Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Ibragimov, Marat, Ibragimov, Rustam, Walden, Johan
Lenguaje:eng
Publicado: Springer 2015
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-16877-7
http://cds.cern.ch/record/2021028
_version_ 1780946882949808128
author Ibragimov, Marat
Ibragimov, Rustam
Walden, Johan
author_facet Ibragimov, Marat
Ibragimov, Rustam
Walden, Johan
author_sort Ibragimov, Marat
collection CERN
description 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.
id cern-2021028
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2015
publisher Springer
record_format invenio
spelling cern-20210282021-04-21T20:16:43Zdoi:10.1007/978-3-319-16877-7http://cds.cern.ch/record/2021028engIbragimov, MaratIbragimov, RustamWalden, JohanHeavy-tailed distributions and robustness in economics and financeMathematical Physics and MathematicsThis 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.Springeroai:cds.cern.ch:20210282015
spellingShingle Mathematical Physics and Mathematics
Ibragimov, Marat
Ibragimov, Rustam
Walden, Johan
Heavy-tailed distributions and robustness in economics and finance
title Heavy-tailed distributions and robustness in economics and finance
title_full Heavy-tailed distributions and robustness in economics and finance
title_fullStr Heavy-tailed distributions and robustness in economics and finance
title_full_unstemmed Heavy-tailed distributions and robustness in economics and finance
title_short Heavy-tailed distributions and robustness in economics and finance
title_sort heavy-tailed distributions and robustness in economics and finance
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-319-16877-7
http://cds.cern.ch/record/2021028
work_keys_str_mv AT ibragimovmarat heavytaileddistributionsandrobustnessineconomicsandfinance
AT ibragimovrustam heavytaileddistributionsandrobustnessineconomicsandfinance
AT waldenjohan heavytaileddistributionsandrobustnessineconomicsandfinance