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Honey, I Shrunk the Sample Covariance Matrix

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Outgoing claims: the papers this work cites, builds on, or argues with.

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A well-conditioned estimator for large-dimensional covariance matrices
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Improved estimation of the covariance matrix of stock returns with an application to portfolio selection
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Stein's Paradox in Statistics
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Estimation for Markowitz Efficient Portfolios
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Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps
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PORTFOLIO SELECTION*
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A Test for the Number of Factors in an Approximate Factor Model
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A Simplified Model for Portfolio Analysis
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INADMISSIBILITY OF THE USUAL ESTIMATOR FOR THE MEAN OF A MULTIVARIATE NORMAL DISTRIBUTION
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Bayes-Stein Estimation for Portfolio Analysis
inferredcites →https://doi.org/10.2307/2331043openalex-snapshot
An Empirical Bayes Approach to Efficient Portfolio Selection
inferredcites →https://doi.org/10.2307/2975974openalex-snapshot
Portfolio Selection
inferredcites →https://doi.org/10.2469/faj.v45.n1.31openalex-snapshot
The Markowitz Optimization Enigma: Is ‘Optimized’ Optimal?
inferredcites →https://doi.org/10.2469/faj.v51.n3.1904openalex-snapshot
The Three Types of Factor Models: A Comparison of Their Explanatory Power
inferredcites →https://doi.org/10.2469/faj.v58.n5.2468openalex-snapshot
Portfolio Constraints and the Fundamental Law of Active Management
inferredcites →https://doi.org/10.3386/w8922openalex-snapshot
Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps
inferredcites →https://doi.org/10.3905/jpm.1992.701922openalex-snapshot
A Mean/Variance Analysis of Tracking Error
inferredcites →https://doi.org/10.3905/jpm.1994.68openalex-snapshot
EAFE is for Wimps

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Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Risk Parity Portfolio Optimization under Heavy-Tailed Returns and Time-Varying Volatility
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Robust Portfolio Allocation with Systematic Risk Contribution Restrictions11The authors gratefully acknowledge financial support of the chair QuantValley/Risk Foundation “Quantitative Management Initiative”. The second author gratefully acknowledges financial support of NSERC Canada.
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Factor Investing: The Rocky Road from Long-Only to Long-Short * *The authors are grateful to Sohnke Bartram, Nicolas Fragneau, Emmanuel Jurczenko, Bruce Phelps, Simon Polbennikov, Thierry Roncalli, Bruno Taillardat, Paolo Sodini and Mihail Velikov for suggestions and discussions.
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Urban pluvial flooding prediction by machine learning approaches – a case study of Shenzhen city, China
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There is no silver bullet: The value of diversification in planning invasive species surveillance
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Beating the market with small portfolios: Evidence from Brazil
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Evaluating the three-cornered hat method for hourly satellite precipitation fusion in hydrological forecasting: A case study in a Tropical Andean Basin
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The Cross-Section of Emerging Market Stock Returns
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Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market
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Factor investing in Brazil: Diversifying across factor tilts and allocation strategies
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Portfolio allocation with the TODIM method
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Robo-advisor using genetic algorithm and BERT sentiments from tweets for hybrid portfolio optimisation
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Company classification using machine learning
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Dynamic portfolio optimization with inverse covariance clustering
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How should individual investors diversify? An empirical evaluation of alternative asset allocation policies
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A multivariate extension to the standard 4σ criterion for comparison of forensic glass evidence
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Estimation error in the average correlation of security returns and shrinkage estimation of covariance and correlation matrices
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A parametric bootstrap to evaluate portfolio allocation models
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