HRP_Portfolio: Hierarchical Risk Parity

In HierPorfolios: Hierarchical Clustering-Based Portfolio Allocation Strategies

Description

Performs the Hierarchical Risk Parity portfolio proposed strategy by De Prado (2016). Several linkage methods for the hierarchical clustering can be used, by default the "single" linkage is used.

Usage

HRP_Portfolio(covar, linkage = "single", graph = FALSE)

Arguments

covar	Covariance matrix of returns. The covariance matrix will be transformed into correlation matrix and then into a distance matrix.
linkage	Linkage method used in the hierarchical clustering. Allowed options are "single", "complete", "average" or "ward". Default option is "single".
graph	To plot de dendrogram set this value to TRUE. By default this value is equal to FALSE.

Value

portfolio weights

References

De Prado, Marcos Lopez. "Building diversified portfolios that outperform out of sample." The Journal of Portfolio Management 42.4 (2016): 59-69.

See Also

HCAA_porfolio

Examples

covar <- cov(mldp_returns)
HRP_Portfolio(covar)

HierPorfolios documentation built on Nov. 8, 2021, 5:09 p.m.