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...
Autores principales: | , , |
---|---|
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 |