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


Exact methods for large-scale multi-period financial planning problems
Authors:R Baldacci  M A Boschetti  N Christofides  S Christofides
Institution:(1) DEIS, University of Bologna, Bologna, Italy;(2) Department of Mathematics, University of Bologna, Via Sacchi 3, 47023 Cesena, Italy;(3) Centre for Quantitative Finance, Imperial College, London, UK
Abstract:A relevant financial planning problem is the periodical rebalance of a portfolio of assets such that the portfolio’s total value exhibits certain characteristics. This problem can be modelled using a transition graph G to represent the future state space evolution of the corresponding economy and mathematically formulated as a linear programming problem. We present two different mathematical formulations of the problem. The first considers explicitly the set of the possible scenarios (scenario-based approach), while the second considers implicitly the whole set of scenarios provided by the graph G (graph-based approach). Unfortunately, for both the formulations the size of the corresponding linear programs can be huge even for simple financial problems. However, the graph-based approach seems to be a more powerful model, since it allows to consider a huge number of scenarios in a very compact formulation. The purpose of this paper is to present both heuristic and exact methods for the solution of large-scale multi-period financial planning problems using the graph-based model. In particular, in this paper we propose lower and upper bounds and three exact methods based on column, row and column/row generation, respectively. Since the methods based on column/row generation exploits simultaneously both the primal and the dual structure of the problem we call it Criss-Cross generation method. Computational results are given to prove the effectiveness of the proposed methods.
Keywords:Portfolio management  Large scale optimization  Linear programming  Column/row generation
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