Practical Financial Optimization / Wiley Finance Series (ePub)

In Practical Financial Optimization: A Library of GAMS
Models, the authors provide a diverse set of models for
portfolio optimization, based on the General Algebraic Modelling
System. 'GAMS' consists of a language which allows a
high-level, algebraic representation of mathematical models and a
set of solvers - numerical algorithms - to solve them.
The system was developed in response to the need for powerful and
flexible front-end tools to manage large, real-life models.

The work begins with an overview of the structure of the GAMS
language, and discusses issues relating to the management of data
in GAMS models. The authors provide models for mean-variance
portfolio optimization which address the question of trading off
the portfolio expected return against its risk. Fixed income
portfolio optimization models perform standard calculations and
allow the user to bootstrap a yield curve from bond prices.
Dedication models allow for standard portfolio dedication with
borrowing and re-investment decisions, and are extended to deal
with maximisation of horizon return and to incorporate various
practical considerations on the portfolio tradeability.
Immunization models provide for the factor immunization of
portfolios of treasury and corporate bonds.

The scenario-based portfolio optimization problem is addressed
with mean absolute deviation models, tracking models, regret
models, conditional VaR models, expected utility maximization
models and put/call efficient frontier models. The authors employ
stochastic programming for dynamic portfolio optimization,
developing stochastic dedication models as stochastic extensions of
the fixed income models discussed in chapter 4. Two-stage and
multi-stage stochastic programs extend the scenario models analysed
in Chapter 5 to allow dynamic rebalancing of portfolios as time
evolves and new information becomes known. Models for structuring
index funds and hedging interest rate risk on international
portfolios 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 business
support systems to suit any special requirements, including models
for the management of participating insurance policies and personal
asset allocation.

The title will be a valuable guide for quantitative developers
and analysts, portfolio and asset managers, investment strategists
and advanced students of finance.