Provide Profit and Loss Forecasting Model in the Tose’e Ta’avon Bank

Document Type : Research Paper

Authors

1 PhD Student in Financial Engineering, Department of Management and Accounting,‎ Rasht Branch, Islamic Azad University, Rasht , Iran ‎ ‎‏

2 Assistant Professor, Department of Management and Accounting, Rasht Branch, Islamic Azad University, Rasht , Iran

3 Assistant Professor, Department of Management and Accounting, Rasht Branch, Islamic Azad University, Rasht , Iran‎

Abstract

Subject and Purpose of the Article: The present study is aimed at forecasting and modeling profit and loss in the Tose’e Ta’avon Bank through  conducting an experimental analysis.
Research Method: The statistical population of the study includes the branches of the Tose’e Ta’avon Bank in Tehran, whose financial data from 2011 to 2020 were collected and been the basis of analysis. This research has used the  causal method through collecting information in the theoretical literature section based on library studies and testing hypotheses based on a  document analysis of financial statements. The statistical techniques used in this research are the combined data regression method, heuristic factor analysis, and Bayesian networks.
Research Findings: The data analysis results show that it is possible to predict profits and         losses of the Tose’e Ta’avon Bank based on the identified factors from the financial ratios. The findings also illustrate that the aforementioned factors can account for more than 90% of the changes in the financial ratios. 
Conclusion, Originality and its Contribution to the Knowledge: It can be expected that the bank's profit and loss can be predicted through the final 12 financial ratios of this research and the 5 factors which have been derived from the given ratios. The results of the model can also be used to identify the optimal combination of financial ratios to obtain a certain profit, but this application of the model requires the use of optimization  algorithms.
 

Keywords

References

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History

  • Receive Date: 14 February 2021
  • Revise Date: 06 March 2021
  • Accept Date: 10 July 2021

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