Journal
HYDROLOGICAL PROCESSES
Volume 27, Issue 22, Pages 3174-3191Publisher
WILEY-BLACKWELL
DOI: 10.1002/hyp.9452
Keywords
nonlinear time series; heteroscedasticity; GARCH; Engle's test; SARIMA model; seasonality; Box-Cox transformation
Categories
Funding
- Natural Sciences and Engineering Research Council (NSERC) of Canada
- Canada Research Chair (CRC) Program
Ask authors/readers for more resources
The existence of time-dependent variance or conditional variance, commonly called heteroscedasticity, in hydrologic time series has not been thoroughly investigated. This paper deals with modelling the heteroscedasticity in the residuals of the seasonal autoregressive integrated moving average (SARIMA) model using a generalized autoregressive conditional heteroscedasticity (GARCH) model. The model is applied to two monthly rainfall time series from humid and arid regions. The effect of Box-Cox transformation and seasonal differencing on the remaining seasonal heteroscedasticity in the residuals of the SARIMA model is also investigated. It is shown that the seasonal heteroscedasticity in the residuals of the SARIMA model can be removed using Box-Cox transformation along with seasonal differencing for the humid region rainfall. On the other hand, transformation and seasonal differencing could not remove heteroscedasticity from the residuals of the SARIMA model fitted to rainfall data in the arid region. Therefore, the GARCH modelling approach is necessary to capture the heteroscedasticity remaining in the residuals of a SARIMA model. However, the evaluation criteria do not necessarily show that the GARCH model improves the performance of the SARIMA model. Copyright (c) 2012 John Wiley & Sons, Ltd.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available