sharma-westerlundandnarayan-2021.pdf (280.18 kB)
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 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).
• 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).
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Journal
MethodsXVolume
8Issue
Issue in ProgressArticle number
101201Publisher
Elsevier BVLocation
Amsterdam, NetherlandsPublisher DOI
Link to full text
ISSN
2215-0161eISSN
2215-0161Language
engPublication classification
C1 Refereed article in a scholarly journal; C Journal articleCopyright notice
2020, The AuthorUsage metrics
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