Heteroskedastic behaviour of stock prices: Evidence from international financial markets

Traditional financial models assume constant variance in asset returns however, empirical evidence highlights volatility persistence, which are effectively captured by ARCH and GARCH models. The aim of this study was to examine the heteroskedastic behaviour of stock prices across international financial markets. Using a GARCH (1,1) model with a student’s t-distribution, this study analyses daily stock returns from the NYSE, FTSE 100, Nikkei 225, and Shanghai Composite (SSE) between 2018 and 2023. The findings confirm significant autoregressive conditional heteroskedasticity in all markets, supporting the notion that financial volatility is dynamic and clustered. Developed markets, such as the NYSE and FTSE 100, exhibit lower baseline volatility but more persistent shocks, indicative of market efficiency and stability. In contrast, emerging markets, particularly SSE, demonstrate higher volatility and greater sensitivity to past shocks, reflecting heightened uncertainty. The results re-iterate the importance of incorporating dynamic volatility models in risk assessments. Given the increasing complexity of global financial systems, this study advocates for enhanced regulatory frameworks and adaptive econometric methodologies to account for evolving market structures and external macroeconomic shocks. Key Words:Heteroskedasticity, Volatility Clustering, GARCH, Stock Markets, Financial