Authors:
- Python source code available on GitHub
- Offers a unified methodological framework, integrating multicriteria analysis methods with portfolio management techniques
- Includes an extensive implementation of multicriteria decision analysis methods in Python, bridging the gap between theory and practice
- Provides hands-on learning with illustrative numerical examples for deeper understanding of methods and techniques
- Presents a large scale empirical testing application with real market data and illustrative graphs and figures, documenting the validity of the proposed approach
Part of the book series: Springer Optimization and Its Applications (SOIA, volume 163)
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Table of contents (8 chapters)
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Front Matter
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Back Matter
About this book
This book covers topics in portfolio management and multicriteria decision analysis (MCDA), presenting a transparent and unified methodology for the portfolio construction process. The most important feature of the book includes the proposed methodological framework that integrates two individual subsystems, the portfolio selection subsystem and the portfolio optimization subsystem. An additional highlight of the book includes the detailed, step-by-step implementation of the proposed multicriteria algorithms in Python. The implementation is presented in detail; each step is elaborately described, from the input of the data to the extraction of the results. Algorithms are organized into small cells of code, accompanied by targeted remarks and comments, in order to help the reader to fully understand their mechanics. Readers are provided with a link to access the source code through GitHub.
This Work may also be considered as a reference which presents the state-of-art research on portfolio construction with multiple and complex investment objectives and constraints. The book consists of eight chapters. A brief introduction is provided in Chapter 1. The fundamental issues of modern portfolio theory are discussed in Chapter 2. In Chapter 3, the various multicriteria decision aid methods, either discrete or continuous, are concisely described. In Chapter 4, a comprehensive review of the published literature in the field of multicriteria portfolio management is considered. In Chapter 5, an integrated and original multicriteria portfolio construction methodology is developed. Chapter 6 presents the web-based information system, in which the suggested methodological framework has been implemented. In Chapter 7, the experimental application of the proposed methodology is discussed and in Chapter 8, the authors provide overall conclusions.The readership of the book aims to be a diverse group, including fund managers, risk managers, investment advisors, bankers, private investors, analytics scientists, operations researchers scientists, and computer engineers, to name just several. Portions of the book may be used as instructional for either advanced undergraduate or post-graduate courses in investment analysis, portfolio engineering, decision science, computer science, or financial engineering.
Authors and Affiliations
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Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece
Elissaios Sarmas, Haris Doukas
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ESSCA École de Management, Paris, France
Panos Xidonas
Bibliographic Information
Book Title: Multicriteria Portfolio Construction with Python
Authors: Elissaios Sarmas, Panos Xidonas, Haris Doukas
Series Title: Springer Optimization and Its Applications
DOI: https://doi.org/10.1007/978-3-030-53743-2
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-53742-5Published: 18 October 2020
Softcover ISBN: 978-3-030-53745-6Published: 18 October 2021
eBook ISBN: 978-3-030-53743-2Published: 17 October 2020
Series ISSN: 1931-6828
Series E-ISSN: 1931-6836
Edition Number: 1
Number of Pages: IX, 176
Number of Illustrations: 91 b/w illustrations, 47 illustrations in colour
Topics: Operations Research/Decision Theory, Applications of Mathematics, Mathematical Modeling and Industrial Mathematics