Probability Distribution of Extreme Share Returns in Malaysia

被引：0

作者：

Zin, Wan Zawiah Wan ^{[1
]}

Safari, Muhammad Aslam Mohd ^{[1
]}

Jaaman, Saiful Hafizah ^{[1
]}

Yie, Wendy Ling Shin ^{[1
]}

机构：

[1] Univ Kebangsaan Malaysia, Fac Sci & Technol, Sch Math Sci, Ukm Bangi 43600, Selangor, Malaysia

来源：

STATISTICS AND OPERATIONAL RESEARCH INTERNATIONAL CONFERENCE (SORIC 2013) | 2014年 / 1613卷

关键词：

Extreme share returns; L-moments method; Generalized Extreme Value distribution; Generalized Pareto distribution; L-MOMENT; MARKETS; RISK;

D O I：

10.1063/1.4894357

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

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.

引用

页码：325 / 333

页数：9

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