Equity Strategy · 6 min read · 2026-03-14
The 9 signals that a factor has decayed.
Smart-beta funds proliferated faster than the alpha they sold. Nine signals identify which factors still work and which have been priced out.
The factor that worked for 50 years may not work for the next 5.
The U.S. value premium produced -40% cumulative excess return over the 2007–2020 period, despite a 90-year history of positive premia. Factor decay is real. The screen identifies which factors carry capacity for continued alpha and which have been arbitraged away.
The nine indicators
The nine signals of factor capacity.
Each is a measurable property of the factor's structure or implementation. Together they describe whether the factor still earns its premium going forward.
Aggregate AUM in factor strategies
Threshold: as % of factor float
When AUM in the factor exceeds 5–10% of the factor-tilted segment, capacity constraints reduce alpha.
Factor-implementing fund expense ratios
Threshold: gross alpha vs. fee
Smart-beta ER of 30–50 bps consumes much of historical factor premium. Fee-after-tax math may eliminate the alpha entirely.
Factor crowding metric (positioning)
Source: hedge fund 13F
Hedge fund 13F filings reveal aggregate positioning. Crowded factors face position-unwind risk.
Alpha decay in academic re-tests
Pattern: out-of-sample fade
Factors showing weaker out-of-sample performance than in-sample (Harvey et al. literature) are decay candidates.
Factor-spread valuations vs. history
Threshold: own historical band
Wide value-growth spreads (cheap value, expensive growth) signal repressed premium poised for reversal. Narrow spreads suggest factor exhausted.
Implementation friction (turnover, taxes)
Threshold: paper alpha vs. net
Factors with high turnover (momentum) lose 50–150 bps to taxes and trading costs. Net alpha post-implementation can be near zero.
Structural changes in the factor mechanism
Pattern: changing fundamentals
If the underlying mechanism producing the factor has structurally changed (intangibles for value, for example), the factor may be redefined or extinct.
Factor correlation breakdown with related factors
Pattern: low correlation = pure
Factors with low correlation to other factors are clean exposures. High correlation suggests overlap and reduced diversification benefit.
Tax efficiency of factor exposure
Pattern: ETF vs mutual fund
Same factor in ETF form is tax-advantaged versus mutual fund form. Implementation choice affects net result by 30–60 bps annually.
Factors are not laws of physics
Equity factors — value, momentum, quality, size, low volatility — were identified through historical data analysis. Their persistence varies. Some (value) have been documented for nearly a century; others (low volatility, profitability) emerged in the 1990s–2000s. The premium associated with each factor exists because it captures either a risk that investors avoid or a behavioral mispricing that arbitrageurs cannot fully eliminate.
Both bases for premium are vulnerable to decay. Risks can become priced; mispricings can be arbitraged away. The discipline is to assess each factor's continuing capacity for premium delivery rather than assume historical patterns persist.
The value factor's lost decade
The U.S. value premium underperformed growth by approximately 40 percentage points cumulatively from 2007 through 2020. The traditional metrics that defined value (price-to-book, price-to-earnings) failed to capture the rising importance of intangible assets — software, brands, customer relationships — that distinguish value-disguised-as-growth from genuine value.
The 2020–2024 partial recovery in value vindicated the factor's continued existence but at a fraction of historical premium. The lesson: factors operate in regimes, and capacity decays in some regimes more than others. The screen distinguishes structural decay from temporary regime shift.
Crowding versus arbitrage
Factor crowding refers to the concentration of capital in factor-tilted strategies. When too much capital chases a factor, the prices of factor-fitting securities are bid up, the discount that produced the factor narrows, and the future premium compresses. Crowding is observable in 13F filings, ETF AUM, and sentiment metrics.
The mirror image is the entry opportunity. Factors whose AUM has declined (as some hedge funds and smart-beta ETFs have closed) often see widening spreads and renewed premium delivery. Capacity in factor strategies cycles.
Implementation matters more than the factor
Many smart-beta ETFs deliver less factor exposure than they advertise. Index construction methodology, rebalancing frequency, and capacity-management decisions all affect actual factor capture. The same factor name implemented by AQR, DFA, or iShares can produce different return streams.
The discipline is to evaluate the implementation: factor purity (correlation to research-pure factor returns), turnover (transaction-cost drag), expense ratio, and tax efficiency. The implementation can absorb 30–60 percent of the gross factor premium before the holder receives anything.
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Common questions
Questions.
Are factors dead?
Some are decayed (small-size as historically defined), some are in regime cycles (value), some appear durable (momentum, quality). The aggregate factor universe still produces some premium; the implementation is the bottleneck.
Should I avoid factor investing?
Not necessarily. Quality and low-volatility factors have continued to deliver in recent decades. Disciplined factor investing with attention to capacity and implementation still has value.
What about multi-factor funds?
Diversifying across factors reduces single-factor regime risk. Funds like AQR Style Premia or Dimensional's multi-factor strategies provide structured exposure with rebalancing across factors.
Is momentum still working?
Yes, but with significant noise. Momentum factor returns have remained positive but volatile. Implementation costs are high; net post-cost returns are smaller.
Does the size factor work?
Mixed evidence. Pure size (small minus big) has produced negative returns over recent decades; size combined with quality screens (avoiding junk small-caps) still produces premium.
How do I monitor factor performance?
AQR, Dimensional, and Research Affiliates publish factor data publicly. Bloomberg and Factset have factor analytics for subscribers. Quarterly review of factor spreads is sufficient for retail.
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