首页 | 本学科首页   官方微博 | 高级检索  
     检索      


The optimal statistical median of a convex set of arrays
Authors:Stefano Benati  Romeo Rizzi
Institution:(1) Dipartimento di Sociologia e Ricerca sociale, Università di Trento, Via Verdi 6, 38100 Trento, Italy;(2) Dipartimento di Matematica ed Informatica, Università di Udine, Via delle Scienze 208, 33100 Udine, Italy
Abstract:We consider the following problem. A set $${r^1, r^2,\ldots , r^K \,{\in} \mathbf{R}^T}$$ of vectors is given. We want to find the convex combination $${z = \sum \lambda_j r^j}$$ such that the statistical median of z is maximum. In the application that we have in mind, $${r^j, j=1,\ldots,K}$$ are the historical return arrays of asset j and $${\lambda_j, j=1,\ldots,K}$$ are the portfolio weights. Maximizing the median on a convex set of arrays is a continuous non-differentiable, non-concave optimization problem and it can be shown that the problem belongs to the APX-hard difficulty class. As a consequence, we are sure that no polynomial time algorithm can ever solve the model, unless P = NP. We propose an implicit enumeration algorithm, in which bounds on the objective function are calculated using continuous geometric properties of the median. Computational results are reported.
Keywords:Global optimization  Median optimization  Statistical median and quantile optimization  Robust statistics  Branch&  bound algorithms
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号