Calculating Value-at-Risk for high-dimensional time series using a nonlinear random mapping model-Reference-Cited by-同舟云学术

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Calculating Value-at-Risk for high-dimensional time series using a nonlinear random mapping model

Published:2017-12 Issue: Volume:67 Page:355-367
ISSN:0264-9993
Container-title:Economic Modelling
language:en
Short-container-title:Economic Modelling

Author:

Zhang Heng-Guo,Su Chi-Wei,Song Yan,Qiu Shuqi,Xiao Ran,Su Fei

Funder

National Social Science Foundation

Ministry of Education's Humanities and Social Science Research Project

Publisher

Elsevier BV

Subject

Economics and Econometrics

Reference57 articles.

1. A comprehensive review of value at risk methodologies;Abad;Span. Rev. Financ. Econ.,2014

2. Hybridizing extreme learning machines and genetic algorithms to select acoustic features in vehicle classification applications;Alexandre;Neurocomputing,2015

3. The use of garch models in var estimation;Angelidis;Stat. Methodol.,2004

4. Long memory and structural breaks in modeling the return and volatility dynamics of precious metals;Arouri;Q. Rev. Econ. Financ.,2012

5. Structural breaks and garch models of stock return volatility: the case of south africa;Babikir;Econ. Model.,2012

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