Globalization and Economic Growth: A Case Study in A Few Developing Countries (1981-2022)

This study makes significant contributions in the following key aspects: First, the study examines the dynamics of herding behavior within the cryptocurrency market, particularly during the Ukraine-Russia conflict and the COVID-19 pandemic. Second, in this article we employ static, and the Generalized Autoregressive Conditional Heteroskedasticity model (GARCH), specifically a GARCH (1,1), for the Temporal Segmentation estimation to uncovers distinct patterns of anti-herding and herding phenomena across specific time periods. Third, methodologically, this study contributes by employing Temporal Segmentation analysis, utilizing CSAD static and CSAD with the GARCH Model. This approach provides a comprehensive understanding of herding behavior in the cryptocurrency market, allowing for a more granular exploration of distinct temporal segments. These findings extend practical implications for portfolio management and risk mitigation, enriching the landscape of behavioral finance. The study's revelations also offer valuable guidance for investors and policymakers, shedding light on market behavior during critical geopolitical and global crisis situations. In essence, this research enhances our comprehension of cryptocurrency market dynamics in the face of unique challenges, contributing to the broader understanding of behavioral patterns in the financial realm.