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Heavy-tailed distributions and robustness in economics and finance / Marat Ibragimov, Rustam Ibragimov and Johan Walden.

By: Contributor(s): Series: Lecture notes in statistics ; 214.Publication details: Switzerland : Springer, 2015.Description: xiv, 119 p. : illustrations ; 24 cmISBN:
  • 9783319168760
Subject(s): DDC classification:
  • 000SA.031 23 Ib14
Contents:
1. Introduction -- 2. Implications of Heavy-tailedness -- 3. Inference and Empirical Examples-- Bibliography.
Summary: This book focuses on general frameworks for modeling heavy-tailed distributions in economics, finance, econometrics, statistics, risk management and insurance. A central theme is that of (non-)robustness, i.e., the fact that the presence of heavy tails can either reinforce or reverse the implications of a number of models in these fields, depending on the degree of heavy-tailedness. These results motivate the development and applications of robust inference approaches under heavy tails, heterogeneity and dependence in observations. Several recently developed robust inference approaches are discussed and illustrated, together with applications.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 000SA.031 Ib14 (Browse shelf(Opens below)) Available 136449
Total holds: 0

Includes bibliographical references.

1. Introduction --
2. Implications of Heavy-tailedness --
3. Inference and Empirical Examples--
Bibliography.

This book focuses on general frameworks for modeling heavy-tailed distributions in economics, finance, econometrics, statistics, risk management and insurance. A central theme is that of (non-)robustness, i.e., the fact that the presence of heavy tails can either reinforce or reverse the implications of a number of models in these fields, depending on the degree of heavy-tailedness. These results motivate the development and applications of robust inference approaches under heavy tails, heterogeneity and dependence in observations. Several recently developed robust inference approaches are discussed and illustrated, together with applications.

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