A two-stage approach to the UCITS-constrained index-tracking problem

作     者：Strub, O. Trautmann, N. 

作者机构：Univ Bern Dept Business Adm Schutzenmattstr 14 CH-3012 Bern Switzerland 

出 版 物：《COMPUTERS & OPERATIONS RESEARCH》 (计算机与运筹学研究)

年 卷 期：2019年第103卷

页      面：167-183页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Portfolio management Index tracking Mixed-integer quadratic programming Heuristics 

摘      要：Undertakings for Collective Investments in Transferable Securities (UCITS) are investment funds that are regulated by the European Union. UCITS have become increasingly popular, resulting in a total corresponding amount of assets under management of (sic) 8.5 trillion by the end of 2016. We present a two-stage approach to the problem of how to construct a portfolio of assets for a UCITS that aims to replicate the returns of a financial index subject to the constraints imposed by the UCITS regulations. In the first stage, we apply a genetic algorithm that treats subsets of the index constituents as individuals to construct a good feasible solution in a short CPU time. In this genetic algorithm, we use a new representation of subsets, which is the first to exhibit all of the following four desirable properties: feasibility, efficiency, locality, and heritability. In the second stage, we apply local branching based on a new mixed-integer quadratic programming formulation to improve the best solution obtained in the first stage. In a numerical experiment on real-world data, the approach yields very good feasible solutions in a short CPU time. (C) 2018 Elsevier Ltd. All rights reserved.