Gökhan Silahtaroğlu - Data Science and Multiple Criteria Decision Making Approaches in Finance: Applications and Methods

This book series focuses on the publication of monographs and edited volumes of wide interest for researchers and practitioners interested in the theory of multicriteria analysis and its applications in management and engineering. The book series publishes novel works related to the foundations and the methodological aspects of multicriteria analysis, its applications in different areas in management and engineering, as well as its connections with other quantitative and analytic disciplines. In recent years, multicriteria analysis has been widely used for decision making purposes by institutions and enterprises. Research is also very active in the field, with numerous publications in a wide range of publication outlets and different domains such as operations management, environmental and energy planning, finance and economics, marketing, engineering, and healthcare.

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This book aims to evaluate different financial issues to reach sustainable economic development. In this context, assessments were made on 6 different important issues. In this way, it is aimed to identify the most important issues related to financial issues. In this process, both data science and fuzzy multi-criteria decision-making methods were considered. In this context, decision trees, artificial neural networks, text mining, and methods such as AHP, ANP, DEMATEL, MOORA, TOPSIS, and VIKOR were used. The most important contribution of the study is the use of these methods, which are frequently preferred in the literature, in the same book.

This book aims to integrate data science applications, such as web mining, text mining, and machine learning, with different significant majors like business, health, economics, finance, and engineering. Within this framework, different perspectives can be taken into consideration in this study. For example, machine learning approach can be used to analyze financial performance or big data methodology can be considered to evaluate the efficiency of the stock exchanges. Therefore, it can be said that this study offers a novelty by focusing on various significant majors at the same time. As a result, it is believed that this study makes a significant contribution to the literature.

In this book, detailed analyses are made on 6 different issues related to financial issues. In this context, financially important issues such as profitability in the banking sector, the factors affecting economic development, the role of the statements of the politicians on the financial system, and the factors affecting the exchange rate risk are examined. As a result of detailed analyses, development suggestions were made for each topic. Thanks to these suggestions, it will be possible to reach a more effective financial system and sustainable economic growth. Therefore, this book is intended to make an important contribution to the literature.

The authors would like to acknowledge the help and patience of their families in this book process. Without their support, this book would not have become a reality.

Second, the authors wish to acknowledge the valuable contributions of the reviewers regarding the improvement of quality, coherence, and content presentation of chapters.

In addition, the authors would also like to acknowledge the valuable help of Mr. Serkan Eti for his significant support about machine learning system.

Gkhan Silahtarolu

Hasan Diner

Serhat Yksel

In this book, analyses related to financial issues have been made. In this context, assessments were made on 6 different important issues. In this way, it is aimed to identify the most important issues related to financial issues. In this process, both data science and fuzzy multi-criteria decision-making methods were considered. In this context, decision trees, artificial neural networks, text mining, and methods such as AHP, ANP, DEMATEL, MOORA, TOPSIS, and VIKOR were used. The most important contribution of the study is the use of these methods, which are frequently preferred in the literature, in the same book.

In the study, firstly, the factors causing crises in developing and developed countries have been tried to be determined. In this framework, decision tree and fuzzy DEMATEL approaches are taken into consideration. In addition, the second chapter is related to identifying the influencing factors of economic growth for both developing and developed economies. For this purpose, decision tree approach and fuzzy TOPSIS methodology are considered at the same time.

On the other side, the third chapter aims to estimate the factors affecting the profitability of the Turkish banking sector. For this purpose, 34 different variables were firstly determined by literature review. In the first stage of the analysis, decision trees method is applied to select the most important variables. After that, fuzzy ANP approach is used to weight these variables. Similarly, the fourth chapter tries to understand the role of the politicians on the macroeconomic situation of the countries. For this purpose, the tweets of Donald Trump are taken into consideration. Text mining approach is used to evaluate these tweets and mostly used words are identified. After that, these keywords are ranked with the help of fuzzy VIKOR approach according to their impacts on macroeconomic performance.