Munich Personal RePEc Archive

Buffered autoregressive models with conditional heteroscedasticity: An application to exchange rates

Zhu, Ke and Li, Wai Keung and Yu, Philip L.H. (2014): Buffered autoregressive models with conditional heteroscedasticity: An application to exchange rates.

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Abstract

This paper introduces a new model called the buffered autoregressive model with generalized autoregressive conditional heteroskedasticity (BAR-GARCH). The proposed model, as an extension of the BAR model in Li et al. (2013), can capture the buffering phenomenon of time series in both conditional mean and conditional variance. Thus, it provides us a new way to study the nonlinearity of a time series. Compared with the existing AR-GARCH and threshold AR-GARCH models, an application to several exchange rates highlights an interesting interpretation of the buffer zone determined by the fitted BAR-GARCH models.

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