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

✍ Scribed by Gökhan Silahtaroğlu, Hasan Dinçer, Serhat Yüksel

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 183
• Edition: 1st ed. 2021
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Preface
Acknowledgments
Introduction
Contents
About the Authors
Chapter 1: Introduction to Data Science and Machine Learning Algorithms
1.1 Artificial Neural Networks
1.1.1 A Few Concrete Examples
1.2 Neural Network Elements
1.3 Hyper Parameters of Deep Neural Networks
1.4 Support Vector Machine
1.5 Kernel
1.6 Regularization
1.7 Gamma
1.8 Margin
1.9 Decision Trees
1.10 Sample Decision Tree
1.11 Testing Learning
1.12 Text Mining
Appendix
References
Chapter 2: Identifying Indicators of Global Financial Crisis with Fuzzy Logic and Data Science: A Comparative Analysis Between...
2.1 Introduction
2.2 General Information About the Financial Crises and 2008 Global Mortgage Crisis
2.2.1 Types of the Financial Crises
2.2.2 2008 Global Financial Crisis
2.3 Literature Review
2.4 An Application on Turkish Banking Industry
2.4.1 Data Set and Variables
2.4.2 Fuzzy DEMATEL
2.4.3 Analysis Results
2.5 Conclusion
Appendix 1
Appendix 2
References
Chapter 3: Determining the Ways to Increase Economic Growth of Developing and Developed Economies: An Application with Data Mi...
3.1 Introduction
3.2 Literature Review
3.3 An Application on Developing and Developed Economies
3.3.1 Data Set and Variables
3.3.2 Fuzzy TOPSIS
3.3.3 Analysis Results
3.4 Conclusion
Appendix 1
Appendix 2
References
Chapter 4: Profitability Prediction of Turkish Banking Industry: A Comparative Analysis with Data Science and Fuzzy ANP
4.1 Introduction
4.2 Literature Review
4.3 An Application on Turkish Banking Industry
4.3.1 Data Set and Variables
4.3.2 Fuzzy ANP
4.3.3 Analysis Results
4.4 Conclusion
Appendix 1
Appendix 2
Analysis Details of Decision Tree Approach
Analysis for 2017
Analysis for 2016
Analysis for 2015
References
Chapter 5: The Influence of the Politicians on Macroeconomic Performance: An Analysis of Donald Trump´s Tweets
5.1 Introduction
5.2 Literature Review
5.3 An Application on Donald Trump´s Tweets
5.3.1 Fuzzy VIKOR
5.3.2 Analysis Results
5.4 Conclusion
Appendix 1
Appendix 2
References
Chapter 6: How Is the Stock Exchange Index Affected by the Disclosures of Politicians?
6.1 Introduction
6.2 Literature Review
6.3 The Analysis of the Impacts of Donald Trump´s Tweets on Dow Jones Index
6.4 Conclusion
Appendix
References
Chapter 7: Defining the Significant Factors of Currency Exchange Rate Risk by Considering Text Mining and Fuzzy AHP
7.1 Introduction
7.2 Literature Review
7.3 Fuzzy AHP
7.4 The Analysis on the Journals Reviewed in Sciencedirect
7.5 Conclusion
Appendix 1
Appendix 2
References
Chapter 8: Emerging Applications and the Future of Data Science
8.1 Building an Effective Data Science Team
8.2 Examining Social Media
8.3 Data Program
8.4 Conclusion
Appendix
Index