Bagging ensemble models for bank profitability: An emprical research on Turkish development and investment banks |
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| Affiliation: | 1. Ataturk University, Institude of Social Sciences, 25240, Erzurum, Turkey;2. Development Bank of Turkey, Ankara, Turkey;1. Department of Chemical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia;2. Duy Tân University, 254 Nguyen Van Linh Road, Da Nang, Viet Nam;3. ICTEAM, Université Catholique de Louvain, 4-6 Avenue G. Lemaître, B-1348 Louvain-La-Neuve, Belgium;1. Instituto de Computación, Facultad de Ingeniería, Universidad de la República, Julio Herrera y Reissig 565, 11300 Montevideo, Uruguay;2. Depto. de Lenguajes y Ciencias de la Computación, Univ. de Málaga, E.T.S. Ingeniería Informática, Campus de Teatinos, 29071 Málaga, Spain;1. Computer Science & Engineering Department, American University of Sharjah, P.O. Box 26666, Sharjah, United Arab Emirates;2. Computer Science & Engineering Department, American University of Sharjah, Sharjah, United Arab Emirates;3. University of Science and Technology Houari Boumediene, Algeria;4. Tomsk State University, Russia;1. Institute of Applied Mathematics and Information Technologies, CNR-IMATI, via Bassini 15, 20133 Milan, Italy;2. European Centre for Living Technology, Ca’ Foscari University of Venice, San Marco 2940, 30124 Venice, Italy;3. Department of Environmental Science, Informatics and Statistics, Ca’ Foscari University of Venice, Dorsoduro 2137, 30123 Venice, Italy;4. Department of Biology, University of Padua, Via U. Bassi 58, 35121 Padua, Italy;5. Explora Biotech S.r.l., Via della Libertá 9, 30175 Venice, Italy |
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| Abstract: | The purpose of this study is to find the determinants of the profits for the Development and Investment Banks (IaDB) in Turkey. In Turkish Banking System, the main financial source of the banks is the deposits, which constitute almost%60 of the balance sheet. As being a sub-group of the banking system, IaDB are not allowed to accept deposits in Turkey, which changes the total structure of the profitability compared to other banks. Till today, none of the relevant research was concentrated on the profit structure of the IaDB neither in Turkey nor in any other countries. Such research would fill that unexpectedly disregarded yet highly important gap.Therefore, to address this gap, quarterly financial data (10 balance sheet ratios) of 13 banks in the period of 2002Q4-2014Q3 were utilized. As a profit measurement among all other available measures, Return on Equity was chosen as dependent variable as it was the most used one as well as many other researcher have preferred as well. This study investigates the potential usage of bagging (Bag), which is one of the most popular ensemble learning methods, in building ensemble models, is used to predict the determinants of Turkish IaDB profitability. Three well-known tree-based machine learning (ML) models (i.e., Decision Stump (DStump), Random Tree (RTree), Reduced Error Pruning Tree (REPTree)) are deployed as base learner. This empirical study indicates that bagging ensemble models (i.e., Bag-DStump, Bag-RTree, Bag-MLP and Bag-REPTree) are superior to their base learners and could improve the prediction accuracy of individual ML models (i.e., DStump, RTree, REPTree). |
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| Keywords: | Bagging (bootstrap aggregating) Ensemble machine learning Decision stump Random tree Reduced error pruning tree Development and investment banks |
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