Purpose A financial crisis is frequently a major concern in many nations, and its negative impact on the economies of South Asian Association for Regional Cooperation (SAARC) nations is substantial. To foresee the effects of such a crisis, a prompt detection technique is required to identify the early signs of a financial crisis. Design/methodology/approach This study, therefore, employed the nominal exchange rate as an indicator to detect crisis signals in SAARC nations. The Markov-switching GARCH model is used to analyze volatility clustering in order to determine whether the SAARC countries are experiencing a financial crisis based on the Nominal Exchange Rate indicator. Findings The results indicate that an MSGARCH(1,1,1) model is suitable for Bangladesh in detecting financial crises. Similarly, an MSGARCH(2,1,1) model is ideal for India, Sri Lanka, Nepal and Bhutan, whereas an MSGARCH(3,1,1) model is more appropriate for Pakistan. According to the volatility prediction model results, in Bangladesh, India, Nepal and Bhutan, there was no imminent crisis detected. However, Pakistan was predicted to face a significant crisis in the coming year. Research limitations/implications Multi-indicators should be used by future researchers to increase the accuracy and scope of crisis identification. Practical implications Addressing these research recommendations allows policymakers and governments to implement changes that enhance financial stability. Originality/value The findings of this study provide a wide range of new information on identifying financial crises in SAARC nations, which could significantly impact the long-term viability of individual monetary systems and the larger regional economy.
Das et al. (Wed,) studied this question.