Concepts
- market-beta — sensitivity to overall market return; sole predictor in CAPM, empirically flat
- value — high book-to-market stocks earn higher returns (HML factor)
- size — small-cap stocks earn higher returns (SMB factor)
- momentum — past winners continue to outperform over 3-12 months (UMD/WML factor)
- profitability — profitable firms earn higher returns despite higher valuations (RMW, gross profitability)
- investment — conservative (low asset growth) firms earn higher returns (CMA factor)
- quality — composite of profitability, growth, and safety (QMJ factor)
- residual-volatility — high-vol stocks earn low returns; -1.06%/mo quintile spread (Ang et al. 2006, 2009)
- long-term-reversal — 3-5 year losers outperform winners by ~25%; overreaction (DeBondt and Thaler 1985)
- liquidity — illiquidity premium (Amihud 2002) and liquidity risk factor, 7.5%/yr spread (Pastor-Stambaugh 2003)
- dividend-yield — dividend-to-price ratio; related to value but distinct risk profile
- betting-against-beta — leveraged low-beta long / high-beta short; leverage constraint theory (Frazzini & Pedersen 2014)
- short-term-reversal — past-week/month losers outperform winners; microstructure/liquidity provision effect
- country-factors — systematic return component from geographic domicile; binary vs. beta-based vs. revenue-based construction
- industry-factors — systematic return component from sector/industry membership; binary vs. beta-based vs. multi-industry construction
Models
- arbitrage-pricing-theory — multi-factor no-arbitrage pricing (Ross 1976); theoretical foundation for all multi-factor models
- capm — single-factor model: expected returns proportional to market beta (Sharpe 1964)
- fama-french-three-factor — market + size + value (Fama and French 1993)
- carhart-four-factor — FF3 + momentum (Carhart 1997)
- fama-french-five-factor — FF3 + profitability + investment; HML becomes redundant (Fama and French 2015)
- q-factor-model — investment-based 4-factor model: MKT + size + investment + ROE (Hou, Xue & Zhang 2015)
- mispricing-factors — behavioral 4-factor model: MKT + size + MGMT + PERF mispricing factors (Stambaugh & Yuan 2017)
- msci-barra-gem — MSCI Barra GEM family: GEM2 → GEM3 → GEMLT → next-gen (2022, adds Crowding/ML/ESG)
- mac3-global-equity-risk-model — Bloomberg commercial risk model with 14 style factors (holdings-based)
- two-sigma-factor-lens — Two Sigma Venn; 18-factor multi-asset return-based model for manager evaluation
- liquid-factor-models — Rosenthal 2024; 10 factors from tradeable instruments for hedging overlays
Entities
- stephen-ross — University of Pennsylvania/MIT; developed the Arbitrage Pricing Theory (1976)
- eugene-fama — University of Chicago; co-developer of FF3, FF5; Fama-MacBeth regression; Nobel 2013
- kenneth-french — Dartmouth; co-developer of FF3, FF5; maintains French Data Library
- william-sharpe — Stanford; developed CAPM; Nobel 1990
- clifford-asness — AQR co-founder; value-momentum interaction, QMJ, size/quality, value-rate debate
- andrea-frazzini — AQR principal; Betting Against Beta, timely value, QMJ, trading costs
- lasse-pedersen — NYU/CBS/AQR; leverage constraints, BAB, market microstructure, QMJ
- robert-arnott — Research Affiliates chairman; fundamental indexation, value premium analysis
- campbell-harvey — Duke University; factor reliability, value death analysis
- aqr-capital-management — quantitative asset manager bridging academic research and practice
- bloomberg — MAC3 risk model provider
- jose-menchero — Bloomberg; architect of MAC3 and Barra GEM2; risk attribution, covariance estimation
- msci — factor index and risk model provider (Barra GEM family, MSCI Factor Indexes)
- invesco — global asset manager; factor investing as “third pillar” framework
Evidence
- value-momentum-interaction — negative correlation (~-0.6), combination Sharpe ratio 1.42, drawdown reduction
- return-based-vs-holdings-based-models — return-based (inferred from returns) vs. holdings-based (from characteristics)
- lag-in-return-based-models — style drift detection lag and cross-market asynchronous trading lag
- migration — how stock migration across portfolios generates size and value premia (Fama & French 2007)
- size-effect-debate — mechanical critique, quality adjustment, declining migration, structural VC thesis
- factor-investing-pitfalls — three blunders: data mining/factor zoo, valuation adjustment, trading costs (Arnott et al. 2019)
- investor-factor-sophistication — mutual fund investors mostly use CAPM; returns from size, value, momentum treated as alpha (Barber et al. 2016)
- factor-investing-overview — definitions, criteria, canonical factors, cyclicality, long/short vs. long-only (Invesco, MSCI, Cazalet & Roncalli)
- smart-beta-disruption — smart beta as disruptive innovation; common vs. stock-specific alpha (Kahn & Lemmon 2016)
- factor-zoo — 316 published factors; multiple testing framework requires t > 3.0 for new discoveries (Harvey, Liu & Zhu 2016)
- characteristics-vs-covariances — characteristics, not factor loadings, drive cross-sectional returns (Daniel & Titman 1997)
- behavioral-explanations-value — value premium from investor extrapolation bias, not risk (LSV 1994)
- fama-macbeth-regression — foundational two-pass cross-sectional regression methodology (Fama & MacBeth 1973)
- factor-trading-costs — real-world costs ~1/10 of academic estimates; anomalies are implementable (Frazzini, Israel & Moskowitz 2015)
- factor-timing — contrarian timing is deceptively difficult vs. buy-low-sell-high for smart beta (Asness et al. 2017; Arnott et al. 2016)
- international-factor-evidence — value, momentum, profitability, investment across 4 global regions (Fama & French 2012, 2017)
- country-vs-industry-effects — variance decomposition of global returns into country and industry components; European convergence and re-divergence