Title
Impact of Oil Prices on Islamic Stock Prices: Evidence from Pakistan using Bootstrap ARDL Approach
Authors
Abstract
Purpose: This research inspects the dynamic association between the oil prices and Islamic stock prices in Pakistan, an area relatively uninvestigated, regardless of the rising significance of Islamic finance.
Design/methodology/approach: The research utilizes daily data from January 2011 to April 2022. The SOR unit root assessment is employed to recognize smooth and sharp structural breaks, and the Bootstrap ARDL technique is employed to explore short- and long-run cointegration between oil prices and Islamic stock prices.
Findings: The findings divulge that certain Islamic stocks show substantial long-run cointegration with the oil prices, whereas others illustrate short-run causal associations. The outcomes highlight the non-linear and time-varying effect of the oil price fluxes on the dynamics of the Islamic stock market.
Research limitations/implications: The assessment is restricted to thirty Islamic stocks in Pakistan and does not include sectoral or regional heterogeneity, signifying a need for comprehensive future investigation.
Practical implications: The outcomes deliver valuable information for investors and policymakers by featuring the prominence of monitoring the dynamics of the oil market when articulating risk management and investment approaches in Islamic financial markets.
Originality/value: This research contributes to the inadequate empirical literature by employing innovative econometric procedures to assess the oil-Islamic stock price association in a developing market, delivering vigorous evidence that augments and complements the current study.
Keywords
Islamic Stock Prices, Oil prices, Bootstrap ARDL, SOR unit root, Pakistan
Classification-JEL
C32, G12, G15, Q43
Pages
1-35
How to Cite
Bhatty, K. A., Laurinavicius, A., Laurinavicius, A., Chang, B. H., ALZOUBI, H. M., & Channa, W. A. (2025). Impact of Oil Prices on Islamic Stock Prices: Evidence from Pakistan using Bootstrap ARDL Approach. Advances in Decision Sciences, 29(2), 1-35.