Volatility Forecasting and Effects of Asymmetric Patterns in Emerging Markets of Asia

Abstract

This study investigates the performance of linear versus nonlinear methods to predict volatility and effects of asymmetric pattern on the emerging markets of Asia i.e.; China, India, Indonesia Pakistan, Bangladesh and Malaysia. Daily data of stock market returns is taken for the period January 2000 to December 2010. 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.