A further analysis of robust regression modeling and data mining corrections testing in global stocks

DOI10.1007/s10479-020-03521-yzbMath1477.62183OpenAlexW3005160853MaRDI QIDQ2241171

Ganlin Xu, Harry M. Markowitz, John B. jun. Guerard

Publication date: 8 November 2021

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-020-03521-y

zbMATH Keywords

testingportfolio optimizationdata miningI/B/E/S forecasts

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Ridge regression; shrinkage estimators (Lasso) (62J07) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (1)

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Uses Software

• robustbase
• ElemStatLearn
• RobStatTM

Cites Work

• Large Sample Properties of Generalized Method of Moments Estimators
• \(S\)-values: conventional context-minimal measures of the sturdiness of regression coefficients
• Global portfolio construction with emphasis on conflicting corporate strategies to maximize stockholder wealth
• The control of the false discovery rate in multiple testing under dependency.
• Least angle regression. (With discussion)
• Handbook of Portfolio Construction
• Introductory Econometrics
• Robust Statistics
• VIF Regression: A Fast Regression Algorithm for Large Data
• Robust Statistics
• The elements of statistical learning. Data mining, inference, and prediction
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