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Efficiency in the stock market is an essential component of the capital allocation system and is crucial in promoting economic growth. In recent years, there has been a growing number of publications focusing on the effect of Covid-19 on human norms. Although there are many studies on the impact of Covid-19 on human norms, the empirical implications of the Covid-19 pandemic on financial markets are still poorly understood. This paper adds to the literature by discussing the effects of a pandemic by studying the stock market efficiency before and after the first case of Covid-19 hit Malaysia. Several robust techniques are utilised to validate the efficient market hypothesis (EMH), namely Ljung-box, Hurst exponent, Chow-denning, and Variance ratio tests. Results indicate a strong influence of Covid-19 on the stock movement. The returns are efficient for the overall sample period. However inefficient after the global pandemic. The findings reported here suggest an increasing chance for market predictability in the Malaysian stock market during the global Covid-19 pandemic. [ABSTRACT FROM AUTHOR]

Prior to the COVID-19 pandemic, majority of universities in Malaysia commonly implement the teaching and learning practices on physical face to face basis. However, the pandemic had drastically changed the norm of the teaching and learning practices into online teaching and learning as one of the measures to curb the spread of the virus among the community. The drastic move had greatly affected the academic communities particularly the students. Some of the possible factors influencing online learning difficulties faced by the students include poor internet accessibility, lack of self-motivation, lack of active interaction with lecturers and peers, lack of conducive learning environment and poor time management. In this paper, the technique of Fuzzy DEMATEL is employed in analyzing the level of influence and relationships of the aforementioned factors in contributing to learning difficulties particularly among fifty mathematic students at a public university in Shah Alam, Selangor, Malaysia. The cause-and-effect analysis that take into consideration the interactions or interrelationships between factors discovered that poor internet accessibility was classified in the cause group whereas the remaining factors which are lack of self-motivation, lack of active interaction with lecturers and peers, lack of conducive learning environment and poor time management were in the effect group. The results indicate that poor internet accessibility has the highest degree of relation in terms of influencing other factors. Based on the prominence value, the lack of self-motivation turns out to be the leading factor contributing to online learning difficulties. [ABSTRACT FROM AUTHOR]

As of March 2022, there have been 3,116,564 infections and 32,827 coronavirus-related deaths reported in the country since the pandemic began on 1st March 2022. This drastic increase in numbers has been alarming everyone. Malaysia has successfully handled the first and second waves of the COVID-19 cases. However, the recent wave of omicron variants in Malaysia sees a massive increase in COVID-19 infections. Therefore, forecasting plays a vital role in determining preparedness for the current pandemic. This study aims to understand the behaviour of the current infection trend and provide valuable information to the authority to prevent future spikes of active cases. In this paper, the SIR model (Susceptible - Infected Recovered) was used to estimate the active cases in Malaysia. This forecast is essential to prepare for the current wave outbreak. Besides that, the number of susceptible can be reduced via vaccinations to reduce future outbreaks. Therefore, with proper planning and execution, the inoculation rates in Malaysia proved to be successful, and the impact of mass vaccination would be seen in future. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to develop the Coronavirus disease (COVID-19) transmission model using the fractional-order differential equation defined by Caputo. This model is developed based on the susceptible-exposed-infected-recovered model, commonly known as the SEIR model. The basic reproduction number, denoted by R0, is computed using the next-generation matrix method. The disease-free equilibrium point is evaluated, and local stability analysis is performed. The analysis shows that the disease-free equilibrium is locally asymptotically stable when R0<1 and unstable when R0>1. In other words, the COVID-19 disease can be eliminated when R0< 1. Finally, numerical results are presented based on the real data of COVID-19 cases in Malaysia. [ABSTRACT FROM AUTHOR]