Reference Library

Plain-language, one-page summaries of every academic paper that grounds this research programme and the SBFoundation platform — factor research, transaction-cost, survivorship, risk-model, and lifecycle-gate design, plus the networks / graph-neural-network literature behind the systemic-risk thesis. Each entry links the paper’s canonical source; the PDFs themselves are not redistributed.

Networks & Graph Neural Networks (PhD proposal)

  • Pathways towards instability in financial networkssource — Bardoscia, Battiston, Caccioli & Caldarelli (2017)
  • The structure and dynamics of multilayer networkssource — Boccaletti et al. (2014)
  • Semi-Supervised Classification with Graph Convolutional Networkssource — Kipf & Welling (2016/2017)
  • Multilayer Networkssource — Kivelä et al. (2014)
  • Relation between Financial Market Structure and the Real Economy: Comparison between Clustering Methodssource — Musmeci, Aste & Di Matteo (2015)
  • Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecastingsource — Yu, Yin & Zhu (2017/2018)

Platform Reference Library

Multiple testing, overfitting & significance

  • … and the Cross-Section of Expected Returnssource — Harvey, Liu & Zhu (2016)
  • The Deflated Sharpe Ratio: Correcting for Selection Bias, Backtest Overfitting and Non-Normalitysource — Bailey & López de Prado (2014)
  • The Probability of Backtest Overfittingsource — Bailey, Borwein, López de Prado & Zhu (2014)
  • The Control of the False Discovery Rate in Multiple Testing under Dependencysource — Benjamini & Yekutieli (2001)
  • False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significantsource — Simmons, Nelson & Simonsohn (2011)
  • The Garden of Forking Paths: Why Multiple Comparisons Can Be a Problem, Even When There Is No “Fishing Expedition” or “p-hacking” and the Research Hypothesis Was Posited Ahead of Timesource — Gelman & Loken (2013)
  • Leakage and the Reproducibility Crisis in ML-based Sciencesource — Kapoor & Narayanan (2023)
  • The Sharpe Ratio Efficient Frontiersource — Bailey & López de Prado (2012)

Anomaly replication, the factor zoo, universe & decay

  • Replicating Anomaliessource — Hou, Xue & Zhang (2020)
  • A Taxonomy of Anomalies and Their Trading Costssource — Novy-Marx & Velikov (2016)
  • Understanding Defensive Equitysource — Novy-Marx (2014)
  • Zeroing In on the Expected Returns of Anomaliessource — Chen & Velikov (2023)
  • Navigating the Factor Zoo around the World: An Institutional Investor Perspectivesource — Bartram et al. (2021)
  • Taming the Factor Zoo: A Test of New Factorssource — Feng, Giglio & Xiu (2020)
  • Does Academic Research Destroy Stock Return Predictability?source — McLean & Pontiff (2016)
  • Monotonicity in Asset Returns: New Tests with Applications to the Term Structure, the CAPM, and Portfolio Sortssource — Patton & Timmermann (2010)
  • Anomalies across the Globe: Once Public, No Longer Existent?source — Jacobs & Müller (2020)

Transaction-cost estimation & implementation

  • A Simple Way to Estimate Bid-Ask Spreads from Daily High and Low Pricessource — Corwin & Schultz (2012)
  • A Simple Estimation of Bid-Ask Spreads from Daily Close, High, and Low Pricessource — Abdi & Ranaldo (2017)
  • Trading Costs of Asset Pricing Anomaliessource — Frazzini, Israel & Moskowitz (2015)
  • Optimal Execution of Portfolio Transactionssource — Almgren & Chriss (2000)
  • Direct Estimation of Equity Market Impactsource — Almgren et al. (2005)
  • Dynamic Trading with Predictable Returns and Transaction Costssource — Gârleanu & Pedersen (2013)
  • Anomalies and Their Short Sale Costssource — Muravyev, Pearson & Pollet (2025)

Crowding, unwinds & factor crashes

  • What Happened to the Quants in August 2007? Evidence from Factors and Transactions Datasource — Khandani & Lo (2007)
  • Momentum Crashessource — Daniel & Moskowitz (2016)
  • How Can “Smart Beta” Go Horribly Wrong?source — Arnott, Beck, Kalesnik & West (2016)
  • Comomentum: Inferring Arbitrage Activity from Return Correlationssource — Lou & Polk (2012)
  • Contrarian Factor Timing is Deceptively Difficultsource — Asness et al. (2017)
  • The Siren Song of Factor Timing (aka “Smart Beta Timing” aka “Style Timing”)source — Asness (2016)

Portfolio construction, risk model & attribution

  • Improved Estimation of the Covariance Matrix of Stock Returns with an Application to Portfolio Selection — [source](https://doi.org/10.1016/S0927-5398(03) — Ledoit & Wolf (2003)
  • Honey, I Shrunk the Sample Covariance Matrixsource — Ledoit & Wolf (2004)
  • The Intuition Behind Black-Litterman Model Portfoliossource — He & Litterman (1999)

Survivorship & delisting bias

  • The Delisting Bias in CRSP Datasource — Shumway (1997)
  • The Delisting Bias in CRSP’s Nasdaq Data and Its Implications for the Size Effectsource — Shumway & Warther (1999)
  • Survivorship Bias in Performance Studiessource — Brown et al. (1992)
  • Mutual Fund Survivorshipsource — Carhart, Carpenter, Lynch & Musto (2002)

Scheduling & control theory (lifecycle-state design)

  • Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environmentsource — Liu & Layland (1973)
  • A Proof for the Queuing Formula: L = λWsource — Little (1961)
  • Control Chart Tests Based on Geometric Moving Averagessource — Roberts (1959)

Seasonality & calendar anomalies

  • Seasonality in the Cross-Section of Stock Returnssource — Heston & Sadka (2008)
  • Mood Betas and Seasonalities in Stock Returnssource — Hirshleifer, Jiang & Meng (2020)

Momentum, value & factor-model foundations (wiki strategy/foundation pages)

  • Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiencysource — Jegadeesh & Titman (1993)
  • Residual Momentumsource — Blitz, Huij & Martens (2011)
  • Volatility-Managed Portfoliossource — Moreira & Muir (2017)
  • Momentum Has Its Momentssource — Barroso & Santa-Clara (2015)
  • Factor Momentum and the Momentum Factorsource — Ehsani & Linnainmaa (2022)
  • The Other Side of Value: The Gross Profitability Premiumsource — Novy-Marx (2013)
  • Betting Against Betasource — Frazzini & Pedersen (2014)
  • Fads, Martingales, and Market Efficiencysource — Lehmann (1990)
  • Simple Technical Trading Rules and the Stochastic Properties of Stock Returnssource — Brock, Lakonishok & LeBaron (1992)
  • Common Risk Factors in the Returns on Stocks and Bonds — [source](https://doi.org/10.1016/0304-405X(93) — Fama & French (1993)
  • Time Series Momentumsource — Moskowitz, Ooi & Pedersen (2012)

Portfolio construction & diversification (wiki strategy pages)

  • Optimal Versus Naive Diversification: How Inefficient is the 1/N Portfolio Strategy?source — DeMiguel, Garlappi & Uppal (2009)
  • Building Diversified Portfolios that Outperform Out of Sample (Hierarchical Risk Parity)source — López de Prado (2016)

Strategy-specific, thematic & AI (wiki strategy/architecture pages)

  • Beyond the Status Quo: A Critical Assessment of Lifecycle Investment Advicesource — Anarkulova et al. (2025)
  • The Alchemy of Multibagger Stocks: An Empirical Investigation of Factors that Drive Outperformance in the Stock Marketsource — Yartseva (2025)
  • ChatGPT-based Investment Portfolio Selectionsource — Romanko et al. (2023)
  • The Mosaic Permutation Test: An Exact and Nonparametric Goodness-of-Fit Test for Factor Modelssource — Spector et al. (2024)
  • Empirical Asset Pricing via Machine Learningsource — Gu, Kelly & Xiu (2020)

Diagnostics, attribution & multi-asset mechanics (wiki gap-fill pages, 2026-07-10)

  • Carrysource — Koijen, Moskowitz, Pedersen & Vrugt (2018)
  • A Century of Evidence on Trend-Following Investingsource — Hurst, Ooi & Pedersen (2017)

Event-driven capture — PEAD, index reconstitution, analyst revisions (wiki doc-063, 2026-07-10)

  • Do Demand Curves for Stocks Slope Down?source — Shleifer (1986)
  • Momentum Strategiessource — Chan, Jegadeesh & Lakonishok (1996)