Portfolio optimization for index tracking modelling in Malaysia stock market

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Index tracking is an investment strategy in portfolio management which aims to construct an optimal portfolio to generate similar mean return with the stock market index mean return without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using the optimization model which adopts regression approach in tracking the benchmark stock market index return. In this study, the data consists of weekly price of stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2013. The results of this study show that the optimal portfolio is able to track FBMKLCI Index at minimum tracking error of 1.0027% with 0.0290% excess mean return over the mean return of FBMKLCI Index. The significance of this study is to construct the optimal portfolio using optimization model which adopts regression approach in tracking the stock market index without purchasing all index components.

Original languageEnglish
Title of host publicationInnovations Through Mathematical and Statistical Research: Proceedings of the 2nd International Conference on Mathematical Sciences and Statistics, ICMSS 2016
PublisherAmerican Institute of Physics Inc.
Volume1739
ISBN (Electronic)9780735413962
DOIs
Publication statusPublished - 2 Jun 2016
Event2nd International Conference on Mathematical Sciences and Statistics: Innovations Through Mathematical and Statistical Research, ICMSS 2016 - Kuala Lumpur, Malaysia
Duration: 26 Jan 201628 Jan 2016

Other

Other2nd International Conference on Mathematical Sciences and Statistics: Innovations Through Mathematical and Statistical Research, ICMSS 2016
CountryMalaysia
CityKuala Lumpur
Period26/1/1628/1/16

Fingerprint

Malaysia
optimization
regression analysis

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Siew, L. W., Jaaman @ Sharman, S. H., & Ismail, H. (2016). Portfolio optimization for index tracking modelling in Malaysia stock market. In Innovations Through Mathematical and Statistical Research: Proceedings of the 2nd International Conference on Mathematical Sciences and Statistics, ICMSS 2016 (Vol. 1739). [020025] American Institute of Physics Inc.. https://doi.org/10.1063/1.4952505

Portfolio optimization for index tracking modelling in Malaysia stock market. / Siew, Lam Weng; Jaaman @ Sharman, Saiful Hafizah; Ismail, Hamizun.

Innovations Through Mathematical and Statistical Research: Proceedings of the 2nd International Conference on Mathematical Sciences and Statistics, ICMSS 2016. Vol. 1739 American Institute of Physics Inc., 2016. 020025.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Siew, LW, Jaaman @ Sharman, SH & Ismail, H 2016, Portfolio optimization for index tracking modelling in Malaysia stock market. in Innovations Through Mathematical and Statistical Research: Proceedings of the 2nd International Conference on Mathematical Sciences and Statistics, ICMSS 2016. vol. 1739, 020025, American Institute of Physics Inc., 2nd International Conference on Mathematical Sciences and Statistics: Innovations Through Mathematical and Statistical Research, ICMSS 2016, Kuala Lumpur, Malaysia, 26/1/16. https://doi.org/10.1063/1.4952505
Siew LW, Jaaman @ Sharman SH, Ismail H. Portfolio optimization for index tracking modelling in Malaysia stock market. In Innovations Through Mathematical and Statistical Research: Proceedings of the 2nd International Conference on Mathematical Sciences and Statistics, ICMSS 2016. Vol. 1739. American Institute of Physics Inc. 2016. 020025 https://doi.org/10.1063/1.4952505
Siew, Lam Weng ; Jaaman @ Sharman, Saiful Hafizah ; Ismail, Hamizun. / Portfolio optimization for index tracking modelling in Malaysia stock market. Innovations Through Mathematical and Statistical Research: Proceedings of the 2nd International Conference on Mathematical Sciences and Statistics, ICMSS 2016. Vol. 1739 American Institute of Physics Inc., 2016.
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