On the flexibility of GARCH-family models with an application to the BRICS stock indices

Financial asset returns are known to exhibit fatter tails with substantial skewness and high kurtosis due to volatility. In this article, the dynamics of implied volatility of BRICS indices are described using 10 GARCH-type models. The innovation processes of these GARCH models are characterized using 13 parametric distributions, including these 4 uncommon, flexible ones: Student's t-gamma mixture, normal-gamma mixture, asymmetric exponential power, and generalized asymmetric student's t distributions. The performance and predictive ability of these GARCH models are evaluated in terms of value at risk and expected shortfall with some loss functions. The EST-GARCH with error distribution based on the asymmetric exponential power distribution gives the best fit.