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Factor investing systematically targets specific stock characteristics (factors) that academic research has shown to predict higher returns over time. It’s the bridge between passive indexing and traditional active management.

Beginner

What It Means

Instead of picking individual stocks based on hunches, factor investing builds portfolios around proven characteristics that have historically led to better returns. Think of factors as “ingredients” that explain why some stocks outperform.

The Main Factors

FactorWhat It TargetsSimple Explanation
ValueCheap stocksBuy stocks trading below their worth
MomentumTrending stocksBuy recent winners, avoid recent losers
QualityStrong companiesBuy profitable, stable businesses
SizeSmaller companiesSmall caps tend to outperform large caps
Low VolatilityStable stocksLess risky stocks often beat expectations

Portfolio Example

Instead of picking individual stocks, you build a portfolio emphasizing companies that are:
  • Undervalued relative to fundamentals (value)
  • Rising in price with positive momentum (momentum)
  • Highly profitable with strong balance sheets (quality)

Why It Matters

Factor investing provides a middle ground: more systematic than stock picking, but with potential to beat the market unlike pure indexing. Decades of research support these factors across markets and time periods.

Advanced

Academic Foundation

Factor investing emerged from academic research showing that the market (beta) alone doesn’t explain all returns:
ModelYearFactors
CAPM1964Market
Fama-French 3-Factor1993Market, Size, Value
Carhart 4-Factor1997+ Momentum
Fama-French 5-Factor2015+ Profitability, Investment

Why Factors May Work

Each factor has economic rationale for its premium:
FactorRisk-Based ExplanationBehavioral Explanation
ValueDistress risk, leverageOverreaction to bad news
MomentumCrash risk, tail riskUnderreaction, herding
QualityLower returns in recessions?Neglect, complexity
SizeIlliquidity, distress riskLess analyst coverage
Low VolLeverage constraintsLottery preferences

Historical Premiums

Long-term annualized premiums (US equities, approximate):
FactorPremiumTime Period
Market (Equity Risk Premium)5-7%1926-present
Value (HML)3-4%1926-present
Size (SMB)2-3%1926-present
Momentum (UMD)6-8%1927-present
Quality/Profitability3-4%1963-present
Past premiums don’t guarantee future results. Value underperformed significantly 2010-2020. Factors can have long periods of poor performance.

Implementation Approaches

ApproachDescriptionTrade-offs
Single-FactorTilt toward one factorConcentrated, high tracking error
Multi-FactorCombine several factorsDiversified, lower tracking error
Factor TimingRotate based on conditionsDifficult to execute, may add value
IntegratedScore stocks on all factors togetherMost efficient, complex

Factor Cyclicality

Factors don’t always work. Historical drawdowns:
FactorWorst DrawdownDuration
Value-60% (vs. growth)2007-2020
Momentum-50%2009 (2 months)
Size-40%1984-1990
Factor diversification helps. When value struggles, momentum often works, and vice versa. Multi-factor approaches smooth returns.

Data Requirements

RequirementDetails
Backtest period20+ years minimum (full market cycles)
Out-of-sampleTest on different markets/time periods
Transaction costsMust account for turnover costs
CapacitySome factors don’t scale to large AUM

Limitations

  • Crowding: As factors become popular, premiums may shrink
  • Implementation Costs: Turnover, especially for momentum, erodes returns
  • Factor Timing: Extremely difficult to time factor rotations
  • Drawdowns: Long periods of underperformance test investor patience
  • Data Mining: Some “factors” are statistical artifacts

Parallax Approach

Parallax combines multiple factors in an integrated framework:
  • Value, Quality, Momentum, Defensive factors
  • Factor scores combined at stock level
  • Risk management overlay
  • Sector and position constraints