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Heavy-tailed distributions and robus...

Ibragimov, Marat.

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Heavy-tailed distributions and robustness in economics and finance

Record Type:	Electronic resources : Monograph/item
Title/Author:	Heavy-tailed distributions and robustness in economics and finance/ by Marat Ibragimov, Rustam Ibragimov, Johan Walden.
Author:	Ibragimov, Marat.
other author:	Ibragimov, Rustam.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	xiv, 119 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Implications of Heavy-tailed ness -- Inference and Empirical Examples -- Conclusion.
Contained By:	Springer eBooks
Subject:	Distribution (Probability theory) -
Online resource:	http://dx.doi.org/10.1007/978-3-319-16877-7
ISBN:	9783319168777 (electronic bk.)

Heavy-tailed distributions and robustness in economics and finance
Ibragimov, Marat.

Heavy-tailed distributions and robustness in economics and finance[electronic resource] /by Marat Ibragimov, Rustam Ibragimov, Johan Walden. - Cham :Springer International Publishing :2015. - xiv, 119 p. :ill., digital ;24 cm. - Lecture notes in statistics,v.2140930-0325 ;. - Lecture notes in statistics ;205..

Introduction -- Implications of Heavy-tailed ness -- Inference and Empirical Examples -- Conclusion.

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.

ISBN: 9783319168777 (electronic bk.)

Standard No.: 10.1007/978-3-319-16877-7doiSubjects--Topical Terms:

533179
Distribution (Probability theory)

LC Class. No.: QA273.6

Dewey Class. No.: 519.24

Heavy-tailed distributions and robustness in economics and finance
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505 0 $a Introduction -- Implications of Heavy-tailed ness -- Inference and Empirical Examples -- Conclusion.
520 $a 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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