Synopses & Reviews
Eschewing a more theoretical approach, Portfolio Optimization shows how the mathematical tools of linear algebra and optimization can quickly and clearly formulate important ideas on the subject. This practical book extends the concepts of the Markowitz budget constraint only model to a linearly constrained model.
Only requiring elementary linear algebra, the text begins with the necessary and sufficient conditions for optimal quadratic minimization that is subject to linear equality constraints. It then develops the key properties of the efficient frontier, extends the results to problems with a risk-free asset, and presents Sharpe ratios and implied risk-free rates. After focusing on quadratic programming, the author discusses a constrained portfolio optimization problem and uses an algorithm to determine the entire (constrained) efficient frontier, its corner portfolios, the piecewise linear expected returns, and the piecewise quadratic variances. The final chapter illustrates infinitely many implied risk returns for certain market portfolios.
Drawing on the author 's experiences in the academic world and as a consultant to many financial institutions, this text provides a hands-on foundation in portfolio optimization. Although the author clearly describes how to implement each technique by hand, he includes several MATLAB programs designed to implement the methods and offers these programs on the accompanying CD-ROM.
Synopsis
Eschewing a more theoretical approach, this text provides a practical introduction to basic portfolio optimization models. It focuses on Markowitz mean-variance portfolio optimization. The first chapters include coverage on the derivation of the classical unconstrained efficient frontier, the capital market line, Sharpe ratios, and implied risk-free rates. The author then discusses quadratic and parametric quadratic programming, which is used to implement the theory in practice. MATLABA(R) is included throughout the text in various realistic examples and then employed in the presented problem sets to help with calculations.