Westerlund and Narayan predictability test: Step-by-step approach using COVID-19 and oil price data
1Centre for Financial Econometrics & Department of Finance, Faculty of Business and Law, Deakin University, 221 Burwood Highway, Burwood, Victoria 3125, Australia.
Methodsx
|August 26, 2021
Summary
This study applies the Westerlund and Narayan (WN) predictability test to COVID-19 and oil prices, finding they do not significantly predict stock returns in most Asian countries, except South Korea.
Area of Science:
- Economics
- Financial econometrics
- Time series analysis
Background:
- Financial markets are influenced by global events and commodity prices.
- Predictability of stock market returns is crucial for investment strategies.
- Existing time series models may not fully capture data complexities like persistency, endogeneity, and heteroskedasticity.
Purpose of the Study:
- To demonstrate a step-by-step application of the Westerlund and Narayan (WN) predictability test.
- To assess the predictive power of COVID-19 and oil prices on stock market returns in four Asian countries.
- To highlight the WN model's ability to handle complex time series characteristics.
Main Methods:
- Utilized the Westerlund and Narayan (WN) predictability test (2012, 2015).
- Employed COVID-19 and oil price data as predictor variables.
- Analyzed stock market returns for Japan, Russia, Singapore, and South Korea.
Main Results:
- The WN model was applied step-by-step, accommodating persistency, endogeneity, and heteroskedasticity.
- COVID-19 and oil prices showed no significant predictive power for stock returns in Japan, Russia, and Singapore.
- A significant predictive relationship was observed for South Korea.
Conclusions:
- The WN test provides a robust framework for analyzing time series predictability.
- COVID-19 and oil price impacts on stock markets vary across Asian economies.
- Further research may explore other macroeconomic factors and advanced time series methodologies.
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