Markowitz portfolio optimization model employing fuzzy measure

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

Abstract

Markowitz in 1952 introduced the mean-variance methodology for the portfolio selection problems. His pioneering research has shaped the portfolio risk-return model and become one of the most important research fields in modern finance. This paper extends the classical Markowitz's mean-variance portfolio selection model applying the fuzzy measure to determine the risk and return. In this paper, we apply the original mean-variance model as a benchmark, fuzzy mean-variance model with fuzzy return and the model with return are modeled by specific types of fuzzy number for comparison. The model with fuzzy approach gives better performance as compared to the mean-variance approach. The numerical examples are included to illustrate these models by employing Malaysian share market data.

Original languageEnglish
Title of host publication4th International Conference on Mathematical Sciences - Mathematical Sciences
Subtitle of host publicationChampioning the Way in a Problem Based and Data Driven Society, ICMS 2016
PublisherAmerican Institute of Physics Inc.
Volume1830
ISBN (Electronic)9780735414983
DOIs
Publication statusPublished - 27 Apr 2017
Event4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016 - Putrajaya, Malaysia
Duration: 15 Nov 201617 Nov 2016

Other

Other4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016
CountryMalaysia
CityPutrajaya
Period15/11/1617/11/16

Fingerprint

optimization
finance
methodology

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Ramli, S., & Jaaman @ Sharman, S. H. (2017). Markowitz portfolio optimization model employing fuzzy measure. In 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016 (Vol. 1830). [040004] American Institute of Physics Inc.. https://doi.org/10.1063/1.4980932

Markowitz portfolio optimization model employing fuzzy measure. / Ramli, Suhailywati; Jaaman @ Sharman, Saiful Hafizah.

4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. Vol. 1830 American Institute of Physics Inc., 2017. 040004.

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

Ramli, S & Jaaman @ Sharman, SH 2017, Markowitz portfolio optimization model employing fuzzy measure. in 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. vol. 1830, 040004, American Institute of Physics Inc., 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016, Putrajaya, Malaysia, 15/11/16. https://doi.org/10.1063/1.4980932
Ramli S, Jaaman @ Sharman SH. Markowitz portfolio optimization model employing fuzzy measure. In 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. Vol. 1830. American Institute of Physics Inc. 2017. 040004 https://doi.org/10.1063/1.4980932
Ramli, Suhailywati ; Jaaman @ Sharman, Saiful Hafizah. / Markowitz portfolio optimization model employing fuzzy measure. 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. Vol. 1830 American Institute of Physics Inc., 2017.
@inproceedings{699912e9c8504e98a9d2076367297504,
title = "Markowitz portfolio optimization model employing fuzzy measure",
abstract = "Markowitz in 1952 introduced the mean-variance methodology for the portfolio selection problems. His pioneering research has shaped the portfolio risk-return model and become one of the most important research fields in modern finance. This paper extends the classical Markowitz's mean-variance portfolio selection model applying the fuzzy measure to determine the risk and return. In this paper, we apply the original mean-variance model as a benchmark, fuzzy mean-variance model with fuzzy return and the model with return are modeled by specific types of fuzzy number for comparison. The model with fuzzy approach gives better performance as compared to the mean-variance approach. The numerical examples are included to illustrate these models by employing Malaysian share market data.",
author = "Suhailywati Ramli and {Jaaman @ Sharman}, {Saiful Hafizah}",
year = "2017",
month = "4",
day = "27",
doi = "10.1063/1.4980932",
language = "English",
volume = "1830",
booktitle = "4th International Conference on Mathematical Sciences - Mathematical Sciences",
publisher = "American Institute of Physics Inc.",

}

TY - GEN

T1 - Markowitz portfolio optimization model employing fuzzy measure

AU - Ramli, Suhailywati

AU - Jaaman @ Sharman, Saiful Hafizah

PY - 2017/4/27

Y1 - 2017/4/27

N2 - Markowitz in 1952 introduced the mean-variance methodology for the portfolio selection problems. His pioneering research has shaped the portfolio risk-return model and become one of the most important research fields in modern finance. This paper extends the classical Markowitz's mean-variance portfolio selection model applying the fuzzy measure to determine the risk and return. In this paper, we apply the original mean-variance model as a benchmark, fuzzy mean-variance model with fuzzy return and the model with return are modeled by specific types of fuzzy number for comparison. The model with fuzzy approach gives better performance as compared to the mean-variance approach. The numerical examples are included to illustrate these models by employing Malaysian share market data.

AB - Markowitz in 1952 introduced the mean-variance methodology for the portfolio selection problems. His pioneering research has shaped the portfolio risk-return model and become one of the most important research fields in modern finance. This paper extends the classical Markowitz's mean-variance portfolio selection model applying the fuzzy measure to determine the risk and return. In this paper, we apply the original mean-variance model as a benchmark, fuzzy mean-variance model with fuzzy return and the model with return are modeled by specific types of fuzzy number for comparison. The model with fuzzy approach gives better performance as compared to the mean-variance approach. The numerical examples are included to illustrate these models by employing Malaysian share market data.

UR - http://www.scopus.com/inward/record.url?scp=85019400335&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85019400335&partnerID=8YFLogxK

U2 - 10.1063/1.4980932

DO - 10.1063/1.4980932

M3 - Conference contribution

VL - 1830

BT - 4th International Conference on Mathematical Sciences - Mathematical Sciences

PB - American Institute of Physics Inc.

ER -