大葉大學圖書館 |

Heavy-tailed distributions and robustness in economics and finance[electronic resource] /

纪录类型:	书目-电子资源 : Monograph/item
[NT 15000414] null:	519.24
[NT 47271] Title/Author:	Heavy-tailed distributions and robustness in economics and finance/ by Marat Ibragimov, Rustam Ibragimov, Johan Walden.
作者:	Ibragimov, Marat.
[NT 51406] other author:	Ibragimov, Rustam.
出版者:	Cham : : Springer International Publishing :, 2015.
面页册数:	xiv, 119 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
标题:	Distribution (Probability theory)
标题:	Statistics.
标题:	Statistics for Business/Economics/Mathematical Finance/Insurance.
标题:	Statistical Theory and Methods.
标题:	Econometrics.
ISBN:	9783319168777 (electronic bk.)
ISBN:	9783319168760 (paper)
[NT 15000228] null:	Introduction -- Implications of Heavy-tailed ness -- Inference and Empirical Examples -- Conclusion.
[NT 15000229] null:	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.
电子资源:	http://dx.doi.org/10.1007/978-3-319-16877-7

Heavy-tailed distributions and robustness in economics and finance[electronic resource] /
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:

472330
Distribution (Probability theory)

LC Class. No.: QA273.6

Dewey Class. No.: 519.24

Heavy-tailed distributions and robustness in economics and finance[electronic resource] /
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