Risk and Asset Allocation

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 hypothes...

সম্পূর্ণ বিবরণ

সংরক্ষণ করুন:
গ্রন্থ-পঞ্জীর বিবরন
প্রধান লেখক: Meucci, Attilio
বিন্যাস: Livre numérique
ভাষা:Anglais
প্রকাশিত: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
সংস্করন:1st ed. 2005.
মালা:Springer Finance Textbooks
অনলাইন ব্যবহার করুন:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
টীকা: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Risk and asset allocation, Attilio Meucci, Berlin, Springer, 2005, 1 volume (xxvi-532 pages), Springer finance, 3-540-22213-8
• Risk and asset allocation, Attilio Meucci, 2009, New York, Springer, 1 vol. (XXVI-532 p.), Springer finance, 978-3-642-00964-8
• Risk and Asset Allocation, Texte imprimé, 9783540802235
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505 1 |a The statistics of asset allocation Univariate statistics Multivariate statistics Modeling the market Classical asset allocation Estimating the distribution of the market invariants Evaluating allocations Optimizing allocations Accounting for estimation risk Estimating the distribution of the market invariants Evaluating allocations Optimizing allocations 
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520 |a 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., in addition to very general multivariate Bayesian techniques. 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. Comprehension is supported by a large number of practical examples, real trading and asset management case studies, figures, geometrical arguments and MATLAB® applications, which can be freely downloaded from symmys.com 
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