This study examines the dynamics of stock market performance, with a focus on geopolitical risk.
We employ quantile regression and NARDL to investigate asymmetric relationships between geopolitical risk, market volatility, commodity prices, currency exchange rates, and Borsa Istanbul (BIST) in 2009–2023.
The quantile regression analysis shows that geopolitical risk and gold prices have no significant impact across any market conditions, while the volatility index has a significant negative impact, particularly in bull markets. Brent crude oil prices positively influence BIST significantly in bear markets, and the USD significantly depresses BIST in bear markets but not in bull markets. The NARDL model results reveal that positive changes in gold prices initially negatively impact BIST before turning positive, while negative changes significantly boost the index; similarly, the USD exchange rate shows significant positive impacts from both lagged positive and negative changes.
This study is limited by its focus on specific geopolitical events, which may overlook other relevant risks. Data constraints, including reliance on historical data, may not fully capture recent geopolitical developments. The NARDL model's assumptions may not account for all dynamic relationships, affecting the accuracy of the results. Additionally, external factors such as global economic conditions may influence BIST but were not fully controlled for in this study. The focus on short- and long-term effects may not adequately address medium-term dynamics, potentially leading to an incomplete understanding of the impacts of geopolitical risks.
This study has significant policy implications. It is recommended to encourage investors to diversify their holdings among different asset classes. According to the study, this strategy will help manage risks associated with geopolitical tensions. A diversified investment approach can offer superior defense against geopolitical event-driven market volatility.
By analyzing geopolitical risk alongside other variables, this study uniquely assesses the drivers influencing stock market movements. This study takes a novel approach by examining asymmetric effects with quantile regression and NARDL.
