Linear and mixed integer programming for portfolio optimization [electronic resource] / Renata Mansini, Włodzimierz Ogryczak, M. Grazia Speranza.
2015
HG4529.5
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Title
Linear and mixed integer programming for portfolio optimization [electronic resource] / Renata Mansini, Włodzimierz Ogryczak, M. Grazia Speranza.
Author
ISBN
9783319184821 electronic book
3319184822 electronic book
9783319184814
3319184822 electronic book
9783319184814
Published
Cham : Springer, 2015.
Language
English
Description
1 online resource (xii, 119 pages) : illustrations.
Item Number
10.1007/978-3-319-18482-1 doi
Call Number
HG4529.5
Dewey Decimal Classification
332.601/5118
Summary
This book presents solutions to the general problem of single period portfolio optimization. It introduces different linear models, arising from different performance measures, and the mixed integer linear models resulting from the introduction of real features. Other linear models, such as models for portfolio rebalancing and index tracking, are also covered. The book discusses computational issues and provides a theoretical framework, including the concepts of risk-averse preferences, stochastic dominance and coherent risk measures. The material is presented in a style that requires no background in finance or in portfolio optimization; some experience in linear and mixed integer models, however, is required. The book is thoroughly didactic, supplementing the concepts with comments and illustrative examples.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed June 18, 2015).
Series
EURO Advanced Tutorials on Operational Research.
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Table of Contents
Portfolio optimization
Linear models for portfolio optimization
Portfolio optimization with transaction costs
Portfolio optimization with other real features
Rebalancing and index tracking
Theoretical framework
Computational issues.
Linear models for portfolio optimization
Portfolio optimization with transaction costs
Portfolio optimization with other real features
Rebalancing and index tracking
Theoretical framework
Computational issues.