Paper Library

A curated collection of papers from Systematically Biased

This post will maintain a growing library of slide decks based on academic papers discussed on Systematically Biased. These are designed for researchers, instructors, students, and practitioners who want a quick way to understand what the paper is about.

The materials are intended for personal study, teaching preparation, and research discussion. Please do not redistribute the files publicly.

Each slide deck is an independent educational summary. It is not affiliated with or endorsed by the original paper authors.

When using these materials, please cite the original paper where appropriate.

The list is sorted in the order in which the papers were added, with the most recently added papers on top.

Click on the paper title to access the paper. Click on the image to access the slide deck.

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DeMiguel et al. - Optimal Versus Naive Diversification

• Title: Optimal Versus Naive Diversification: How Inefficient is the 1/N Portfolio Strategy?

• Authors: Victor DeMiguel; Lorenzo Garlappi; Raman Uppal

• Publication: Review of Financial Studies

• Year: 2009

• Volume: 22

• Issue: 5

• Pages: 1915-1953

• DOI: 10.1093/rfs/hhm075

• Document type: Published journal article

• Main field: Portfolio choice; empirical asset allocation; estimation error

• The paper in one sentence: The paper shows that many optimized portfolio rules fail to beat 1/N out of sample because estimation error overwhelms the theoretical gains from optimization.

• Tags: 1/N portfolio, naive diversification, mean-variance optimization, estimation error, Sharpe ratio, certainty equivalent, turnover, portfolio constraints, minimum variance, out-of-sample tests

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Benveniste et al. - Untangling Universality and Dispelling Myths in MVO

• Title: Untangling Universality and Dispelling Myths in Mean-Variance Optimization

• Authors: Jerome Benveniste; Petter N. Kolm; Gordon Ritter

• Publication: Journal of Portfolio Management, special issue dedicated to Harry Markowitz

• Document type: Published journal article

• Main field: Portfolio theory; mean-variance optimization; expected utility

• The paper in one sentence: The paper argues that MVO is much broader than Gaussian/quadratic-utility folklore, characterizes distributions where expected-utility and MVO optima coincide, and reframes common MVO criticisms as input and implementation problems.

• Tags: mean-variance optimization, expected utility, mean-variance equivalence, elliptical distributions, asymmetric returns, factor risk models, sample covariance, 1/N portfolio, mean-quadratic variation

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Kolm et al. - 60 Years of Portfolio Optimization

• Title: 60 Years of Portfolio Optimization: Practical Challenges and Current Trends

• Authors: Petter N. Kolm; Reha Tutuncu; Frank J. Fabozzi

• Publication: European Journal of Operational Research

• Year: 2014

• Volume: 234

• Pages: 356-371

• DOI: 10.1016/j.ejor.2013.10.060

• Document type: Published journal article / survey

• Main field: Portfolio optimization; quantitative asset management

• The paper in one sentence: A practitioner map of how to make Markowitz optimization usable by adding costs, constraints, robust inputs, alpha structure, and dynamic rebalancing

• Tags: mean-variance optimization, portfolio construction, transaction costs, constraints, estimation error, Black-Litterman, robust optimization, risk parity, multi-period optimization.

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Zhang and Zhou - Large Language Models for Asset Pricing

• Title: Large Language Models for Asset Pricing: Learning from Earnings Calls

• Authors: Yizhong Zhang; Guofu Zhou

• Date: 2026-05

• Document type: Working paper / draft

• Main field: Empirical asset pricing; machine learning; textual analysis

• The paper in one sentence: The paper uses point-in-time LLM embeddings of earnings calls to isolate a text-explained announcement-return signal, EARAI, that predicts future fundamentals and delivers strong long-short returns.

• Tags: large language models, ChronoGPT, earnings calls, text embeddings, EARAI, post-earnings announcement drift, analyst expectations, characteristics, asset pricing.

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