Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/337245 
Year of Publication: 
2022
Citation: 
[Journal:] Journal of Derivatives and Quantitative Studies: Seonmul yeon'gu (JDQS) [ISSN:] 2713-6647 [Volume:] 30 [Issue:] 2 [Year:] 2022 [Pages:] 114-124
Publisher: 
Emerald, Leeds
Abstract: 
Risk parity, also known as equal risk contribution, has recently gained increasing attention as a portfolio allocation method. However, solving portfolio weights must resort to numerical methods as the analytic solution is not available. This study improves two existing iterative methods: the cyclical coordinate descent (CCD) and Newton methods. The authors enhance the CCD method by simplifying the formulation using a correlation matrix and imposing an additional rescaling step. The authors also suggest an improved initial guess inspired by the CCD method for the Newton method. Numerical experiments show that the improved CCD method performs the best and is approximately three times faster than the original CCD method, saving more than 40% of the iterations.
Subjects: 
Risk parity
Equal risk contribution
Cyclical coordinate descent
Newton method
JEL: 
G10
G13
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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