This thesis aimed to identify the approaches with the most academic impact and to explain them in greater detail. Hence, models of each category were chosen and compared. The non-parametric models were represented by the historical simulation, the parametric models by GARCH-type models (GARCH, RiskMetrics, IGARCH, FIGARCH, GJR, APARCH and EGARCH) and the semi-parametric models by the Monte Carlo simulation. The functional principle of each approach was explained, compared and contrasted.
Test for conditional and unconditional coverage were then applied to these models and revealed that models accounting for asymmetry and long memory predicted value-at-risk with sufficient accuracy. Basis for this were daily returns of the German CDAX from 2003 to 2013. Author keywords: Value-at-risk, GARCH, historical simulation, Monte Carlo simulation, unconditional coverage, conditional coverage