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Heavy-Tailed Distributions and Robustness in Economics and Finance

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 implication...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Ibragimov, Marat (Autor), Ibragimov, Rustam (Autor), Walden, Johan (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edición:1st ed. 2015.
Colección:Lecture Notes in Statistics, 214
Temas:
Acceso en línea:Texto Completo

MARC

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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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