Overview
- Displays recent research on Credible Asset Allocation and Related Topics
- Introduces readers to the theoretical foundations and applications
- Presents edited papers presented at the 15th International Conference of the Thailand Econometric Society
Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 429)
Included in the following conference series:
Conference proceedings info: TES 2022.
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Table of contents (50 papers)
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Front Matter
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Theoretical Results
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Front Matter
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Other volumes
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Credible Asset Allocation, Optimal Transport Methods, and Related Topics
Keywords
About this book
This book describes state-of-the-art economic ideas and how these ideas can be (and are) used to make economic decision (in particular, to optimally allocate assets) and to gauge the results of different economic decisions (in particular, by using optimal transport methods). Special emphasis is paid to machine learning techniques (including deep learning) and to different aspects of quantum econometrics—when quantum physics and quantum computing models are techniques are applied to study economic phenomena. Applications range from more traditional economic areas to more non-traditional topics such as economic aspects of tourism, cryptocurrencies, telecommunication infrastructure, and pandemic. This book helps student to learn new techniques, practitioners to become better knowledgeable of the state-of-the-art econometric techniques, and researchers to further develop these important research directions
Editors and Affiliations
Bibliographic Information
Book Title: Credible Asset Allocation, Optimal Transport Methods, and Related Topics
Editors: Songsak Sriboonchitta, Vladik Kreinovich, Woraphon Yamaka
Series Title: Studies in Systems, Decision and Control
DOI: https://doi.org/10.1007/978-3-030-97273-8
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-97272-1Published: 30 July 2022
Softcover ISBN: 978-3-030-97275-2Published: 30 July 2023
eBook ISBN: 978-3-030-97273-8Published: 29 July 2022
Series ISSN: 2198-4182
Series E-ISSN: 2198-4190
Edition Number: 1
Number of Pages: XI, 773
Number of Illustrations: 39 b/w illustrations, 91 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Economic Theory/Quantitative Economics/Mathematical Methods
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