This study aims to examine the dynamic relationship between conventional, Islamic and ESG stock returns, and various financial, non-financial and policy-related uncertainties. Additionally, the study examines the hedging potential and interconnectedness of these indices under varying market conditions.
The study uses a novel method of quantile coherency, introduced by Baruník and Kley (2019), which facilitates in-depth analysis of the dependence structure across quantiles and frequencies. It enables the identification of co-movement patterns among stock returns and uncertainty measures in both standard and extreme market conditions. Additionally, this study uses impulse response functions and dynamic conditional correlation (DCC)-GJR-GARCH approaches for robustness.
The results indicate a positive connection between the returns of these stock indices and non-financial uncertainty, particularly in the extreme low and high quantiles over yearly periods, highlighting the effective hedging capability of different stock indices against geopolitical risks. Regarding policy-related uncertainty, the authors observe a significant positive correlation between these stock indices and economic policy uncertainty, particularly at the monthly frequency during bearish market conditions. Furthermore, most conventional, Islamic and ESG stock returns exhibit a negative correlation with financial uncertainties, indicating a lack of effectiveness in hedging against crude oil volatility and implied stock volatility. The robustness of these findings is checked by time-varying correlation (DCC-GJR-GARCH) analysis.
The results have significant implications for investors, portfolio managers, and policymakers, particularly those seeking to construct a portfolio suitable for all market conditions. This study is among the first to apply quantile coherency analysis to explore how Islamic, ESG and conventional stock markets respond to a broad spectrum of uncertainties.
