Value-at-Risk forecasting: A hybrid ensemble learning GARCH-LSTM based approach-Reference-Cited by-同舟云学术

Value-at-Risk forecasting: A hybrid ensemble learning GARCH-LSTM based approach

Published:2022-09 Issue: Volume:78 Page:102903
ISSN:0301-4207
Container-title:Resources Policy
language:en
Short-container-title:Resources Policy

Author:

Kakade Kshitij^ORCID,Jain Ishan^ORCID,Mishra Aswini Kumar^ORCID

Publisher

Elsevier BV

Subject

Law,Management, Monitoring, Policy and Law,Economics and Econometrics,Sociology and Political Science

Reference63 articles.

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3. Do volatilities matter in the interconnectedness between world energy commodities and stock markets of BRICS?;Amoako;Discrete Dynam. Nat. Soc.,2022

4. Neural networks and value at risk. Michael J. Brennan Irish Finance Working Paper Series Research Paper;Arimond,2020

5. Can crude oil price returns drive stock returns of oil producing countries in Africa? Evidence from bivariate and multiple wavelet;Asafo-Adjei;Macoeconomic. Finance. Emerge Market Economic.,2021

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