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Smooth Transition Autoregressive-GARCH Model in Forecasting Non-linear Economic Time Series Data

机译:平稳过渡自回归-GARCH模型在预测非线性经济时间序列数据中的应用

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The regime switching models are particularly popular in the comity of non-linear models; it is of interest to investigate regime switching models with GARCH specification. GARCH model was augmented with STAR model vis-a vis Exponential autoregressive GARCH (EAR-GARCH), Exponential smooth transition autoregressive GARCH (ESTAR- GARCH) model and Logistic smooth transition autoregressive GARCH (LSTAR-GARCH) model. The properties of the new models were derived and compared with conventional GARCH model which shows that the variance obtained for STAR-GARCH model was minimum compared to classical GARCH model, the new methodology proposed is illustrated with foreign exchange rate data from Great Britain (Pound) and Botswana (Pula) against United States of America (Dollar). It is evident that all STAR-GARCH outperformed the classical GARCH model, however, LSTAR-GARCH performed best and closely followed by ESTAR-GARCH, this is followed by EAR-GARCH. The implication is that the use of LSTAR –GARCH produces the best resu however LSTAR may be utilized in some occasions.
机译:在非线性模型的流行中,状态切换模型尤其流行。研究具有GARCH规范的状态切换模型非常有趣。相对于指数自回归GARCH(EAR-GARCH),指数平滑过渡自回归GARCH(ESTAR-GARCH)模型和Logistic平滑过渡自回归GARCH(LSTAR-GARCH)模型,STAR模型增强了GARCH模型。推导了新模型的特性,并与常规GARCH模型进行了比较,结果表明,与传统GARCH模型相比,STAR-GARCH模型获得的方差最小,并用来自英国的英镑汇率数据说明了该新方法。博茨瓦纳(普拉)对美利坚合众国(美元)。显然,所有STAR-GARCH的性能都优于经典GARCH模型,但是LSTAR-GARCH的表现最佳,紧随其后的是ESTAR-GARCH,其次是EAR-GARCH。这意味着使用LSTAR –GARCH可以产生最佳结果。但是LSTAR可能会在某些情况下使用。

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