mldp_returns

<p>This dataset contains the simulated returns used in the numerical example of Marcos Lopez de Prado's paper, hence the name <code>mldp_returns</code>. The Python code used to reproduce this simulated data is kindly provided by the author in the supplementary material of his paper.</p>

dataset

Machine learning portfolio allocation strategies based on hierarchical clustering methods.
The implemented methods are:
Hierarchical risk parity (De Prado, 2016) <DOI: 10.3905/jpm.2016.42.4.059> and
Hierarchical clustering-based asset allocation (Raffinot, 2017)
<DOI: 10.3905/jpm.2018.44.2.089>.

Carlos Trucios

mldp_returns: Returns of 10 simulated assets.

Description

Arguments

References