Pierre Serti: Forecasting the financial volatility of LVMH, Louis Vuitton Moët Hennessy

This paper examines the performance abilities of forecasting and modeling the financial volatility of the daily stock returns of LVMUY, belonging to Louis Vuitton Moët Hennessy. The volatility is modeled by the GARCH model and further extended into the EGARCH and the GJR-GARCH models under two distributional assumptions for the error term, i.e Gaussian distribution and Student-t distribution. We compare the performance in forecasting the volatility among the GARCH family models by calculating the AIC and the Loglikelihood for each model. The results shows that the EGARCH model with the Student-t distribution is the best model in forecasting the financial volatility. Despite the limitations of the GARCH model in comparison to the EGARCH model, the symmetric GARCH model stil provide adequate results in forecasting purposes.