Linear and mixed integer programming for portfolio optimization [electronic resource] / Renata Mansini, Włodzimierz Ogryczak, M. Grazia Speranza.
Mansini, Renata, author.; Ogryczak, Włodzimierz, author.; Speranza, M. G. (Maria Grazia), author.
2015
HG4529.5
Available Online

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Title Linear and mixed integer programming for portfolio optimization [electronic resource] / Renata Mansini, Włodzimierz Ogryczak, M. Grazia Speranza.
Author Mansini, Renata, author.
ISBN 9783319184821 electronic book
3319184822 electronic book
9783319184814
DOI https://doi.org/10.1007/978-3-319-18482-1
Published Cham : Springer, 2015.
Language English
Description 1 online resource (xii, 119 pages) : illustrations.
Other Standard Identifiers 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).
Added Author Ogryczak, Włodzimierz, author.
Speranza, M. G. (Maria Grazia), author.
Series EURO Advanced Tutorials on Operational Research.
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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.

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