Forecasting Volatility in the Eurozone: (GJR)-(E)GARCH Approach

This study aims to model and forecast volatility in Eurozone returns using generalised conditional heteroskedasticity (GARCH)-type models that capture volatility clustering, asymmetry and leverage effects. The application of GARCH-type models to forecast volatility in the Eurozone remains underexplored, even as recent geopolitical tensions signal heightened volatility. For this purpose, the Euro Stoxx 50 has been selected as a representative of the Eurozone equity market, comprising blue-chip companies considered leaders in their respective sectors. To model volatility, three GARCH-type models were selected: GARCH(1,1), exponential GARCH (EGARCH)(1,1) and GJR-GARCH(1,1). The results of the GARCH(1,1) model showed that current volatility is strongly influenced by past shocks and volatility. Moreover, volatility is highly persistent, suggesting that shocks have long-lasting effects. The EGARCH(1,1) results revealed evidence of asymmetry, indicating that negative shocks influence volatility differently than positive shocks of equal size. The results of the GJR-GARCH(1,1) model indicated that negative shocks increase volatility more than positive shocks of the same magnitude. In other words, the leverage effect was found. Among the three models, EGARCH achieves the lowest values across all criteria, demonstrating greater forecasting ability than the other two models. The current outcomes are vital for understanding the contributions of different GARCH models to volatility management and the recent situation in the Eurozone equity market, providing valuable insights for investors, policymakers and risk managers and helping them design more effective portfolio and hedging strategies, especially during financial shocks and uncertainty.