This paper examines the performance of different kind of GARCH models with Gaussian, Student-t and generalized error distribution for Colombo Stock Exchange (CSE), in Sri Lanka. Analyzing the daily closing price index of CSE from January 02, 2007 to March 10, 2013. It was found that the Asymmetric GARCH models give better result than symmetric GARCH model. According to distributional assumption these models under Student-t as well as generalized error provided better fit than normal distributional assumption. The Non-Parametric Specification test suggest that the GARCH, EGARCH, TARCH and APARCH models with Student-t distributional assumption are the most successful model for CSE.
Abstract: In this paper, we use generalized influence function and generalized Cook distance to measure the local influence of minor perturbation on the modified ridge regression estimator in ridge type linear regression model. The diagnostics under the perturbation of constant variance and individual explanatory variables are obtained when multicollinearity presents among the regressors. Also we proposed a statistic that reveals the influential cases for Mallow’s method which is used to choose modified ridge regression estimator biasing parameter. Two real data sets are used to illustrate our methodologies.