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A Fast Algorithm for Computing High-dimensional Risk Parity Portfolios

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  • Th\'eophile Griveau-Billion
  • Jean-Charles Richard
  • Thierry Roncalli

Abstract

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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File URL: http://arxiv.org/pdf/1311.4057
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Paper provided by arXiv.org in its series Papers with number 1311.4057.

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Date of creation: Nov 2013
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Handle: RePEc:arx:papers:1311.4057

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  1. 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.
  2. Bruder, Benjamin & Roncalli, Thierry, 2012. "Managing risk exposures using the risk budgeting approach," MPRA Paper 37246, University Library of Munich, Germany.
  3. Roncalli, Thierry, 2013. "Introduction to Risk Parity and Budgeting," MPRA Paper 47679, University Library of Munich, Germany.
  4. 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.
  5. 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).
  6. Cazalet, Zelia & Grison, Pierre & Roncalli, Thierry, 2013. "The Smart Beta Indexing Puzzle," MPRA Paper 48823, University Library of Munich, Germany.
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