A financial network for energy sector of Bursa Malaysia during covid-19 by using triangular maximally filtered graph approach - Bahaludin, Hafizah; Mahamood, Fatin Nur Amirah; Abdullah, Mimi Hafizah; Fauzi, Muhammad Ashraf; Omar, Mawardi (IIUM Press, 2022)
The global COVID-19 outbreak has created disruptions across all economic sectors. Energy is one of the most severely affected industries. As the global economic outlook deteriorated, oil prices plunged, severely impacting energy industries in most nations. This unprecedented situation motivated us to study what happens to the interconnectedness among energy stock that listed in Bursa Malaysia. Filtering correlation matrices have been proven to be very useful for the study and describe of the underlying interconnectedness structure of complex datasets. The triangulated maximally filtered graph (TMFG) is one of the approaches that construct a network based on the correlation measure in which compatible with the big data. Therefore, the objective of this study was to examine the impact of COVID-19 on the shariah-compliant energy stock in Bursa Malaysia during COVID-19 by using TMFG approach. The data range is from 2019 - 2020. The network was formed for 2019 and 2020, and the centrality measure was computed to investigate the network further. The results indicate that ten out of twenty- six stocks experienced an increase in the number of links because of COVID-19. The energy, infrastructure, equipment, and services subsector dominate the networks and Hibiscus Petroleum Bhd (HIBI) was the most influential stock during COVID-19. The market participant can obtain a thorough overview of the energy market's condition in order to create the portfolio and implement the policy.