Offers a set of functions for the design of portfolios using hierarchical clustering, such as Lopez de Prado's (2015) hierarchical risk parity (HRP) method, as well as the hierarchical equal risk contribution (HERC) method proposed by Raffinot (2018). In addition, we provide some extensions the original methods, such as: divisive clustering, a tuning parameter for HRP and HERC, alternative risk measures (such as expected shortfall) for HERC, and budget constraints on HRP.
Package details |
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Maintainer | |
License | MIT + file LICENSE |
Version | 0.1 |
Package repository | View on GitHub |
Installation |
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