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Multicriteria portfolio construction...

Doukas, Haris.

Multicriteria portfolio construction with Python

Record Type:	Electronic resources : Monograph/item
Title/Author:	Multicriteria portfolio construction with Pythonby Elissaios Sarmas, Panos Xidonas, Haris Doukas.
Author:	Sarmas, Elissaios.
other author:	Xidonas, Panos.
Published:	Cham :Springer International Publishing :2020.
Description:	ix, 176 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Portfolio managementData processing.
Online resource:	https://doi.org/10.1007/978-3-030-53743-2
ISBN:	9783030537432$q(electronic bk.)

Multicriteria portfolio construction with Python
Sarmas, Elissaios.

Multicriteria portfolio construction with Python[electronic resource] /by Elissaios Sarmas, Panos Xidonas, Haris Doukas. - Cham :Springer International Publishing :2020. - ix, 176 p. :ill., digital ;24 cm. - Springer optimization and its applications,v.1631931-6828 ;. - Springer optimization and its applications ;v. 3..

1. Introduction -- 2. The Portfolio Management Problem -- 3. Multicriteria Decision Analysis Methods -- 3. Literature Review -- 5. The Proposed Methodology -- 6. Information System in Python -- 7. Empirical Testing -- 8. Conclusions -- Bibliography.

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.

ISBN: 9783030537432$q(electronic bk.)

Standard No.: 10.1007/978-3-030-53743-2doiSubjects--Topical Terms:

537753
Portfolio management
--Data processing.

LC Class. No.: HG4529.5 / .S276 2020

Dewey Class. No.: 332.60285

Multicriteria portfolio construction with Python
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520 $a 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.
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