Time-varying granger causality tests for applications in global crude oil markets: a study on the DCC-MGARCH Hong test

  • Analysing causality among oil prices and, in general, among financial and economic variables is of central relevance in applied economics studies. The recent contribution of Lu et al. (2014) proposes a novel test for causality— the DCC-MGARCH Hong test. We show that the critical values of the test statistic must be evaluated through simulations, thereby challenging the evidence in papers adopting the DCC-MGARCH Hong test. We also note that rolling Hong tests represent a more viable solution in the presence of short-lived causality periods.

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Author:Massimiliano CaporinORCiDGND, Michele CostolaORCiD
URN:urn:nbn:de:hebis:30:3-616382
URL:https://ssrn.com/abstract=3941778
Parent Title (English):SAFE working paper ; No. 324
Series (Serial Number):SAFE working paper (324)
Publisher:SAFE
Place of publication:Frankfurt am Main
Document Type:Working Paper
Language:English
Date of Publication (online):2021/10/14
Date of first Publication:2021/10/14
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2021/10/18
Tag:COVID-19; DCC-GARCH; Granger Causality; Hong test; Oil market
Page Number:33
HeBIS-PPN:487404424
Institutes:Wirtschaftswissenschaften / Wirtschaftswissenschaften
Wissenschaftliche Zentren und koordinierte Programme / House of Finance (HoF)
Wissenschaftliche Zentren und koordinierte Programme / Center for Financial Studies (CFS)
Wissenschaftliche Zentren und koordinierte Programme / Sustainable Architecture for Finance in Europe (SAFE)
Dewey Decimal Classification:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
JEL-Classification:C Mathematical and Quantitative Methods / C1 Econometric and Statistical Methods: General / C10 General
C Mathematical and Quantitative Methods / C1 Econometric and Statistical Methods: General / C13 Estimation
C Mathematical and Quantitative Methods / C3 Multiple or Simultaneous Equation Models / C32 Time-Series Models; Dynamic Quantile Regressions (Updated!)
Sammlungen:Universitätspublikationen
Licence (German):License LogoDeutsches Urheberrecht