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      • Open Access Article

        1 - An Analysis of Covid-19 Pandemic Outbreak on Economy using Neural Network and Random Forest
        Md. Nahid  Hasan Tanvir  Ahmed Md.  Ashik Md. Jahid  Hasan Tahaziba  Azmin Jia Uddin
        The pandemic disease outbreaks are causing a significant financial crisis affecting the worldwide economy. Machine learning techniques are urgently required to detect, predict and analyze the economy for early economic planning and growth. Consequently, in this paper, w More
        The pandemic disease outbreaks are causing a significant financial crisis affecting the worldwide economy. Machine learning techniques are urgently required to detect, predict and analyze the economy for early economic planning and growth. Consequently, in this paper, we use machine learning classifiers and regressors to construct an early warning model to tackle economic recession due to the cause of covid-19 pandemic outbreak. A publicly available database created by the National Bureau of Economic Research (NBER) is used to validate the model, which contains information about national revenue, employment rate, and workers' earnings of the USA over 239 days (1 January 2020 to 12 May 2020). Different techniques such as missing value imputation, k-fold cross validation have been used to pre-process the dataset. Machine learning classifiers- Multi-layer Perceptron- Neural Network (MLP-NN) and Random Forest (RF) have been used to predict recession. Additionally, machine learning regressors-Long Short-Term Memory (LSTM) and Random Forest (RF) have been used to detect how much recession a country is facing as a result of positive test cases of covid-19 pandemic. Experimental results demonstrate that the MLP-NN and RF classifiers have exhibited average 88.33% and 85% of recession (where 95%, 81%, 89% and 85%, 81%, 89% for revenue, employment rate and workers earnings, respectively) and average 90.67% and 93.67% of prediction accuracy for LSTM and RF regressors (where 92%, 90%, 90%, and 95%, 93%, 93% respectively). Manuscript profile
      • Open Access Article

        2 - Working Capital Behavior of Firms under Economic Recession: Evidence from Tehran Capital Market
        Meysam Kaviani فرشاد بزرگی nikfarjam farzad
        In the current challenging economy with increasing environmental pressures and limited external resources, current assets and liabilities, i.e., the working capital of economic enterprises, are increasingly important, and the working capital of economic enterprises can More
        In the current challenging economy with increasing environmental pressures and limited external resources, current assets and liabilities, i.e., the working capital of economic enterprises, are increasingly important, and the working capital of economic enterprises can be considered as a competitive advantage for them. The working capital of the company is the amount invested in current assets. Working capital is considered as a life-giving force for every economic unit and its management should be considered as an important function in management. The purpose of this research is to investigate and analyze the working capital behavior of companies under economic recession in Tehran's capital market. For this purpose, the information of the companies in the period of 10 years from 2013 to 2022 was reviewed and 110 companies were selected. In order to test the hypotheses of the research, multivariate regression method was used. The results showed that the economic recession has a significant impact on the components of working capital management, while the shock from the production sector does not affect them considering the role of financial constraints. The results also showed that the economic recession has a positive effect on the ratio of working capital and a negative effect on the cash conversion cycle, and finally that the economic recession, while having a negative effect on performance, is also affected by the shock from the production sector with the moderating role of financial restrictions. Manuscript profile
      • Open Access Article

        3 - Working Capital Behavior of Firms under Economic Recession: Evidence from Tehran Capital Market
        میثم  کاویانی فرشاد بزرگی nikfarjam farzad
        Meysam Kaviani Frshad Bozorgi Farzad Nikfarjam Abstract In the current challenging economy with increasing environmental pressures and limited external resources, current assets and liabilities, i.e., the working capital of economic enterprises, are increasi More
        Meysam Kaviani Frshad Bozorgi Farzad Nikfarjam Abstract In the current challenging economy with increasing environmental pressures and limited external resources, current assets and liabilities, i.e., the working capital of economic enterprises, are increasingly important, and the working capital of economic enterprises can be considered as a competitive advantage for them. The working capital of the company is the amount invested in current assets. Working capital is considered as a life-giving force for every economic unit and its management should be considered as an important function in management. The purpose of this research is to investigate and analyze the working capital behavior of companies under economic recession in Tehran's capital market. For this purpose, the information of the companies in the period of 10 years from 2013 to 2022 was reviewed and 110 companies were selected. In order to test the hypotheses of the research, multivariate regression method was used. The results showed that the economic recession has a significant impact on the components of working capital management, while the shock from the production sector does not affect them considering the role of financial constraints. The results also showed that the economic recession has a positive effect on the ratio of working capital and a negative effect on the cash conversion cycle, and finally that the economic recession, while having a negative effect on performance, is also affected by the shock from the production sector with the moderating role of financial restrictions. Manuscript profile