Linear and Mixed Integer Programming for Portfolio Optimization

✍ Scribed by Renata Mansini, Włodzimierz Ogryczak, M. Grazia Speranza (auth.)

• Publisher: Springer International Publishing
• Year: 2015
• Tongue: English
• Leaves: 131
• Series: EURO Advanced Tutorials on Operational Research
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xii
Portfolio Optimization....Pages 1-18
Linear Models for Portfolio Optimization....Pages 19-45
Portfolio Optimization with Transaction Costs....Pages 47-62
Portfolio Optimization with Other Real Features....Pages 63-72
Rebalancing and Index Tracking....Pages 73-86
Theoretical Framework....Pages 87-96
Computational Issues....Pages 97-114
Back Matter....Pages 115-119

✦ Subjects

Operation Research/Decision Theory; Finance/Investment/Banking; Quantitative Finance; Operations Research, Management Science