The Development of a Fuzzy Logic System in a Stochastic Environment with Normal Distribution Variables for Cash Flow Deficit Detection in Corporate Loan Policy
This paper develops a Mamdani fuzzy logic system (FLS) that has stochastic fuzzy input variables designed to identify cash-flow deficits in bank lending policies. These deficits do not cover the available cash-flow (CFA) resulting from the company’s operating activity. Thus, due to these d...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-04-01
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| Series: | Symmetry |
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| Online Access: | https://www.mdpi.com/2073-8994/11/4/548 |
| _version_ | 1811306819733159936 |
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| author | Marcel-Ioan Boloș Ioana-Alexandra Bradea Camelia Delcea |
| author_facet | Marcel-Ioan Boloș Ioana-Alexandra Bradea Camelia Delcea |
| author_sort | Marcel-Ioan Boloș |
| collection | DOAJ |
| description | This paper develops a Mamdani fuzzy logic system (FLS) that has stochastic fuzzy input variables designed to identify cash-flow deficits in bank lending policies. These deficits do not cover the available cash-flow (CFA) resulting from the company’s operating activity. Thus, due to these deficits, solutions must be identified to avoid companies’ financial difficulties. The novelty of this paper lies in its using stochastic fuzzy variables, or those categories of variables that are defined by fuzzy sets, characterized by normally distributed density functions specific to random variables, and characterized by fuzzy membership functions. The variation intervals of the stochastic fuzzy variables allow identification of the probabilistic risk situations to which the company is exposed during the crediting period using the Mamdani-type fuzzy logic system. The mechanism of implementing the fuzzy logic system is based on two stages. The first is based on the determination of the cash-flow requirements resulting from loan reimbursement and interest rates. This stage has the role of determining the need for financial resources to cover the liabilities. The second stage is based on the identification of the stochastic fuzzy variables which have a role in influencing the cash flow deficits and the probability values estimation of these variables taking into account probability calculations. Based on these probabilistic values, using the Mamdani fuzzy logic system, estimations are computed for the available cash-flow (the output variable). The estimated values for CFA are then used to detect probability risk situations in which the company will not have enough resources to cover its liabilities to financial creditors. All the FLS calculations refer to future time periods. Testing and simulating the fuzzy controller confirms its functionality. |
| first_indexed | 2024-04-13T08:52:36Z |
| format | Article |
| id | doaj.art-aaf37defe5b343e6add055d3afed2600 |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-04-13T08:52:36Z |
| publishDate | 2019-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-aaf37defe5b343e6add055d3afed26002022-12-22T02:53:26ZengMDPI AGSymmetry2073-89942019-04-0111454810.3390/sym11040548sym11040548The Development of a Fuzzy Logic System in a Stochastic Environment with Normal Distribution Variables for Cash Flow Deficit Detection in Corporate Loan PolicyMarcel-Ioan Boloș0Ioana-Alexandra Bradea1Camelia Delcea2Department of Finance and Banks, University of Oradea, 410087 Oradea, RomaniaDepartment of Informatics and Cybernetics, Bucharest University of Economic Studies, 010552 Bucharest, RomaniaDepartment of Informatics and Cybernetics, Bucharest University of Economic Studies, 010552 Bucharest, RomaniaThis paper develops a Mamdani fuzzy logic system (FLS) that has stochastic fuzzy input variables designed to identify cash-flow deficits in bank lending policies. These deficits do not cover the available cash-flow (CFA) resulting from the company’s operating activity. Thus, due to these deficits, solutions must be identified to avoid companies’ financial difficulties. The novelty of this paper lies in its using stochastic fuzzy variables, or those categories of variables that are defined by fuzzy sets, characterized by normally distributed density functions specific to random variables, and characterized by fuzzy membership functions. The variation intervals of the stochastic fuzzy variables allow identification of the probabilistic risk situations to which the company is exposed during the crediting period using the Mamdani-type fuzzy logic system. The mechanism of implementing the fuzzy logic system is based on two stages. The first is based on the determination of the cash-flow requirements resulting from loan reimbursement and interest rates. This stage has the role of determining the need for financial resources to cover the liabilities. The second stage is based on the identification of the stochastic fuzzy variables which have a role in influencing the cash flow deficits and the probability values estimation of these variables taking into account probability calculations. Based on these probabilistic values, using the Mamdani fuzzy logic system, estimations are computed for the available cash-flow (the output variable). The estimated values for CFA are then used to detect probability risk situations in which the company will not have enough resources to cover its liabilities to financial creditors. All the FLS calculations refer to future time periods. Testing and simulating the fuzzy controller confirms its functionality.https://www.mdpi.com/2073-8994/11/4/548fuzzy logic systemdecision making processcash-flow deficitloan policy |
| spellingShingle | Marcel-Ioan Boloș Ioana-Alexandra Bradea Camelia Delcea The Development of a Fuzzy Logic System in a Stochastic Environment with Normal Distribution Variables for Cash Flow Deficit Detection in Corporate Loan Policy Symmetry fuzzy logic system decision making process cash-flow deficit loan policy |
| title | The Development of a Fuzzy Logic System in a Stochastic Environment with Normal Distribution Variables for Cash Flow Deficit Detection in Corporate Loan Policy |
| title_full | The Development of a Fuzzy Logic System in a Stochastic Environment with Normal Distribution Variables for Cash Flow Deficit Detection in Corporate Loan Policy |
| title_fullStr | The Development of a Fuzzy Logic System in a Stochastic Environment with Normal Distribution Variables for Cash Flow Deficit Detection in Corporate Loan Policy |
| title_full_unstemmed | The Development of a Fuzzy Logic System in a Stochastic Environment with Normal Distribution Variables for Cash Flow Deficit Detection in Corporate Loan Policy |
| title_short | The Development of a Fuzzy Logic System in a Stochastic Environment with Normal Distribution Variables for Cash Flow Deficit Detection in Corporate Loan Policy |
| title_sort | development of a fuzzy logic system in a stochastic environment with normal distribution variables for cash flow deficit detection in corporate loan policy |
| topic | fuzzy logic system decision making process cash-flow deficit loan policy |
| url | https://www.mdpi.com/2073-8994/11/4/548 |
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