An artificial intelligence-based forecasting of the dynamics of relative profit rates at a financial crisis juncture: A model, a case study and crisis management policies

The purpose of this paper is to (i) demonstrate that the behavior of the relative profit rates at financial crisis junctures in a dual financial system could be different than that of the other periods, (ii) show that relative profit rates (and their dynamics) at crisis junctures could be forecasted...

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Main Author: Kara Ahmet
Format: Article
Language:English
Published: Sciendo 2025-03-01
Series:Financial Internet Quarterly
Subjects:
Online Access:https://doi.org/10.2478/fiqf-2025-0002
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author Kara Ahmet
author_facet Kara Ahmet
author_sort Kara Ahmet
collection DOAJ
description The purpose of this paper is to (i) demonstrate that the behavior of the relative profit rates at financial crisis junctures in a dual financial system could be different than that of the other periods, (ii) show that relative profit rates (and their dynamics) at crisis junctures could be forecasted with a relatively high degree of accuracy via artificial intelligence algorithms and (iii) exemplify the possibility of crisis-management policies that can smoothen the trajectory of the relative profit rates and facilitate the control of possible erratic fluctuations at the crisis junctures in such systems. We employ a series of methodological tools involving (i) statistical tests, (ii) artificial intelligence algorithms and (iii) the system dynamics simulation method to achieve the three objectives outlined in the paragraph above. The results are of practical significance to the financial policy makers aiming to formulate and put in practice effective policies at crisis junctures.
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spelling doaj-art-e4d28464d9e44b39a082da31d8d1039e2025-08-20T02:50:27ZengSciendoFinancial Internet Quarterly2719-34542025-03-01211152610.2478/fiqf-2025-0002An artificial intelligence-based forecasting of the dynamics of relative profit rates at a financial crisis juncture: A model, a case study and crisis management policiesKara Ahmet0Istanbul Commerce University, TurkeyThe purpose of this paper is to (i) demonstrate that the behavior of the relative profit rates at financial crisis junctures in a dual financial system could be different than that of the other periods, (ii) show that relative profit rates (and their dynamics) at crisis junctures could be forecasted with a relatively high degree of accuracy via artificial intelligence algorithms and (iii) exemplify the possibility of crisis-management policies that can smoothen the trajectory of the relative profit rates and facilitate the control of possible erratic fluctuations at the crisis junctures in such systems. We employ a series of methodological tools involving (i) statistical tests, (ii) artificial intelligence algorithms and (iii) the system dynamics simulation method to achieve the three objectives outlined in the paragraph above. The results are of practical significance to the financial policy makers aiming to formulate and put in practice effective policies at crisis junctures.https://doi.org/10.2478/fiqf-2025-0002dual financial systemsdynamics of relative profit ratesartificial-intelligence-based– forecastingcrisis juncturescrisis managementg1c6
spellingShingle Kara Ahmet
An artificial intelligence-based forecasting of the dynamics of relative profit rates at a financial crisis juncture: A model, a case study and crisis management policies
Financial Internet Quarterly
dual financial systems
dynamics of relative profit rates
artificial-intelligence-based– forecasting
crisis junctures
crisis management
g1
c6
title An artificial intelligence-based forecasting of the dynamics of relative profit rates at a financial crisis juncture: A model, a case study and crisis management policies
title_full An artificial intelligence-based forecasting of the dynamics of relative profit rates at a financial crisis juncture: A model, a case study and crisis management policies
title_fullStr An artificial intelligence-based forecasting of the dynamics of relative profit rates at a financial crisis juncture: A model, a case study and crisis management policies
title_full_unstemmed An artificial intelligence-based forecasting of the dynamics of relative profit rates at a financial crisis juncture: A model, a case study and crisis management policies
title_short An artificial intelligence-based forecasting of the dynamics of relative profit rates at a financial crisis juncture: A model, a case study and crisis management policies
title_sort artificial intelligence based forecasting of the dynamics of relative profit rates at a financial crisis juncture a model a case study and crisis management policies
topic dual financial systems
dynamics of relative profit rates
artificial-intelligence-based– forecasting
crisis junctures
crisis management
g1
c6
url https://doi.org/10.2478/fiqf-2025-0002
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