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Linear and Mixed Integer Programming for Portfolio Optimization [electronic resource] / by Renata Mansini, Włodzimierz Ogryczak, M. Grazia Speranza.

By: Contributor(s): Series: EURO Advanced Tutorials on Operational ResearchPublisher: Cham : Springer International Publishing : Imprint: Springer, 2015Description: XII, 119 p. 25 illus., 12 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319184821
Subject(s): Genre/Form: Additional physical formats: Printed edition:: No titleDDC classification:
  • 658.40301 23
LOC classification:
  • HD30.23
Online resources:
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.
In: Springer eBooksSummary: 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.
Item type: eBooks
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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.

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.

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