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  • 标题:Westerlund and Narayan predictability test: Step-by-step approach using COVID-19 and oil price data
  • 本地全文:下载
  • 作者:Susan Sunila Sharma
  • 期刊名称:MethodsX
  • 印刷版ISSN:2215-0161
  • 电子版ISSN:2215-0161
  • 出版年度:2021
  • 卷号:8
  • 页码:1-6
  • DOI:10.1016/j.mex.2020.101201
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn 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).Graphical abstractDisplay Omitted
  • 关键词:Predictability;COVID-19;Oil price
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