Exploring Volatility clustering financial markets and its implication

Abstract

Volatility clustering is a prominent feature of financial markets exhibiting persistent fluctuations in volatility over time. Its characteristics such as long memory, asymmetry and varying cluster durations pose challenges for market participants although it may also present some opportunities. The aim of this study was to investigate the historical patterns and statistical properties of volatility clustering across different financial markets. This study used a GARCH and ARCH model for four stock markets from June 14, 2018 to June 14, 2023. The findings revealed the presence of volatility clustering in line with prior study. These clustering which may be due to the recent episodes in financial markets such as the covid-19 poses significant risk for traders and active market participants. Hence, regulatory authorities need to implement measures to enhance market resilience, sufficient liquidity and regulate high-frequency trading activities to mitigate systemic risk

Keywords

• volatility clustering
• garch model
• arch model
• financial markets.