Open AccessMatrix Evolutions: Synthetic Correlations and Explainable Machine Learning for Constructing Robust Investment Portfolios
Author(s) -
Jochen Papenbrock,
Peter Schwendner,
Markus Jaeger,
Stephan Krügel
Publication year - 2021
Publication title -
the journal of financial data science
Language(s) - English
Resource type - Journals
eISSN - 2640-3951
pISSN - 2640-3943
DOI - 10.3905/jfds.2021.1.056
Subject(s) - computer science , portfolio , portfolio optimization , stylized fact , covariance matrix , futures contract , machine learning , volatility (finance) , asset allocation , artificial intelligence , econometrics , mathematical optimization , algorithm , finance , economics , mathematics , macroeconomics
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