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Factor-adjusted alpha is the return you generated that cannot be explained by known investment factors like market, value, size, or momentum. It isolates genuine stock-picking skill from factor exposures.

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Beginner

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What It Means

Regular alpha can be misleading - a “value fund” might show high alpha just from value stock exposure, not manager skill. Factor-adjusted alpha removes all known factor effects to reveal true skill.

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Portfolio Example

  • Your portfolio returned 16% this year
  • S&P 500 returned 10% (6% apparent excess return)
  • But your portfolio has heavy value exposure, and value beat growth by 4%
  • Factor-Adjusted Alpha = 16% - (10% market + 4% value) = 2%
Your real skill added 2%, not the apparent 6%.

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Why It Matters

Factor-adjusted alpha reveals whether a manager has genuine stock-picking ability or is simply riding factor exposures that could be obtained cheaply through factor ETFs.

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Advanced

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Mathematical Definition

Factor-Adjusted Alpha (α) = Rp - [Rf + Σ(βi × Fi)]

Fama-French Five-Factor Model:
α = Rp - [Rf + βM(RM-Rf) + βSMB×SMB + βHML×HML + βRMW×RMW + βCMA×CMA]

Where:
- RM-Rf = Market risk premium
- SMB = Small Minus Big (size)
- HML = High Minus Low (value)
- RMW = Robust Minus Weak (profitability)
- CMA = Conservative Minus Aggressive (investment)

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Comparison Example

Two portfolios both returned 15% vs. market’s 10%:
PortfolioJensen’s AlphaFactor ExposuresFama-French Alpha
Value Fund5%High value, high size1.5%
Stock Picker5%Neutral all factors4.8%
The Stock Picker has genuine skill; the Value Fund mostly rode factor exposures.

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Common Factor Models

ModelFactorsUse Case
CAPMMarketBasic alpha
Fama-French 3Market, Size, ValueTraditional
Carhart 4+ MomentumInclude trends
Fama-French 5+ Profitability, InvestmentCurrent standard
CustomIndustry-specific factorsSpecialized analysis

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Historical Context

Eugene Fama and Kenneth French (1993) developed the three-factor model showing that size and value explain returns beyond market beta. They expanded to five factors in 2015. This revolutionized how we evaluate active management.

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What It Reveals

FindingImplication
High factor-adjusted alphaGenuine skill, justifies fees
Low factor-adjusted alphaFactor exposure, not skill
Negative factor-adjusted alphaDestroying value vs. factors

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Data Requirements

RequirementDetails
Minimum36 months for basic estimate
Preferred60+ months for stable estimates
Factor DataNeed factor portfolio returns
Statistical Testt-statistic should exceed 2.0
Factor loadings (betas) are time-varying. Use rolling estimation and be cautious about conclusions from short periods.

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Limitations

LimitationDescription
Model DependencyDifferent factor models give different alphas
Missing FactorsIf true factors not in model, alpha still contaminated
Data IntensiveRequires factor return data and regression
Time-VaryingFactor exposures change over time

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Modern Extensions

Beyond Fama-French, sophisticated analysis includes:
  • Betting Against Beta (BAB): Low-beta stock premium
  • Quality Minus Junk (QMJ): Quality factor
  • Liquidity Factor: Compensation for illiquidity
  • Momentum: Trend persistence
Managers are now evaluated against 8-10 factor models.

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Related Terms

Alpha

Basic excess return measure

Factor Investing

The factors being adjusted for

Style Analysis R-Squared

Related analysis technique