ATTILIO MEUCCI RISK AND ASSET ALLOCATION PDF

The final prices may differ from the prices shown due to specifics of VAT rules About this Textbook This encyclopedic, self-contained, detailed exposition spans all the steps of one-period allocation from the basics to the most advanced and recent developments. A variety of multivariate estimation methods are analyzed in depth, including non-parametric, maximum-likelihood under non-normal hypotheses, shrinkage, robust, etc. Evaluation methods such as stochastic dominance, expected utility, value at risk and coherent measures are thoroughly analyzed in a unified setting and applied in a variety of contexts, including total return and benchmark allocation, prospect theory, etc. Portfolio optimization is presented with emphasis on estimation risk, which is tackled by means of Bayesian, resampling and robust optimization techniques. This work is both a reference for practitioners and a textbook for students. The only prerequisites are linear algebra and multivariate calculus.

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The final prices may differ from the prices shown due to specifics of VAT rules About this Textbook This encyclopedic, self-contained, detailed exposition spans all the steps of one-period allocation from the basics to the most advanced and recent developments.

A variety of multivariate estimation methods are analyzed in depth, including non-parametric, maximum-likelihood under non-normal hypotheses, shrinkage, robust, etc. Evaluation methods such as stochastic dominance, expected utility, value at risk and coherent measures are thoroughly analyzed in a unified setting and applied in a variety of contexts, including total return and benchmark allocation, prospect theory, etc.

Portfolio optimization is presented with emphasis on estimation risk, which is tackled by means of Bayesian, resampling and robust optimization techniques. This work is both a reference for practitioners and a textbook for students. The only prerequisites are linear algebra and multivariate calculus.

All the statistical tools, such as copulas, location-dispersion ellipsoids and matrix-variate distribution theory, are introduced from the basics. The same holds for the mathematical machinery, such as computational results from cone programming and heuristic arguments from functional analysis. Attilio Meucci is a vice president at Lehman Brothers, Inc. Previously, the author was a trader at Relative Value International, a hedge fund in Greenwich, CT that trades in equities and fixed-income securities worldwide.

Attilio Meucci is the author of several publications in mathematics and finance and has taught graduate courses on Asset Allocation and Risk Management worldwide. 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.

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! 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. It explains most of the concepts intuitively and with a minimal mathematical machinery.

For students of finance and economics it gives a self-contained overview of the main quantitative concepts in the subject.

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Risk and Asset Allocation

Attilio Meucci is a vice president at Lehman Brothers, Inc. Previously, the author was a trader at Relative Value International, a hedge fund in Greenwich, CT that trades in equities and fixed-income securities worldwide. Attilio Meucci is the author of several publications in mathematics and finance and has taught graduate courses on Asset Allocation and Risk Management worldwide. Inhaltsangabe The statistics of asset allocation. Rezensionen From the reviews: This exciting new book takes a fresh look at asset allocation and offers up a masterly account of this important subject.

7805A JRC PDF

Risk and Asset Allocation

A variety of multivariate estimation methods are analyzed in depth, including non-parametric, maximum-likelihood under non-normal hypotheses, shrinkage, robust, etc. Evaluation methods such as stochastic dominance, expected utility, value at risk and coherent measures are thoroughly analyzed in a unified setting and applied in a variety of contexts, including total return and benchmark allocation, prospect theory, etc. Portfolio optimization is presented with emphasis on estimation risk, which is tackled by means of Bayesian, resampling and robust optimization techniques. This work is both a reference for practitioners and a textbook for students.

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Attilio Meucci

Multivariate estimation methods are analyzed in depth, including non-parametric, maximum-likelihood under non-normal hypotheses, shrinkage, robust, and very general Bayesian techniques. Evaluation methods such as stochastic dominance, This encyclopedic, detailed exposition spans all the steps of one-period allocation from the foundations to the most advanced developments. Evaluation methods such as stochastic dominance, expected utility, value at risk and coherent measures are thoroughly discussed in a unified setting and applied in a variety of contexts, including prospect theory, total return and benchmark allocation. Portfolio optimization is presented with emphasis on estimation risk, which is tackled by means of Bayesian, resampling and robust optimization techniques.

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