Stock indices, fundamental gauges of economic strength, come under meticulous scrutiny in this research. The emphasis is placed on examining causality, analyses of the flow of information, within these crucial indicators of economic vitality. Employing the non-parametric transfer entropy method, we explore the cause-effect relationships and information dynamics within stock indices over five-year periods, three-year intervals, and the unprecedented context of the COVID-19 pandemic. The study centers on the NIFTY 50, a pivotal index in the Indian market, alongside major global indices such as S&P 500, SGX Nifty, NASDAQ, SSE Composite Index (Shanghai), DAX, and DOW Jones. Key findings reveal the consistent leadership of DOW Jones and bidirectional information flows across all index pairs during specific time frames. Notably, the research highlights the significance of the SGX Nifty and the influential role of the NASDAQ Composite Index on the Indian IT sector. This work contributes to scholarly discourse, providing strategic insights for investors navigating global financial markets, particularly during periods of economic uncertainty. The findings inform decision-making and strategic planning in the dynamic landscape of international financial markets.