Data science and multiple criteria decision making approaches in finance : applications and methods
Author(s)
Bibliographic Information
Data science and multiple criteria decision making approaches in finance : applications and methods
（Multiple criteria decision making / series editor, Constantin Zopounidis）
Springer, c2021
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
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
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.
by "Nielsen BookData"