Consequences of COVID-19 on Banking Sector Index: Artificial Neural Network Model

Assous, Hamzeh F.; AL-Najjar, Dania

doi:10.3390/ijfs9040067

Cited by 16 publications

(19 citation statements)

References 44 publications

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“…Ref. [59] explored the consequences of the Saudi banking index due to the COVID-19 pandemic. They considered the lockdown data with the COVID-19 cases, interest rates, and oil prices to conduct the research and drew an ANN model.…”

Section: Research On the Banking Sector During The Covid-19 Pandemic ...mentioning

confidence: 99%

Impact of COVID-19 on Financial Performance and Profitability of Banking Sector in Special Reference to Private Commercial Banks: Empirical Evidence from Bangladesh

et al. 2022

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The current crisis caused by the COVID-19 pandemic has hit the global economy hard, causing significant damage to every aspect of the global banking system, and Bangladesh is no exception. For that reason, its performance and profitability have been affected. In this study, we investigate the impact of COVID-19 on the financial performance and profitability of the listed private commercial banks in Bangladesh. We initially compute each bank’s financial performance index (FPI) to determine the position according to their financial performance individually before and the current period of COVID-19 by the standardized CAMELS rating system. After assessing the position, the fixed-effect regression model is used to explore the impact of the bank’s specific variables and macroeconomic variables along with the banks’ variables on the banks’ profitability. The banks that performed better during the pre-pandemic period of COVID-19 also performed better during the pandemic period of COVID-19. The performance of AIBL, EBL, and BBL was almost autonomously higher during both periods. In the case of bank profitability, our paper discovered that during the pandemic period of COVID-19, high non-performing loan rates, holding more liquid assets, a high amount of hedging capital, and inappropriate bank size lessened the banks’ profitability. In contrast, a low leverage position and inflation rate enhanced the bank’s profitability during this period. The outcome of this study will help bank authorities detect the loopholes and take preventive measures that can improve their profitability during a crisis period like COVID-19. The investors and depositors who invest money in banks can precisely decide their portfolios.

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Section: Research On the Banking Sector During The Covid-19 Pandemic ...mentioning

confidence: 99%

Impact of COVID-19 on Financial Performance and Profitability of Banking Sector in Special Reference to Private Commercial Banks: Empirical Evidence from Bangladesh

et al. 2022

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“…However, making these right decisions is a complicated mission because many macroeconomic variables and international factors interact to influence the movement of stock markets indices and subindices into unanticipated levels. [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

The Co-Movement between International and Emerging Stock Markets Using ANN and Stepwise Models: Evidence from Selected Indices

AL-Najjar

2022

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In the past two decades, especially after the financial crisis of 2007–09, the literature for examining the availability of integration between the stock exchanges in developed and developing markets has grown. The importance of this topic stems from the significant implications of the linkage between exchange markets on various decisions taken by interested parties, such as policymakers and investors, in the decisions for portfolio diversification. This study examines the relationship between a developing stock exchange index, Amman Stock Exchange Index (ASEI), and the number of international indices, including S&P 500, NASDAQ, Nikkei, DAX, CAC, and HSI for 2008-2019. To validate the availability of the linkage between the indices, the author includes various tests of a correlation coefficient, stepwise regression analysis, and artificial neural network (ANN). Despite the results indicating that the ANN is more efficient than linear regression in investigating the availability of the relationship between ASEI and international indices, stepwise regression and neural network support this relationship. Furthermore, ANN results revealed that the S&P 500 index and year have the most substantial relationship with ASEI. Our research is theoretically and practically important; policymakers and investors can benefit from our findings. Future studies may explore the effect of different international stock market indices on ASEI or other developing markets. Further studies can use macroeconomic factors to build prediction models for stock market indices.

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“…ere is no known research article for authors who predicted Tadawul All Share Index (TASI) using air quality indices as independent variables. erefore, the researchers compared the best results with most research that predicted the stock market using neural network models described in [36] and [41]. Assous and Al-Najjar [36] reported that the neural network model is the best in stock market predictions.…”

Section: Developed Chaid and Cr-tree Prediction Modelsmentioning

confidence: 99%

Developing Machine Learning Techniques to Investigate the Impact of Air Quality Indices on Tadawul Exchange Index

et al. 2022

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The air quality index (AQI) can be described using different pollutant indices. Many investigators study the effect of stock prices and air quality in the field to show if there is a relationship between changing the stock market and the concentration of various pollutants. This study aims to find a relationship between Saudi Tadawul All Share Index (TASI) and multiple pollutants, including particulate matter (PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and AQI. Based on tree models, the relationship is created using linear regression and two prediction models, Chi-square Automatic Interaction Detection (CHAID), and CR-Tree. In order to achieve the target of this research, the TASI dataset relates to six pollutants using time; afterward, the new dataset is divided into three parts—test, validate, and train—after eliminating the outlier data. In order to test the performance of two prediction models, R2 and various error functions are used. The linear regression model results found that PM10, NO2, CO, month, day, and year are significant, whereas O3, SO2, and AQI indices are insignificant. The test dataset showed that R2 scores are 0.995 and 0.986 for CR-Tree and CHAID, respectively, with RMSE values of 387 and 227 for CR-Tree and CHAID, respectively. The prediction models showed that the CHAID model performed better than CR-Tree because it used only three indices, namely, PM10, AQI, and O3, with year and month. The results indicated an effect between changing TASI and the three pollutants, PM10, AQI, and O3.

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Consequences of COVID-19 on Banking Sector Index: Artificial Neural Network Model

Cited by 16 publications

References 44 publications

Impact of COVID-19 on Financial Performance and Profitability of Banking Sector in Special Reference to Private Commercial Banks: Empirical Evidence from Bangladesh

Impact of COVID-19 on Financial Performance and Profitability of Banking Sector in Special Reference to Private Commercial Banks: Empirical Evidence from Bangladesh

The Co-Movement between International and Emerging Stock Markets Using ANN and Stepwise Models: Evidence from Selected Indices

Developing Machine Learning Techniques to Investigate the Impact of Air Quality Indices on Tadawul Exchange Index

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