Author
Listed:
- Raheel Gohar
(College of Business Administration, Al Yamamah University, Riyadh, Saudi Arabia)
- Kashif Bhatty
(Department of Management Sciences, Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology, Larkana, Pakistan)
- Mohamed Osman
(Dubai Business School, University of Dubai Dubai, UAE.)
- Wing-Keung Wong
(Department of Finance, Fintech & Blockchain Research Center, and Big Data Research Center, Asia University, Taiwan. Department of Medical Research, China Medical University Hospital Department of Economics and Finance, The Hang Seng University of Hong Kong)
- Bisharat Hussain Chang
(Department of Business Administration, Sukkur IBA University, Sukkur, Pakistan)
Abstract
[Purpose] Oil prices play an important role in the Pakistani stock market. In this regard, we examine the relationship between oil prices and sectorial stock prices in the context of Pakistan. [Design/methodology/approach] To fulfill the objectives of this study, we use a newly developed methodology called the bootstrap ARDL model. Moreover, we compare the results of the Bootstrap ARDL model with the standard ARDL model. In addition, this study uses Granger Causality in Quantile test to examine the causal relationship among the underlying variables. [Findings] Results indicate that the co-integration exists between oil prices and sectoral stock prices for the Automobile, Cement, and Power Generation and Distribution sectors. However, no co-integration is found for the other sectors. On the contrary, other sectors represent degenerate cases. Moreover, Granger causality is employed to show short-run causality among the given variables. The estimates based on the granger causality test indicate that short-run causality exists between oil prices and most of the sectors. [Originality/Value] Rising oil prices and their effect on stock prices are important concerns in the context of Pakistan. This study extends the literature by examining the effect of oil prices on the sectorial stock prices of Pakistan. Moreover, it also examines the effect by using a new and robust technique called the bootstrap ARDL model. [Practical implications] Overall, the findings based on the new and robust technique can be useful for making investment or policy decisions. Policymakers are advised to follow the guidelines to make relevant decisions.
Suggested Citation
Raheel Gohar & Kashif Bhatty & Mohamed Osman & Wing-Keung Wong & Bisharat Hussain Chang, 2022.
"Oil prices and sectorial stock indices of Pakistan: Empirical evidence using bootstrap ARDL model,"
Advances in Decision Sciences, Asia University, Taiwan, vol. 26(4), pages 50-77, December.
Handle:
RePEc:aag:wpaper:v:26:y:2022:i:4:p:50-77
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