Modern Portfolio Optimization with Nuopt(tm), S-Plus(r), and S+bayes(tm)

ISBN-13: 9780387210162 / Angielski / Twarda / 2005 / 406 str.

Bernd Scherer; R. Douglas Martin

Opis

In recent years portfolio optimization and construction methodologies have become an increasingly critical ingredient of asset and fund management, while at the same time portfolio risk assessment has become an essential ingredient in risk management, and this trend will only accelerate in the coming years. Unfortunately there is a large gap between the limited treatment of portfolio construction methods that are presented in most university courses with relatively little hands-on experience and limited computing tools, and the rich and varied aspects of portfolio construction that are used in practice in the finance industry. Current practice demands the use of modern methods of portfolio construction that go well beyond the classical Markowitz mean-variance optimality theory and require the use of powerful scalable numerical optimization methods. This book fills the gap between current university instruction and current industry practice by providing a comprehensive computationally-oriented treatment of modern portfolio optimization and construction methods. The computational aspect of the book is based on extensive use of S-Plus(R), the S+NuOPT(TM) optimization module, the S-Plus Robust Library and the S+Bayes(TM) Library, along with about 100 S-Plus scripts and some CRSP(R) sample data sets of stock returns. A special time-limited version of the S-Plus software is available to purchasers of this book. "For money managers and investment professionals in the field, optimization is truly a can of worms rather left un-opened, until now Here lies a thorough explanation of almost all possibilities one can think of for portfolio optimization, complete with error estimation techniques and explanation of when non-normality plays a part. A highly recommended and practical handbook for the consummate professional and student alike " Steven P. Greiner, Ph.D., Chief Large Cap Quant & Fundamental Research Manager, Harris Investment Management "The authors take a huge step in the long struggle to establish applied post-modern portfolio theory. The optimization and statistical techniques generalize the normal linear model to include robustness, non-normality, and semi-conjugate Bayesian analysis via MCMC. The techniques are very clearly demonstrated by the extensive use and tight integration of S-Plus software. Their book should be an enormous help to students and practitioners trying to move beyond traditional modern portfolio theory." Peter Knez, CIO, Global Head of Fixed Income, Barclays Global Investors "With regard to static portfolio optimization, the book gives a good survey on the development from the basic Markowitz approach to state of the art models and is in particular valuable for direct use in practice or for lectures combined with practical exercises." Short Book Reviews of the International Statistical Institute, December 2005

Recenzje

From the reviews:

"With regard to static portfolio optimization, the book gives a good survey on the development from the basic Markowitz approach to state of the art models and is in particular valuable for direct use in practice or for lectures combined with practical exercises." Short Book Reviews of the International Statistical Institute,  December 2005

"Portfolio theory deals with how to allocate resources among several alternatives. ... this book will be especially appealing for practitioners and graduate students with an interest in methods. ... this book covers many aspects of modern portfolio theory with the main focus on their implementation in S-PLUS. ... this book contains a variety of valuable tools for the practitioner using S-PLUS." (Matthias Fischer, Statistical Papers, Vol. 48, 2006)

"This book's subtitle, 'With NuOPT^TM , S-PLUS^® and S+ Bayes^TM,' highlights one of its special features. It is loaded with S-PLUS scripts, more than 100 of them. ... The book also features statistical methodology that adds considerably to the tool set that would be traditionally used for portfolio optimization. ... this is definitely an MBA-level textbook." (Technometrics, Vol. 48 (3), August, 2006)

"This book discusses modern portfolio optimization and applications. It is intended for quantitative finance professionals and graduate students in finance, operation research and applied mathematics." (Qin Lu, Zentralblatt MATH, Vol. 1104 (6), 2007)

Spis treści

Linear and Quadratic Programming.- General Optimization With Simple.- Advanced Issues in Mean-Variance Optimization.- Resampling and Portfolio Choice.- Scenario Optimization: Addressing Non-normality.- Robust Statistical Methods for Portfolio Construction.- Bayes Methods.

O autorze

Bernd M. Scherer ist seit 2006 Intendant des Hauses der Kulturen der Welt, Berlin.

Blurb

In recent years portfolio optimization and construction methodologies have become an increasingly critical ingredient of asset and fund management, while at the same time portfolio risk assessment has become an essential ingredient in risk management, and this trend will only accelerate in the coming years. Unfortunately there is a large gap between the limited treatment of portfolio construction methods that are presented in most university courses with relatively little hands-on experience and limited computing tools, and the rich and varied aspects of portfolio construction that are used in practice in the finance industry. Current practice demands the use of modern methods of portfolio construction that go well beyond the classical Markowitz mean-variance optimality theory and require the use of powerful scalable numerical optimization methods. This book fills the gap between current university instruction and current industry practice by providing a comprehensive computationally-oriented treatment of modern portfolio optimization and construction methods. The computational aspect of the book is based on extensive use of S-Plus®, the S+NuOPT™ optimization module, the S-Plus Robust Library and the S+Bayes™ Library, along with about 100 S-Plus scripts and some CRSP® sample data sets of stock returns. A special time-limited version of the S-Plus software is available to purchasers of this book.

"For money managers and investment professionals in the field, optimization is truly a can of worms rather left un-opened, until now! Here lies a thorough explanation of almost all possibilities one can think of for portfolio optimization, complete with error estimation techniques and explanation of when non-normality plays a part. A highly recommended and practical handbook for the consummate professional and student alike!"

Steven P. Greiner, Ph.D.

Chief Large Cap Quant & Fundamental Research Manager

Harris Investment Management

"The authors take a huge step in the long struggle to establish applied post-modern portfolio theory. The optimization and statistical techniques generalize the normal linear model to include robustness, non-normality, and semi-conjugate Bayesian analysis via MCMC. The techniques are very clearly demonstrated by the extensive use and tight integration of S-Plus software. Their book should be an enormous help to students and practitioners trying to move beyond traditional modern portfolio theory."

Peter Knez

CIO, Global Head of Fixed Income

Barclays Global Investors