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

fYear

2011

fDate

17-18 Oct. 2011

Firstpage

82

Lastpage

85

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Business Intelligence and Financial Engineering (BIFE), 2011 Fourth International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4577-1541-9

Type

conf

DOI

10.1109/BIFE.2011.9

Filename

6121093