Title :
A Study of the USDX Predication Based on ARIMA and GARCH Models
Author :
Liu, Zhiwei ; Lv, Ya
Author_Institution :
Sch. of Econ. & Manage., Univ. of Sci. & Technol. Beijing, Beijing, China
Abstract :
In order to predict and describe the volatility of the U.S. dollar index, the ARIMA and GARCH models are used to study the U.S. dollar index respectively. After establishing two time series models, we find that there are differences in predicting future trends of the U.S. dollar index between two models. The results show that ARIMA model is a proper short-term forecasting method. It is effective when predicting for a month. The GARCH model is a proper method for forecasting the U.S. dollar index for a longer term, and the satisfactory results of the longer-term forecast are obtained.
Keywords :
autoregressive moving average processes; forecasting theory; foreign exchange trading; ARIMA model; GARCH model; USDX predication; United States dollar index; autoregressive integrated moving average model; generalised autoregressive conditional heteroskedasticity model; long-term forecasting; short-term forecasting method; Autoregressive processes; Biological system modeling; Correlation; Exchange rates; Indexes; Predictive models; Time series analysis; ARIMA; Forecast; GARCH; US Dollar Index;
Conference_Titel :
Business Intelligence and Financial Engineering (BIFE), 2011 Fourth International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4577-1541-9
DOI :
10.1109/BIFE.2011.9
