Data Science and Multiple Criteria Decision Making Approaches in Finance
Applications and Methods
(Sprache: Englisch)
This book considers and assesses essential financial issues by utilizing data science and fuzzy multiple criteria decision making (MCDM) methods. It introduces readers to a range of data science methods, and demonstrates their application in the fields of...
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Klappentext zu „Data Science and Multiple Criteria Decision Making Approaches in Finance “
This book considers and assesses essential financial issues by utilizing data science and fuzzy multiple criteria decision making (MCDM) methods. It introduces readers to a range of data science methods, and demonstrates their application in the fields of business, health, economics, finance and engineering. In addition, it provides suggestions based on the assessment results on each topic, which can help to enhance the efficiency of the financial system and the sustainability of economic development. Given its scope, the book will help readers broaden their perspective on the assessment and evaluation of financial issues using data science and MCDM approaches.
Inhaltsverzeichnis zu „Data Science and Multiple Criteria Decision Making Approaches in Finance “
1. Introduction to Data Science and Machine Learning Algorithms.- 2. Identifying Indicators of Global Financial Crisis with Fuzzy Logic and Data Science: A Comparative Analysis between Developing and Developed Economies.- 3. Determining the Ways to Increase Economic Growth of Developing and Developed Economies: An Application with Data Mining and Fuzzy TOPSIS.- 4. Profitability Prediction of Turkish Banking Industry: A Comparative Analysis with Data Science and Fuzzy ANP.- 5. The Influence of the Politicians on Macroeconomic Performance: An Analysis of Donald Trump's Tweets.- 6. How is the Stock Exchange Index Affected by the Disclosures of Politicians?.- 7. Defining the Significant Factors of Currency Exchange Rate Risk by Considering Text Mining and Fuzzy AHP.- 8. Emerging Applications and the Future of Data Science.
Autoren-Porträt von Gökhan Silahtaroglu, Hasan Dinçer, Serhat Yüksel
Gökhan Silahtaroglu is a Professor of Data Science andHead of the Department of Management Information Systems, Faculty of Economics and Administrative Sciences, Istanbul Medipol University (Turkey). Dr. Silahtaroglu received his PhD in management sciences and quantitative methods from Istanbul University in 2005.Hasan Dinçer is a Professor of Finance at the Faculty of Economics and Administrative Sciences, Istanbul Medipol University (Turkey). He has more than 150 scientific articles to his credit, many of which are indexed in SSCI, SCI-Expanded and Scopus. He is also the editor of numerous books published by Springer and IGI Global.
Serhat Yüksel is an Associate Professor of Finance at the Faculty of Economics and Administrative Sciences, Istanbul Medipol University (Turkey). He has more than 150 scientific articles, many of which are indexed in SSCI, SCI-Expanded and Scopus, to his credit. He is also the editor of various books published by Springer and IGI Global.
Bibliographische Angaben
- Autoren: Gökhan Silahtaroglu , Hasan Dinçer , Serhat Yüksel
- 2022, 1st ed. 2021, XVI, 173 Seiten, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3030741788
- ISBN-13: 9783030741785
Sprache:
Englisch
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