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Factor Investing: Building a Systematic Edge

Value, Momentum, Quality, Size, Low-Vol — the academic factors that work, and how to combine them.

#advanced #factor-investing
Factor Investing: Building a Systematic Edge

Factor investing is the empirical foundation of quantitative stock selection. Decades of research have identified persistent characteristics that predict higher returns.

The Big Five

  1. Value — Cheap stocks (low P/B, P/E, EV/EBITDA) outperform over time. Fama-French (1992). Premium is ~3–5% annually but comes with long droughts.
  2. Momentum — Stocks going up tend to keep going up (12-1 month return). Jegadeesh & Titman (1993). Strongest short-term predictor but crash-prone in regime shifts.
  3. Quality — Profitable companies with strong balance sheets outperform. Novy-Marx (2013) showed gross profitability predicts returns as well as value.
  4. Size — Small-caps outperform large-caps over very long horizons. The premium has weakened since publication — possibly arbitraged away.
  5. Low Volatility — Low-vol stocks deliver better risk-adjusted returns, defying CAPM. Persists because institutions chase high-beta for benchmark outperformance.

Why factors work

Risk-based: Premiums compensate for real risks (distress, slow information diffusion).

Behavioral: Investors systematically overpay for glamour, under-react to news, neglect boring compounders.

Our 5-pillar implementation

  • Quality pillar = Quality factor (ROIC, margins, balance sheet)
  • Growth pillar = Growth factor (revenue/EPS acceleration)
  • Valuation pillar = Value factor (P/E, EV/EBITDA, sector-relative)
  • Momentum pillar = Momentum factor (12-1 return, risk-adjusted)
  • Revisions pillar = Earnings revision factor (analyst estimate changes)

Weights are dynamically adjusted for sector context and macro regime — our edge over static factor ETFs.

The interaction effects

Cheap + improving momentum = deep value turning around (most profitable). Expensive + decelerating momentum = crowded growth unwinding (most dangerous). Our scorer captures these through pairwise pillar interaction terms.

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