“…(Manera et al, 2013) the study served the return volatility of selected commodity as financial assets i.e., gold, potato, Mentha oil and crude oil traded under MCX (multi commodity exchange), India covering the period from 2004 to 2012 by using GARCH Model. (Mukherjee and Goswami, 2017) investigated the prediction capability of GARCH, GJR-GARCH, EGARCH and APARCH models together with the different error constructs like Student's t-distribution, normal distribution and asymmetric Student's t-distribution with a comparison between asymmetric and symmetric distributions using these three different error constructs by taking two major indices of Tel-Aviv stock exchange (TASE) i.e., TA25 and TA100. The results suggest that overall estimation can be improved by employing the asymmetric GARCH model with fat-tailed densities for estimating conditional variance (Alberg et al, 2008).…”