80% total	2.50% → 10.00% total

Fund snapshot

Issuer

Victory Capital

Asset class

Equity

Inception

2017-10-24

Dividend yield

1.66%

Div CAGR

14.03%

Dividend valuation

93 (100=median)

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All US Leaders US Universe Methodology

Research disclaimer

Factor decomposition shows what USVM'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.

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