Atnaujinkite slapukų nuostatas

Data Science and Multiple Criteria Decision Making Approaches in Finance: Applications and Methods 2021 ed. [Kietas viršelis]

, ,
  • Formatas: Hardback, 173 pages, aukštis x plotis: 235x155 mm, weight: 459 g, 14 Illustrations, black and white; XVI, 173 p. 14 illus., 1 Hardback
  • Serija: Multiple Criteria Decision Making
  • Išleidimo metai: 30-May-2021
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 3030741753
  • ISBN-13: 9783030741754
Kitos knygos pagal šią temą:
Data Science and Multiple Criteria Decision Making Approaches in Finance: Applications and Methods 2021 ed.Didesnis paveikslėlis
  • Formatas: Hardback, 173 pages, aukštis x plotis: 235x155 mm, weight: 459 g, 14 Illustrations, black and white; XVI, 173 p. 14 illus., 1 Hardback
  • Serija: Multiple Criteria Decision Making
  • Išleidimo metai: 30-May-2021
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 3030741753
  • ISBN-13: 9783030741754
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9783030741754.html
Raktažodžiai:
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.
1 Introduction to Data Science and Machine Learning Algorithms
1(16)
1.1 Artificial Neural Networks
1(1)
1.1.1 A Few Concrete Examples
2(1)
1.2 Neural Network Elements
2(2)
1.3 Hyper Parameters of Deep Neural Networks
4(1)
1.4 Support Vector Machine
4(3)
1.5 Kernel
7(1)
1.6 Regularization
7(1)
1.7 Gamma
8(1)
1.8 Margin
8(1)
1.9 Decision Trees
9(1)
1.10 Sample Decision Tree
10(1)
1.11 Testing Learning
11(1)
1.12 Text Mining
12(2)
Appendix
14(1)
References
15(2)
2 Identifying Indicators of Global Financial Crisis with Fuzzy Logic and Data Science: A Comparative Analysis Between Developing and Developed Economies
17(38)
2.1 Introduction
17(1)
2.2 General Information About the Financial Crises and 2008 Global Mortgage Crisis
18(3)
2.2.1 Types of the Financial Crises
18(2)
2.2.2 2008 Global Financial Crisis
20(1)
2.3 Literature Review
21(2)
2.4 An Application on Turkish Banking Industry
23(7)
2.4.1 Data Set and Variables
23(1)
2.4.2 Fuzzy DEMATEL
23(4)
2.4.3 Analysis Results
27(3)
2.5 Conclusion
30(1)
Appendix 1
31(1)
Appendix 2
31(16)
References
47(8)
3 Determining the Ways to Increase Economic Growth of Developing and Developed Economies: An Application with Data Mining and Fuzzy TOPSIS
55(22)
3.1 Introduction
55(1)
3.2 Literature Review
56(2)
3.3 An Application on Developing and Developed Economies
58(3)
3.3.1 Data Set and Variables
58(1)
3.3.2 Fuzzy TOPSIS
59(1)
3.3.3 Analysis Results
60(1)
3.4 Conclusion
61(1)
Appendix 1
62(1)
Appendix 2
63(8)
References
71(6)
4 Profitability Prediction of Turkish Banking Industry: A Comparative Analysis with Data Science and Fuzzy ANP
77(32)
4.1 Introduction
77(2)
4.2 Literature Review
79(1)
4.3 An Application on Turkish Banking Industry
80(7)
4.3.1 Data Set and Variables
80(2)
4.3.2 Fuzzy ANP
82(2)
4.3.3 Analysis Results
84(3)
4.4 Conclusion
87(1)
Appendix 1
88(1)
Appendix 2
89(14)
Analysis Details of Decision Tree Approach
89(14)
References
103(6)
5 The Influence of the Politicians on Macroeconomic Performance: An Analysis of Donald Trump's Tweets
109(20)
5.1 Introduction
109(2)
5.2 Literature Review
111(1)
5.3 An Application on Donald Trump's Tweets
112(5)
5.3.1 Fuzzy VIKOR
112(1)
5.3.2 Analysis Results
113(4)
5.4 Conclusion t~
117(1)
Appendix 1
118(1)
Appendix 2
118(5)
References
123(6)
6 How Is the Stock Exchange Index Affected by the Disclosures of Politicians?
129(16)
6.1 Introduction
129(1)
6.2 Literature Review
130(3)
6.3 The Analysis of the Impacts of Donald Trump's Tweets on Dow Jones Index
133(6)
6.4 Conclusion
139(1)
Appendix
140(1)
References
140(5)
7 Defining the Significant Factors of Currency Exchange Rate Risk by Considering Text Mining and Fuzzy AHP
145(24)
7.1 Introduction
145(2)
7.2 Literature Review
147(1)
7.3 Fuzzy AHP
148(2)
7.4 The Analysis on the Journals Reviewed in Sciencedirect
150(1)
7.5 Conclusion
151(3)
Appendix 1
154(1)
Appendix 2
155(10)
References
165(4)
8 Emerging Applications and the Future of Data Science
169(4)
8.1 Building an Effective Data Science Team
169(1)
8.2 Examining Social Media
170(1)
8.3 Data Program
170(1)
8.4 Conclusion
171(1)
Appendix
172(1)
Index 173
Gökhan Silahtarolu 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. Silahtarolu received his PhD in management sciences and quantitative methods from Istanbul University in 2005.





Hasan Dinēer 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.