Metadata-Version: 2.1
Name: pyhrp
Version: 0.0.5
Summary: Python for Hierarchical Risk Parity
Home-page: https://github.com/tschm/hrp
Author: Thomas Schmelzer
Author-email: thomas.schmelzer@gmail.com
License: UNKNOWN
Project-URL: Source Code, https://github.com/tschm/hrp
Description: # pyhrp
        
        A recursive implementation of the Hierarchical Risk Parity (hrp) approach by Marcos Lopez de Prado.
        We take heavily advantage of the scipy.cluster.hierarchy package. 
        
        Here's a simple example
        
        ```python
        import numpy as np
        
        from pyhrp.cluster import root
        from pyhrp.graph import dendrogram
        from pyhrp.hrp import dist, hrp_feed
        
        # use a small covariance matrix
        cov = np.array([[1, 0.2, 0], [0.2, 2, 0.0], [0, 0, 3]])
        
        # we compute the rootnode of a graph here
        # The rootnode points to left and right and has an id attribute.
        rootnode, link = root(dist(cov), 'ward')
        
        # plot the dendrogram
        ax = dendrogram(link, orientation="left")
        ax.get_figure().savefig("dendrogram.png")
        
        v, weights = hrp_feed(rootnode, cov=cov)
        
        print(v)
        print(np.linalg.multi_dot([weights, cov, weights]))
        print(weights)
        print(weights.sum())
        ```
        
        ## Installation:
        ```
        pip install pyhpr
        ```
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
