Journal of Investment Strategies
ISSN:
2047-1238 (print)
2047-1246 (online)
Editor-in-chief: Ali Hirsa
Need to know
- The authors introduce a robust, risk-based optimization approach to create truly diversified allocations.
- The methodology focuses on the risk contribution of clusters of assets to the overall portfolio.
- The framework allows to design solutions that are aligned with clients' needs and targets.
- The approach could be leveraged to create cross asset risk factor or smart beta strategies.
Abstract
In this paper, we introduce a robust, risk-based optimization routine to create allocations that are truly diversified, with less extreme weights and risk allocations, as well as a higher number of uncorrelated exposures. The framework allows us to design, build and analyze solutions that are aligned with clients’ specific investment needs and their desired risk profile. We combine simple yet profound elements of graph theory and machine learning with more traditional optimization methods to build a diversified portfolio based on the information contained in the correlation matrix.
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