Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices

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

Abstract

Traditional portfolio optimization methods in the likes of Markowitz' mean-variance model and semi-variance model utilize static expected return and volatility risk from historical data to generate an optimal portfolio. The optimal portfolio may not truly be optimal in reality due to the fact that maximum and minimum values from the data may largely influence the expected return and volatility risk values. This paper considers distributions of assets' return and volatility risk to determine a more realistic optimized portfolio. For illustration purposes, the sectorial indices data in FTSE Bursa Malaysia is employed. The results show that stochastic optimization provides more stable information ratio.

Original languageEnglish
Title of host publicationAIP Conference Proceedings
PublisherAmerican Institute of Physics Inc.
Pages480-486
Number of pages7
Volume1602
ISBN (Print)9780735412361
DOIs
Publication statusPublished - 2014
Event3rd International Conference on Mathematical Sciences, ICMS 2013 - Kuala Lumpur
Duration: 17 Dec 201319 Dec 2013

Other

Other3rd International Conference on Mathematical Sciences, ICMS 2013
CityKuala Lumpur
Period17/12/1319/12/13

Fingerprint

Malaysia
volatility
optimization
static models

Keywords

  • Sectorial portfolio optimization
  • Simulation

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Mamat, N. J. Z., Jaaman @ Sharman, S. H., & Ahmad, R. . R. (2014). Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices. In AIP Conference Proceedings (Vol. 1602, pp. 480-486). American Institute of Physics Inc.. https://doi.org/10.1063/1.4882529

Static vs stochastic optimization : A case study of FTSE Bursa Malaysia sectorial indices. / Mamat, Nur Jumaadzan Zaleha; Jaaman @ Sharman, Saiful Hafizah; Ahmad, Rokiah @ Rozita.

AIP Conference Proceedings. Vol. 1602 American Institute of Physics Inc., 2014. p. 480-486.

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

Mamat, NJZ, Jaaman @ Sharman, SH & Ahmad, RR 2014, Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices. in AIP Conference Proceedings. vol. 1602, American Institute of Physics Inc., pp. 480-486, 3rd International Conference on Mathematical Sciences, ICMS 2013, Kuala Lumpur, 17/12/13. https://doi.org/10.1063/1.4882529
Mamat NJZ, Jaaman @ Sharman SH, Ahmad RR. Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices. In AIP Conference Proceedings. Vol. 1602. American Institute of Physics Inc. 2014. p. 480-486 https://doi.org/10.1063/1.4882529
Mamat, Nur Jumaadzan Zaleha ; Jaaman @ Sharman, Saiful Hafizah ; Ahmad, Rokiah @ Rozita. / Static vs stochastic optimization : A case study of FTSE Bursa Malaysia sectorial indices. AIP Conference Proceedings. Vol. 1602 American Institute of Physics Inc., 2014. pp. 480-486
@inproceedings{718f8766fced47e8ba42224673265e5f,
title = "Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices",
abstract = "Traditional portfolio optimization methods in the likes of Markowitz' mean-variance model and semi-variance model utilize static expected return and volatility risk from historical data to generate an optimal portfolio. The optimal portfolio may not truly be optimal in reality due to the fact that maximum and minimum values from the data may largely influence the expected return and volatility risk values. This paper considers distributions of assets' return and volatility risk to determine a more realistic optimized portfolio. For illustration purposes, the sectorial indices data in FTSE Bursa Malaysia is employed. The results show that stochastic optimization provides more stable information ratio.",
keywords = "Sectorial portfolio optimization, Simulation",
author = "Mamat, {Nur Jumaadzan Zaleha} and {Jaaman @ Sharman}, {Saiful Hafizah} and Ahmad, {Rokiah @ Rozita}",
year = "2014",
doi = "10.1063/1.4882529",
language = "English",
isbn = "9780735412361",
volume = "1602",
pages = "480--486",
booktitle = "AIP Conference Proceedings",
publisher = "American Institute of Physics Inc.",

}

TY - GEN

T1 - Static vs stochastic optimization

T2 - A case study of FTSE Bursa Malaysia sectorial indices

AU - Mamat, Nur Jumaadzan Zaleha

AU - Jaaman @ Sharman, Saiful Hafizah

AU - Ahmad, Rokiah @ Rozita

PY - 2014

Y1 - 2014

N2 - Traditional portfolio optimization methods in the likes of Markowitz' mean-variance model and semi-variance model utilize static expected return and volatility risk from historical data to generate an optimal portfolio. The optimal portfolio may not truly be optimal in reality due to the fact that maximum and minimum values from the data may largely influence the expected return and volatility risk values. This paper considers distributions of assets' return and volatility risk to determine a more realistic optimized portfolio. For illustration purposes, the sectorial indices data in FTSE Bursa Malaysia is employed. The results show that stochastic optimization provides more stable information ratio.

AB - Traditional portfolio optimization methods in the likes of Markowitz' mean-variance model and semi-variance model utilize static expected return and volatility risk from historical data to generate an optimal portfolio. The optimal portfolio may not truly be optimal in reality due to the fact that maximum and minimum values from the data may largely influence the expected return and volatility risk values. This paper considers distributions of assets' return and volatility risk to determine a more realistic optimized portfolio. For illustration purposes, the sectorial indices data in FTSE Bursa Malaysia is employed. The results show that stochastic optimization provides more stable information ratio.

KW - Sectorial portfolio optimization

KW - Simulation

UR - http://www.scopus.com/inward/record.url?scp=84904113881&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84904113881&partnerID=8YFLogxK

U2 - 10.1063/1.4882529

DO - 10.1063/1.4882529

M3 - Conference contribution

AN - SCOPUS:84904113881

SN - 9780735412361

VL - 1602

SP - 480

EP - 486

BT - AIP Conference Proceedings

PB - American Institute of Physics Inc.

ER -