This study aims to determine an accurate forecasting model, especially an error rate of around 0, and to examine how the automatic rejection system reacts to stock price as a result of the pandemic. The statistical clustering method is used for the dataset in form of daily observations, while the sample covers the period of cases before and after COVID-19 pandemic from 02 January 2019 to 20 June 2020 at the Trinitan Minerals and Metal Company. Furthermore, the data used in the estimation are the opening and closing price of returns, which are later processed using SAS analysis tools. It is shown that the most appropriate decision-making processes are those proven to be most effective. Therefore, predicting future events based on a suitable time series model will help policymakers and strategists make decisions and develop appropriate strategic plans regarding the stock market. Meanwhile, 98% of the ARIMA (1,1,1) is a forecasting model which can be applied to predict stock prices. The new approach of this study is an integrated autoregressive moving average used as an attempt to accurately predict stock prices during a pandemic.

This study aims to analyze company characteristics as a determinant of conventional and Islamic bank earnings management in several ASEAN countries (Association of South East Asian Nations). The Multiple Discriminant Analysis was applied to determine the differences between Islamic and Conventional Banks. This test was conducted based on Capital Adequacy Ratio, Income Before Tax and Interest, Non-Performing and Changing Loans, and Company's Size in the banks of Indonesia, Malaysia, and Brunei Darussalam from 2014 to 2018. The data obtained from 200 banking entities were analyzed discriminatively. The results showed that there were simultaneous differences between Capital Adequacy Ratio, Earnings Before Tax, Loan Loss Provision, Non-Performing and Changing Loans, and Company's Size as determinants of earnings management between Islamic and conventional banks. Also, it was found that Company's Size was the dominant variable determining the management differences. Based on Discriminant Analysis, there were significant differences in the determinants of conventional and Islamic earnings management. The Changing Loan variable showed the highest contribution in determining earnings management in Islamic banks. Overall, this study found that conventional banks dominated Islamic system in practicing earnings management.

This study aims to the rise in global economic integration is due to an expansion in volatility spillovers. Therefore, it is extraordinarily necessary to analyze the volatility spillovers for growing and developed international locations through the use of portfolio funding and danger management. This lookup investigates the Volatility Spillovers of Sharia Index on 6 ASEAN international locations all through the Covid-19 Pandemic the usage of the EGARCH model. Data have been received from 5 international locations with enormous volatility spillovers, particularly Indonesia, Malaysia, Singapore, Thailand, and Vietnam, to decide the reciprocal relationship of the inventory index in ASEAN as properly as the route of volatility movements. The result confirmed that this lookup is necessary for ASEAN traders besides for the Philippines. Furthermore, this lookup has sturdy sensible significance due to the fact the correct prediction of the volatility spillovers in worldwide fairness markets is quintessential for decreasing portfolio risk.