An empirical characterization of volatility dynamics in the DAX

This paper addresses stock market volatility in Germany between 1991 and 2018. Through a GARCH model with leverage term, an estimation of volatility in the DAX is provided. Such estimation is then plugged into a quantile regression model where potential economic determinants are analyzed. The results suggest that stock market volatility in Germany reached its historical peak between 2000 and 2004. Moreover, animal spirits play an important role across different quantiles of the volatility distribution, whereas the relevance of established risk factors proposed in the literature is limited to specific cases. Overall, the findings stress the importance of appropriate distributional assumptions when analyzing extreme financial events.