Smooth Transition GARCH Models in Forecasting Non-Linear Economic Time Series Data

Abstract

The need to capture the heterogeneous and volatility nature of both financial and economic time series theory and modeling their behavior in practical work have stimulated interest in the empirical modeling of variances which forms the basis for this study. In the study we augmented GARCH models with smooth transition model by dropping the assumption of autoregression of the model; necessary theoretical frame work was derived and properties of the new model established and illustrated with foreign exchange rate data from Federal Republic of Nigeria (Naira), Great Britain (Pound), Botswana (Pula) and Japanese (Yen) against United States of America (Dollar). The smooth transition GARCH model is better than the classical GARCH model as there were reduction in the variances of the augmented model; this claim is confirmed by the empirical illustration with foreign exchange data. Within the group of smooth transition GARCH model, Logistic Smooth Transition is adjudged the best as it produced the least variance.