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.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Thierry Roncalli, 2014.
"Introduction to Risk Parity and Budgeting,"
- Cazalet, Zelia & Grison, Pierre & Roncalli, Thierry, 2013. "The Smart Beta Indexing Puzzle," MPRA Paper 48823, University Library of Munich, Germany.
- Roncalli, Thierry, 2013. "Introducing Expected Returns into Risk Parity Portfolios: A New Framework for Tactical and Strategic Asset Allocation," MPRA Paper 49821, University Library of Munich, Germany.
- Bruder, Benjamin & Roncalli, Thierry, 2012. "Managing risk exposures using the risk budgeting approach," MPRA Paper 37246, University Library of Munich, Germany.
- Teiletche, Jérôme & Roncalli, Thierry & Maillard, Sébastien, 2010. "The properties of equally-weighted risk contributions portfolios," Economics Papers from University Paris Dauphine 123456789/4688, Paris Dauphine University.
- Jerome H. Friedman & Trevor Hastie & Rob Tibshirani, . "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, American Statistical Association, vol. 33(i01).
When requesting a correction, please mention this item's handle: RePEc:arx:papers:1311.4057. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (arXiv administrators)
If references are entirely missing, you can add them using this form.