Probability distribution of extreme share returns in Malaysia

Wan Zawiah Wan Zin @ Wan Ibrahim, Muhammad Aslam Mohd Safari, Saiful Hafizah Jaaman @ Sharman, Wendy Ling Shin Yie

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

Abstract

The objective of this study is to investigate the suitable probability distribution to model the extreme share returns in Malaysia. To achieve this, weekly and monthly maximum daily share returns are derived from share prices data obtained from Bursa Malaysia over the period of 2000 to 2012. The study starts with summary statistics of the data which will provide a clue on the likely candidates for the best fitting distribution. Next, the suitability of six extreme value distributions, namely the Gumbel, Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA), the Lognormal (GNO) and the Pearson (PE3) distributions are evaluated. The method of L-moments is used in parameter estimation. Based on several goodness of fit tests and L-moment diagram test, the Generalized Pareto distribution and the Pearson distribution are found to be the best fitted distribution to represent the weekly and monthly maximum share returns in Malaysia stock market during the studied period, respectively.

Original languageEnglish
Title of host publicationStatistics and Operational Research International Conference, SORIC 2013
PublisherAmerican Institute of Physics Inc.
Pages325-333
Number of pages9
Volume1613
ISBN (Electronic)9780735412491
DOIs
Publication statusPublished - 1 Jan 2014
EventStatistics and Operational Research International Conference, SORIC 2013 - Sarawak, Malaysia
Duration: 3 Dec 20135 Dec 2013

Other

OtherStatistics and Operational Research International Conference, SORIC 2013
CountryMalaysia
CitySarawak
Period3/12/135/12/13

Fingerprint

Malaysia
Pearson distributions
moments
goodness of fit
logistics
diagrams
statistics

Keywords

  • Extreme share returns
  • Generalized Extreme Value distribution
  • Generalized Pareto distribution
  • L-moments method

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Wan Zin @ Wan Ibrahim, W. Z., Safari, M. A. M., Jaaman @ Sharman, S. H., & Yie, W. L. S. (2014). Probability distribution of extreme share returns in Malaysia. In Statistics and Operational Research International Conference, SORIC 2013 (Vol. 1613, pp. 325-333). American Institute of Physics Inc.. https://doi.org/10.1063/1.4894357

Probability distribution of extreme share returns in Malaysia. / Wan Zin @ Wan Ibrahim, Wan Zawiah; Safari, Muhammad Aslam Mohd; Jaaman @ Sharman, Saiful Hafizah; Yie, Wendy Ling Shin.

Statistics and Operational Research International Conference, SORIC 2013. Vol. 1613 American Institute of Physics Inc., 2014. p. 325-333.

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

Wan Zin @ Wan Ibrahim, WZ, Safari, MAM, Jaaman @ Sharman, SH & Yie, WLS 2014, Probability distribution of extreme share returns in Malaysia. in Statistics and Operational Research International Conference, SORIC 2013. vol. 1613, American Institute of Physics Inc., pp. 325-333, Statistics and Operational Research International Conference, SORIC 2013, Sarawak, Malaysia, 3/12/13. https://doi.org/10.1063/1.4894357
Wan Zin @ Wan Ibrahim WZ, Safari MAM, Jaaman @ Sharman SH, Yie WLS. Probability distribution of extreme share returns in Malaysia. In Statistics and Operational Research International Conference, SORIC 2013. Vol. 1613. American Institute of Physics Inc. 2014. p. 325-333 https://doi.org/10.1063/1.4894357
Wan Zin @ Wan Ibrahim, Wan Zawiah ; Safari, Muhammad Aslam Mohd ; Jaaman @ Sharman, Saiful Hafizah ; Yie, Wendy Ling Shin. / Probability distribution of extreme share returns in Malaysia. Statistics and Operational Research International Conference, SORIC 2013. Vol. 1613 American Institute of Physics Inc., 2014. pp. 325-333
@inproceedings{801157de856d420c9f60628befa21a66,
title = "Probability distribution of extreme share returns in Malaysia",
abstract = "The objective of this study is to investigate the suitable probability distribution to model the extreme share returns in Malaysia. To achieve this, weekly and monthly maximum daily share returns are derived from share prices data obtained from Bursa Malaysia over the period of 2000 to 2012. The study starts with summary statistics of the data which will provide a clue on the likely candidates for the best fitting distribution. Next, the suitability of six extreme value distributions, namely the Gumbel, Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA), the Lognormal (GNO) and the Pearson (PE3) distributions are evaluated. The method of L-moments is used in parameter estimation. Based on several goodness of fit tests and L-moment diagram test, the Generalized Pareto distribution and the Pearson distribution are found to be the best fitted distribution to represent the weekly and monthly maximum share returns in Malaysia stock market during the studied period, respectively.",
keywords = "Extreme share returns, Generalized Extreme Value distribution, Generalized Pareto distribution, L-moments method",
author = "{Wan Zin @ Wan Ibrahim}, {Wan Zawiah} and Safari, {Muhammad Aslam Mohd} and {Jaaman @ Sharman}, {Saiful Hafizah} and Yie, {Wendy Ling Shin}",
year = "2014",
month = "1",
day = "1",
doi = "10.1063/1.4894357",
language = "English",
volume = "1613",
pages = "325--333",
booktitle = "Statistics and Operational Research International Conference, SORIC 2013",
publisher = "American Institute of Physics Inc.",

}

TY - GEN

T1 - Probability distribution of extreme share returns in Malaysia

AU - Wan Zin @ Wan Ibrahim, Wan Zawiah

AU - Safari, Muhammad Aslam Mohd

AU - Jaaman @ Sharman, Saiful Hafizah

AU - Yie, Wendy Ling Shin

PY - 2014/1/1

Y1 - 2014/1/1

N2 - The objective of this study is to investigate the suitable probability distribution to model the extreme share returns in Malaysia. To achieve this, weekly and monthly maximum daily share returns are derived from share prices data obtained from Bursa Malaysia over the period of 2000 to 2012. The study starts with summary statistics of the data which will provide a clue on the likely candidates for the best fitting distribution. Next, the suitability of six extreme value distributions, namely the Gumbel, Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA), the Lognormal (GNO) and the Pearson (PE3) distributions are evaluated. The method of L-moments is used in parameter estimation. Based on several goodness of fit tests and L-moment diagram test, the Generalized Pareto distribution and the Pearson distribution are found to be the best fitted distribution to represent the weekly and monthly maximum share returns in Malaysia stock market during the studied period, respectively.

AB - The objective of this study is to investigate the suitable probability distribution to model the extreme share returns in Malaysia. To achieve this, weekly and monthly maximum daily share returns are derived from share prices data obtained from Bursa Malaysia over the period of 2000 to 2012. The study starts with summary statistics of the data which will provide a clue on the likely candidates for the best fitting distribution. Next, the suitability of six extreme value distributions, namely the Gumbel, Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA), the Lognormal (GNO) and the Pearson (PE3) distributions are evaluated. The method of L-moments is used in parameter estimation. Based on several goodness of fit tests and L-moment diagram test, the Generalized Pareto distribution and the Pearson distribution are found to be the best fitted distribution to represent the weekly and monthly maximum share returns in Malaysia stock market during the studied period, respectively.

KW - Extreme share returns

KW - Generalized Extreme Value distribution

KW - Generalized Pareto distribution

KW - L-moments method

UR - http://www.scopus.com/inward/record.url?scp=85035788506&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85035788506&partnerID=8YFLogxK

U2 - 10.1063/1.4894357

DO - 10.1063/1.4894357

M3 - Conference contribution

AN - SCOPUS:85035788506

VL - 1613

SP - 325

EP - 333

BT - Statistics and Operational Research International Conference, SORIC 2013

PB - American Institute of Physics Inc.

ER -