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

By: Mansini, Renata [author.]Contributor(s): Ogryczak, Włodzimierz [author.] | Speranza, M. Grazia [author.] | SpringerLink (Online service)Material type: TextTextSeries: EURO Advanced Tutorials on Operational ResearchPublication details: 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 resourceISBN: 9783319184821Subject(s): business | Operations research | Decision making | Finance | Economics, Mathematical | Management science | Business and Management | Operation Research/Decision Theory | Finance, general | Quantitative Finance | Operations Research, Management ScienceDDC classification: 658.40301 LOC classification: HD30.23Online resources: Click here to access online
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.
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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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