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Banking Profitability, Inflation and GDP Relationship: A Monte Carlo Scenario Analysis for Turkey

https://doi.org/10.47703/ejebs.v69i1.479

Abstract

Economic and political catastrophes have a negative impact on the state budget and the banking industry. The purpose of the study is to assess the impact of macroeconomic factors on the profitability of the Turkish banking sector between 2016 and 2023, using the Monte Carlo method. The study uses the Monte Carlo method with 10, 50 and 100 iterations. The simulation is based on empirical data from the Association of Turkish Banks and the Turkish Statistical Institute, including gross domestic product, inflation, return on equity and return on assets. The results of the study showed that, when using the Monte Carlo model with 100 iterations, the values of ROE and ROA show moderate growth (to an average of 27.68% and 46.94%, respectively) under scenarios of strong economic development, despite the continued instability of inflation, which confirms the presence of stable but sensitive dependencies between variables. According to the findings, there will be no essential changes in the values of the Gross Domestic Product, Inflation values of the state, Return on Equity and Return on Assets values of the banking industry unless correlative relations and volatility (standard deviation) scores can not diminish or balance in 10, 50 and 100 iterations. The importance of macroeconomic variables and globalization is presented as a key factor contributing to this situation. On the other side, the period was very hard for Turkey and the banking industry. In the final section, a brief suggestion will be provided in light of the Monte Carlo Simulation Model algorithms.

 

About the Author

Olcay Ölçen
Aviation Consulting Group, ACG, Florida, United States.
United States

PhD, Email: olcay.olcen@gmail.com



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Ölçen O. Banking Profitability, Inflation and GDP Relationship: A Monte Carlo Scenario Analysis for Turkey. Eurasian Journal of Economic and Business Studies. 2025;69(1):111–125. https://doi.org/10.47703/ejebs.v69i1.479

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