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Westerlund and Narayan predictability test: Step-by-step approach using COVID-19 and oil price data

In this note, we provide a step-by-step approach of Westerlund and Narayan (WN, 2012, 2015) predictability test using COVID-19 and oil price data. This is an important exercise because the WN model addresses three salient features of time series data, namely persistency, endogeneity and heteroskedas...

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Detalles Bibliográficos
Autor principal: Sharma, Susan Sunila
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374153/
https://www.ncbi.nlm.nih.gov/pubmed/34434725
http://dx.doi.org/10.1016/j.mex.2020.101201
Descripción
Sumario:In this note, we provide a step-by-step approach of Westerlund and Narayan (WN, 2012, 2015) predictability test using COVID-19 and oil price data. This is an important exercise because the WN model addresses three salient features of time series data, namely persistency, endogeneity and heteroskedasticity. We consider COVID-19 and oil price data as predictors of stock market returns for four Asian countries to demonstrate the applicability of the WN (2012, 2015) predictability approach. • This note demonstrates a step-by-step approach of the WN (2012, 2015) predictability test. • WN model accommodates three salient features of time-series data, namely persistency, endogeneity, and heteroskedasticity. • COVID-19 and oil price does not significantly predict stock returns of Japan, Russia, and Singapore (except in the case of South Korea).