Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/316658 
Year of Publication: 
2024
Citation: 
[Journal:] Journal of Asset Management [ISSN:] 1479-179X [Volume:] 25 [Issue:] 2 [Publisher:] Palgrave Macmillan [Place:] London [Year:] 2024 [Pages:] 136-146
Publisher: 
Palgrave Macmillan, London
Abstract: 
This study presents network risk parity, a graph theory-based portfolio construction methodology that arises from a thoughtful critique of the clustering-based approach used by hierarchical risk parity. Advantages of network risk parity include: the ability to capture one-to-many relationships between securities, overcoming the one-to-one limitation; the capacity to leverage the mathematics of graph theory, which enables us, among other things, to demonstrate that the resulting portfolios is less concentrated than those obtained with mean-variance; and the ability to simplify the model specification by eliminating the dependency on the selection of a distance and linkage function. Performance-wise, due to a better representation of systematic risk within the minimum spanning tree, network risk parity outperforms hierarchical risk parity and other competing methods, especially as the number of portfolio constituents increases.
Subjects: 
Portfolio construction
Graph theory
Hierarchical clustering
Eigenvalues
JEL: 
G11
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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