Journal
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
Volume 35, Issue 4, Pages 528-542Publisher
AMER STATISTICAL ASSOC
DOI: 10.1080/07350015.2015.1123634
Keywords
Buffered AR-GARCH model; Buffered AR model; Exchange rate; GARCH model; Nonlinear time series; Threshold AR model
Funding
- Research Grants Council of the Hong Kong SAR Government (GRF) [HKU703711P]
- National Natural Science Foundation of China [11571348, 11371354, 71532013]
- Academy of Mathematics and System Science, Chinese Academy of Sciences [2014-cjrwlzx-zk]
- Key Laboratory of RCSDS, Chinese Academy of Sciences
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This article introduces a new model called the buffered autoregressive model with generalized autoregressive conditional heteroscedasticity (BAR-GARCH). The proposed model, as an extension of the BAR model in Li et al. (2015), can capture the buffering phenomena of time series in both the conditional mean and variance. Thus, it provides us a new way to study the nonlinearity of time series. Compared with the existing AR-GARCH and threshold AR-GARCH models, an application to several exchange rates highlights the importance of the BAR-GARCH model.
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