Practical Financial Optimization
A Library of GAMS Models
von Soren S Nielson und Andrea Consiglio, herausgegeben von Stavros A. ZeniosIn Practical Financial Optimization: A Library of GAMSModels, the authors provide a diverse set of models forportfolio optimization, based on the General Algebraic ModellingSystem. 'GAMS' consists of a language which allows ahigh-level, algebraic representation of mathematical models and aset of solvers - numerical algorithms - to solve them. The system was developed in response to the need for powerful andflexible front-end tools to manage large, real-life models.
The work begins with an overview of the structure of the GAMSlanguage, and discusses issues relating to the management of datain GAMS models. The authors provide models for mean-varianceportfolio optimization which address the question of trading offthe portfolio expected return against its risk. Fixed incomeportfolio optimization models perform standard calculations andallow the user to bootstrap a yield curve from bond prices. Dedication models allow for standard portfolio dedication withborrowing and re-investment decisions, and are extended to dealwith maximisation of horizon return and to incorporate variouspractical considerations on the portfolio tradeability. Immunization models provide for the factor immunization ofportfolios of treasury and corporate bonds.
The scenario-based portfolio optimization problem is addressedwith mean absolute deviation models, tracking models, regretmodels, conditional VaR models, expected utility maximizationmodels and put/call efficient frontier models. The authors employstochastic programming for dynamic portfolio optimization, developing stochastic dedication models as stochastic extensions ofthe fixed income models discussed in chapter 4. Two-stage andmulti-stage stochastic programs extend the scenario models analysedin Chapter 5 to allow dynamic rebalancing of portfolios as timeevolves and new information becomes known. Models for structuringindex funds and hedging interest rate risk on internationalportfolios are also provided.
The final chapter provides a set of 'case studies': models for large-scale applications of portfolio optimization, which can be used as the basis for the development of businesssupport systems to suit any special requirements, including modelsfor the management of participating insurance policies and personalasset allocation.
The title will be a valuable guide for quantitative developersand analysts, portfolio and asset managers, investment strategistsand advanced students of finance.
The work begins with an overview of the structure of the GAMSlanguage, and discusses issues relating to the management of datain GAMS models. The authors provide models for mean-varianceportfolio optimization which address the question of trading offthe portfolio expected return against its risk. Fixed incomeportfolio optimization models perform standard calculations andallow the user to bootstrap a yield curve from bond prices. Dedication models allow for standard portfolio dedication withborrowing and re-investment decisions, and are extended to dealwith maximisation of horizon return and to incorporate variouspractical considerations on the portfolio tradeability. Immunization models provide for the factor immunization ofportfolios of treasury and corporate bonds.
The scenario-based portfolio optimization problem is addressedwith mean absolute deviation models, tracking models, regretmodels, conditional VaR models, expected utility maximizationmodels and put/call efficient frontier models. The authors employstochastic programming for dynamic portfolio optimization, developing stochastic dedication models as stochastic extensions ofthe fixed income models discussed in chapter 4. Two-stage andmulti-stage stochastic programs extend the scenario models analysedin Chapter 5 to allow dynamic rebalancing of portfolios as timeevolves and new information becomes known. Models for structuringindex funds and hedging interest rate risk on internationalportfolios are also provided.
The final chapter provides a set of 'case studies': models for large-scale applications of portfolio optimization, which can be used as the basis for the development of businesssupport systems to suit any special requirements, including modelsfor the management of participating insurance policies and personalasset allocation.
The title will be a valuable guide for quantitative developersand analysts, portfolio and asset managers, investment strategistsand advanced students of finance.
