Belief Propagation Algorithm for Portfolio Optimization Problems

arXiv1008.3746MaRDI QIDQ6220323

Muneki Yasuda, Takashi Shinzato

Publication date: 23 August 2010

Abstract: The typical behavior of optimal solutions to portfolio optimization problems with absolute deviation and expected shortfall models using replica analysis was pioneeringly estimated by S. Ciliberti and M. M'ezard [Eur. Phys. B. 57, 175 (2007)]; however, they have not yet developed an approximate derivation method for finding the optimal portfolio with respect to a given return set. In this study, an approximation algorithm based on belief propagation for the portfolio optimization problem is presented using the Bethe free energy formalism, and the consistency of the numerical experimental results of the proposed algorithm with those of replica analysis is confirmed. Furthermore, the conjecture of H. Konno and H. Yamazaki, that the optimal solutions with the absolute deviation model and with the mean-variance model have the same typical behavior, is verified using replica analysis and the belief propagation algorithm.

This page was built for publication: Belief Propagation Algorithm for Portfolio Optimization Problems

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6220323)