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Risk and Asset Allocation (Springer Finance / Springer Finance Textbooks) 1st ed. 2005. Corr. 3rd printing 2009 Edition

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ISBN-13: 978-3642009648
ISBN-10: 3642009646
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Editorial Reviews


From the reviews:

This exciting new book takes a fresh look at asset allocation and offers up a masterly account of this important subject. The quantitative emphasis and included MATLAB software make it a must-read for the mathematically oriented investment professional.

Peter Carr, Head of Quantitative Research, Bloomberg LP, Director of Masters in Mathematical Finance program, NYU

Meucci’s Risk and Asset Allocation is one of those rare books that takes a completely fresh look at a well-studied problem, optimal financial portfolio allocation based on statistically estimated models of risk and expected return. Designed for graduate students or quantitatively oriented asset managers, Meucci provides a sophisticated and integrated treatment, from investment theory, to optimization methods, to statistical analysis of multi-variate return data, through computational implementation of the results. This is rigorous and relevant!

Darrel Duffie, Professor of Graduate Business School, Stanford University

A wonderful book! Mathematically rigorous and yet practical, heavily illustrated with graphs and worked examples, Attilio Meucci has written a comprehensive treatment of asset allocation starting from statistical concepts, covering investment primitives, and leading to portfolio optimization in a Bayesian context with parameter uncertainty.

Bob Litterman, Head of Quantitative Resources, Goldman Sachs Asset Management

This book takes the reader on a journey through portfolio management starting with the basics and reaching some fascinating terrain. Attilio Meucci shows a real talent for explaining the most difficult of subjects in a very clear manner.

Paul Wilmott, wilmott.com

"This book presents a detailed and well-explained introduction to one-period asset allocation techniques … . the book gives an impressive and comprehensive introduction to static one-period asset allocation. It explains most of the concepts intuitively and with a minimal mathematical machinery. … For practitioners, the book serves as a theoretical basis of their actual work. For students of finance and economics it gives a self-contained overview of the main quantitative concepts in the subject." (Ludger Overbeck, SIAM Review, Vol. 48 (3), 2006)

"This book delves into the classical mathematics of portfolio optimization with a few nods to more recent developments in risk measurement such as value-at-risk and copulas. … For anyone with an interest in the mathematics of portfolio optimization, the book is certainly worth a look. … The author covers a wealth of statistical and optimization techniques that are worth reading about." (www.riskbook.com, May, 2006)

"The book offers a wide exposition of the main approaches to asset allocation, starting from the classical models up to the recent developments in portfolio management. … By virtue of the sequential structure of the subjects and the simple but efficacious mathematical treatment, the monograph is useful for graduate students and quantitatively-oriented practitioners too. … The book is complemented by online resources, consisting of software applications performed by MATLAB … ." (Emilia Di Lorenzo, Zentralblatt MATH, Vol. 1102 (4), 2007)

From the Publisher

The author will donate all the proceeds from his royalties to charity, learn more at symmys.com. --This text refers to the Hardcover edition.

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Product Details

  • Series: Springer Finance / Springer Finance Textbooks
  • Paperback: 532 pages
  • Publisher: Springer; 1st ed. 2005. Corr. 3rd printing 2009 edition (May 22, 2009)
  • Language: English
  • ISBN-10: 3642009646
  • ISBN-13: 978-3642009648
  • Product Dimensions: 6.1 x 1.3 x 9.2 inches
  • Shipping Weight: 2 pounds (View shipping rates and policies)
  • Average Customer Review: 4.7 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Best Sellers Rank: #665,423 in Books (See Top 100 in Books)

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Most Helpful Customer Reviews

21 of 23 people found the following review helpful By NY reviewer on August 24, 2010
Format: Paperback
This outstanding book on portfolio theory is a must-have for the professional risk-manager and trader. Note that this bound book is really one of three that Dr. Meucci has written; there is a full-length technical appendix and a full-length problems book that are on-line and free of charge. Also, all of his code is available from the Matlab Central site.

I acknowledge another reviewer's pov that the notation is non-standard, however I have a different reaction. Meucci has designed a notation that uniformly covers what are otherwise highly diverse fields. With this unified notation connections and comparisons are made quickly and effectively across areas that have to date been hard to reconcile. For instance, Chapter 5 on indices of satisfaction: I defy anyone to have a clearer comparison on the certainty equivalent, variance at risk, and coherence measures -- three areas that to my readings of the literature are otherwise unavailable all in one place. As another example: portfolio theory *is* all about multidimensional distributions, and Meucci covers uni- and multi-variate statistics in his first three chapters with deep additions in his technical appendices. Using this as a base it is clear how to construct and forecast the returns on a portfolio.

This book additionally brings robust statistical analysis to the fore. Rather than leaving the reader with a multivariate gaussian models and Markowitz mean-variance optimization Meucci starts in his later chapters a full repeal of these simple approaches and looks both at robust distribution analysis along with robust, or constrained, such as second-order cone programming, analysis of returns and optimization. This is the forefront of risk theory.

Given that Dr.
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26 of 37 people found the following review helpful By Frank Ashe on January 30, 2007
Format: Hardcover
A great book if you have a strong mathematical background. But the question of asset allocation is bedevilled by mathematics which is too strong to support the weak data supplied by the markets in which we invest.

Unless this weak data is properly integrated into the asset allocation process, an area which Meucci spends too little time on, then the users of quantitative procedures will continue to be disappointed.
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1 of 1 people found the following review helpful By E. Lau on March 15, 2014
Format: Hardcover Verified Purchase
With a reasonable math background (calculus and an understanding of linear algebra), this book is extremely informative and useful for anyone trying to get into the quantitative finance area. I would recommend reading "A Primer for the Mathematical Financial Engineering"(http://www.amazon.com/Primer-Mathematics-Financial-Engineering-Edition/dp/0979757622) to get a brief overview of the math required in this book prior if you have not had any experience in the mathematical finance area though.
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Risk and Asset Allocation (Springer Finance / Springer Finance Textbooks)
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