A robust optimization approach for index tracking problem
Gharakhani, Mohsen, Zarea Fazlelahi, Forough, & Sadjadi, S.J. (2014) A robust optimization approach for index tracking problem. Journal of Computer Science, 10(12), pp. 2450-2463.
Index tracking is an investment approach where the primary objective is to keep portfolio return as close as possible to a target index without purchasing all index components. The main purpose is to minimize the tracking error between the returns of the selected portfolio and a benchmark. In this paper, quadratic as well as linear models are presented for minimizing the tracking error. The uncertainty is considered in the input data using a tractable robust framework that controls the level of conservatism while maintaining linearity. The linearity of the proposed robust optimization models allows a simple implementation of an ordinary optimization software package to find the optimal robust solution. The proposed model of this paper employs Morgan Stanley Capital International Index as the target index and the results are reported for six national indices including Japan, the USA, the UK, Germany, Switzerland and France. The performance of the proposed models is evaluated using several financial criteria e.g. information ratio, market ratio, Sharpe ratio and Treynor ratio. The preliminary results demonstrate that the proposed model lowers the amount of tracking error while raising values of portfolio performance measures.
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|Item Type:||Journal Article|
|Keywords:||Robust Optimization;, Index Tracking;, Portfolio Selection;, Mean Absolute Deviation Model;, MinMax Model|
|Divisions:||Current > Research Centres > Australian Centre for Entrepreneurship
Current > QUT Faculties and Divisions > QUT Business School
|Copyright Owner:||Copyright 2014 the author(s)|
|Copyright Statement:||This open access article is distributed under a Creative Commons Attribution (CC-BY) 3.0 license|
|Deposited On:||26 Jul 2015 22:35|
|Last Modified:||27 Jul 2015 23:45|
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