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Covariance/Correlation Matrix HRP-Clustering

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 Marcos Lopez de Prado, Senior Managing Director at GUGGENHEIM PARTNERS

 Friday, June 10, 2016

Clustering a covariance or correlation matrix allows us to recognize hierarchical structures present in the data. Once clustered, that covariance matrix can be used to derive robust HRP portfolios that significantly outperform mean-variance (Markowitz) style or risk-parity solutions. This video shows how a large, numerically ill-conditioned covariance matrix of changes in yields for 1000+ bonds, becomes quasi-diagonal as the HRP-clustering proceeds. For additional details, please read/visit: * http://ssrn.com/abstract=2708678 * www.QuantResearch.org


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2 comments on article "Covariance/Correlation Matrix HRP-Clustering"

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 Guy R. Fleury, Independent Computer Software Professional

 Saturday, June 11, 2016



Great job, and most interesting. Thanks.


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 Guy Marcelis, Consultant, Investor, Entrepreneur

 Tuesday, June 14, 2016



Interesting, I thought you guys were past this stage since ages ... When did you start going along this route?

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