A Fast Algorithm for Computing High-dimensional Risk Parity Portfolios

In this paper we propose a cyclical coordinate descent (CCD) algorithm for solving high dimensional risk parity problems. We show that this algorithm converges and is very fast even with large covariance matrices (n > 500). Comparison with existing algorithms also shows that it is one of the most efficient algorithms.

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Year of publication:	2013-09-01
Authors:	Griveau-Billion, Théophile ; Richard, Jean-Charles ; Roncalli, Thierry
Institutions:	Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München
Subject:	Risk parity \| risk budgeting \| ERC portfolio \| cyclical coordinate descent algorithm \| lasso

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Extent:	application/pdf
Series:	MPRA Paper.
Type of publication:	Book / Working Paper
Classification:	C60 - Mathematical Methods and Programming. General ; G11 - Portfolio Choice
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011111212