Abstract
ABSTRACTFinancial 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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Communications in Statistics: Case Studies, Data Analysis and Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
