Shivam Sehgal | Jaspal Singh
pages: 42-57; JEL classification: G01, G15; Keywords: Bitcoin, Indian Financial Markets, MODWT, Wavelet Analysis, COVID-19; Abstract: This study employs the Maximal Overlap Discrete Wavelet Transform technique to analyze the wavelet-based correlations between Bitcoin, bond markets, and thirteen sectoral stock indices in India over the period from 2017 to 2023, focusing on the comparison of pre-and post-COVID-19 pandemic effects. The aim is to investigate the dynamic interrelationships and to understand the impact of the COVID-19 pandemic on these financial assets. The study period is divided into preCOVID-19 and post-COVID-19. Findings from the study reveal a minimal negative correlation between Bitcoin, bond markets, and the sectoral stock indices in the pre-COVID era, indicating a lack of significant interdependence among these assets. However, the scenario changes markedly in the post-COVID period, shifting towards a positive correlation. This shift suggests that the COVID-19 pandemic has altered the relationship dynamics, leading to a more interconnected financial environment where movements in Bitcoin have begun to show a significant positive correlation with the movements in bond and sectoral stock indices in India. The study contributes to the existing literature by providing empirical evidence of how external shocks, such as the COVID-19 pandemic, can influence the correlation patterns among different financial assets. It highlights the importance of considering the changing dynamics in financial market correlations for investors, policymakers, and researchers in portfolio diversification, risk management, and financial stability analysis. Further, it underscores the role of alternative investments like Bitcoin in the evolving market landscape, particularly in response to global crises.