Enhancing fitting distribution performance through the investigation of patterns in Malaysia extreme share returns

• Published in: AIP Conference Proceedings
• Main Author: Marsani M.F.; Mohd Kasihmuddin M.S.; Badyalina B.; Kerk L.C.; Hassim N.H.; Mokhtar N.A.; Palaniappan S.
• Format: Conference paper
• Language: English
• Published: American Institute of Physics Inc. 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182555234&doi=10.1063%2f5.0171657&partnerID=40&md5=42ff71ebaf3cca6eaa02761eacdd8915

Fitting proper probability distribution while modeling share returns can improve risk management. This study used a concept of a trend to model extreme share returns called the two stages (TS) method in modeling the share returns. The proposed method is first carried out by determining the trend in the data sequence, and then L-moment is employed to estimate the generalized extreme value (GEV) distribution. The extreme share returns are derived from the block maxima minima approach. The Mann Kendal test is utilised to determine the trend for weekly and monthly extreme return intervals. Results showed that the proposed TS method could reach the optimal accuracy on GEV distribution fitting performance for the extreme series if the series data has a positive trend. © 2024 Author(s).