Regime Switching GARCH Models and GARCH Models, in Stock Market of the Developing Countries'

Abstract

This study is fore comparing GARCH models and Markov switching GARCH models in their ability to estimate and forecasting the volatility of Tehran stock market in some horizon of forecasting. This paper provides an analysis of regime switching in volatility and out-of-sample forecasting of the IRAN using daily data for the period 1995-2011. We first model volatility regime switching within a univariate Markov-Switching framework. Then We provide out-of-sample forecasts of the TEHRAN daily returns using two competing non-linear models, the GARCH Markov Switching model and the uniregime GARCH Model. The comparison of the out-of-sample forecasts is done on the basis of forecast accuracy, using the 7statistical loss function. The results, also, shows that SW-GARCH models can remove the high persistence of GARCH models and separately in each regime of volatility, the persistence are high. This shows the priority of SW-GARCH models. Another implication is that there is evidence of regime clustering.