Linear vs Non-Linear Volatility Models (Comparative Analysis of Eagle vs Nest Markets)

This study investigates the performance of linear versus nonlinear methods to predict volatility and effects of asymmetric pattern on the emerging markets of Asia from EAGLEs and NEST Daily data of stock market returns is taken for the period 4 January 2000 to 30 May 2017. Nonlinear and asymmetric ARCH effects have been observed from the estimations. A range of model from random walk model to multifaceted ARCH class models are used to predict volatility. The results reveal that MA (1) model ranks first with use of RMSE criterion in linear models. For nonlinear models, the ARCH, GARCH(1, 1) model and EGARCH (1, 1) model perform well. GARCH (1,1) model outperforms on the basis of AIC, SIC and Log Likelihood method