Modern Portfolio Optimization with NuOPT(TM), S-PLUS®, and S+Bayes(TM)
(Sprache: Englisch)
This practical handbook provides a comprehensive computationally-oriented treatment of modern portfolio optimization and construction methods. It fills the gap between current university instruction and current industry practice.
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Produktinformationen zu „Modern Portfolio Optimization with NuOPT(TM), S-PLUS®, and S+Bayes(TM) “
This practical handbook provides a comprehensive computationally-oriented treatment of modern portfolio optimization and construction methods. It fills the gap between current university instruction and current industry practice.
Klappentext zu „Modern Portfolio Optimization with NuOPT(TM), S-PLUS®, and S+Bayes(TM) “
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. This trend will only accelerate in the coming years. This practical handbook fills the gap between current university instruction and current industry practice. It provides a comprehensive computationally-oriented treatment of modern portfolio optimization and construction methods using the powerful NUOPT for S-PLUS optimizer.
Inhaltsverzeichnis zu „Modern Portfolio Optimization with NuOPT(TM), S-PLUS®, and S+Bayes(TM) “
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.
Autoren-Porträt von Bernd Scherer, R. Douglas Martin
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. This book fills the gap between current university instruction and current industry practice by providing a comprehensive treatment of modern portfolio optimization and construction methods illustrated by using the powerful NUOPT for S-PLUS optimizer and the S-PLUS computing environment for financial analytics on a wide variety of examples.
Bibliographische Angaben
- Autoren: Bernd Scherer , R. Douglas Martin
- 2010, Softcover reprint of hardcover 1st ed. 2005, XXII, 406 Seiten, Masse: 23,7 x 23,5 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 1441919341
- ISBN-13: 9781441919342
Sprache:
Englisch
Pressezitat
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 NuOPTTM , S-PLUS® and S+ BayesTM,' 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)
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