Management
Md. Rezaul Karim; Sifat Ara Saba
Abstract
This paper has tried to assess the impact of COVID-19 on stock return in different sectors listed under Dhaka Stock Exchange in Bangladesh during the period from 08 March 2020 to 15 September 2020. To measure the impact of COVID-19 on stock return, daily change in number of confirmed cases and ...
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This paper has tried to assess the impact of COVID-19 on stock return in different sectors listed under Dhaka Stock Exchange in Bangladesh during the period from 08 March 2020 to 15 September 2020. To measure the impact of COVID-19 on stock return, daily change in number of confirmed cases and deaths have been used as independent variables and DSE stock return has been taken as variable of interest. Data were collected from Bangladesh Government’s official portal, DSE archive and annual reports of listed firms. Sample is selected using two stage sampling method which is a probabilistic model. To test the validity of the used model, Pearson’s correlations analysis, Breusch and Pagan’s heteroscedasticity test, White’s homoscedasticity test and Hausman’s fixed random tests are conducted. After testing the validity, fixed effect method of panel data regression model has been used to test the two hypotheses. The result reveals that most of the sectors responded negatively to the growth in COVID-19 confirmed cases. It is also observed that selected sectors reacted more proactively to the growth in number of deaths as compared to the growth in number of confirmed cases. Where banking and textile sectors are the most sufferers to the growth of both confirmed cases and deaths, pharmaceuticals & chemicals industry proved out to be the gainers. The findings will have policy implications for the regulators as well as for the investors to design the optimum portfolio of investment. The study will add new dimensions to the existing literature.
Accounting
Md. Rezaul Karim; Muhammad Armaan Hossain
Abstract
The purpose of this study is to predict the areas in financial statements susceptive to fraud in the banking sector of Bangladesh. Data of 13 years ranging from 2006 to 2018 of 29 listed banks in Bangladesh were examined for the purpose of this study. Financial data suggested by International Standard ...
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The purpose of this study is to predict the areas in financial statements susceptive to fraud in the banking sector of Bangladesh. Data of 13 years ranging from 2006 to 2018 of 29 listed banks in Bangladesh were examined for the purpose of this study. Financial data suggested by International Standard on Auditing (ISA) 240 as fraud risk indicators were used as the independent variables and banks identified by Centre for Policy Dialogue (CPD) to be engaged in fraud, scam and heists were taken as dependent variable. Multilayer Perceptron Network (MLP), a class of feedforward Artificial Neural Network (ANN) model was used as the analytical tool. It is found that loan disbursement, assets, profit, operating expenses and tax are the areas that can signal the probable fraud in financial statements of the listed banks of Bangladesh. The findings of this study will have policy implications for auditors and the regulators of money market in Bangladesh.
