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The United States and China are strong trading partners of Malaysia, with about 23% of total exports in 2017. Therefore, the trade war pressures since 2018 between the United States and China have affected the Malaysian economy. Thus, this paper aims to analyse the effects of the war on the Malaysian stock market using a threshold network approach. Then, the networks examine the changes of important stocks before, during and after the trade war in which the periods are taken from 16th March 2017 until 31st May 2021. The important stocks are determined by four standard centrality approaches, namely degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality. This paper uses 240 companies of the FTSE Bursa Malaysia Emas Index to create the Malaysian stock market networks. The results show that Dagang Nexchange Berhad and Jaya Tiasa Holdings Berhad have higher connectivity with other stocks during the turmoil period and after the turmoil period respectively. Besides, Dagang Nexchange Berhad acts as the most important stock according to all centrality measures. The findings of this study give an insight to the government regulators and investors with information regarding the current topological structure of Malaysia's stock market. [ABSTRACT FROM AUTHOR]

This paper investigates the forecasting ability of Mallows Model Averaging (MMA) by conducting an empirical analysis of five Asia countries, Malaysia, Thailand, Philippines, Indonesia and China's GDP growth rate. Results reveal that MMA has no noticeable differences in predictive ability compared to the general autoregressive fractional integrated moving average model (ARFIMA) and its predictive ability is sensitive to the effect of financial crisis. MMA could be an alternative forecasting method for samples without recent outliers such as financial crisis. [ABSTRACT FROM AUTHOR]