Paper Info
Title
Index tracking with controlled number of assets using a hybrid heuristic combining genetic algorithm and non-linear programming.
Abstract
In this paper, we discuss the index tracking strategy using mathematical programming. First, we use a non-linear programming formulation for the index tracking problem, considering a limited number of assets. Since the problem is difficult to be solved in reasonable time by commercial mathematical packages, we apply a hybrid solution approach, combining mathematical programming and genetic algorithm. We show the efficiency of the proposed approach comparing the results with optimal solutions, with previous developed methods, and from real-world market indexes. The computational experiments focus on Ibovespa (the most important Brazilian market index), but we also present results for consolidated markets such as Su0026P 100 (USA), FTSE 100 (UK) and DAX (Germany). The proposed framework shows its ability to obtain very good results (gaps from the optimal solution smaller than 5 % in 8 min of CPU time) even for a highly volatile index from a developing country.
Year
DOI
Venue
2017
10.1007/s10479-016-2111-x
Annals OR
Keywords
Field
DocType
Index tracking, Portfolio optimization, Genetic algorithm
Heuristic,Mathematical optimization,CPU time,Stock market index,Nonlinear programming,Developing country,Portfolio optimization,Genetic algorithm,Mathematics
Journal
Volume
Issue
ISSN
258
2
1572-9338
Citations 
PageRank 
References 
6
0.45
19
Authors
4
Name
Order
Citations
PageRank
Leonardo Riegel Sant'Anna160.79
Tiago Pascoal Filomena2272.41
Pablo Cristini Guedes360.45
Denis Borenstein419020.73