Semi-parametric forecasting model for USD/CNY exchange rate
CAI Zong-wu1,2,3,4, CHEN Lin-na2, FANG Ying2,3,4
1. Department of Mathematics & Statistics, University of North Carolina at Charlotte, Charlotte, NC 28223, USA; 2. Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen 361005, China; 3. China Ministry of Education (MOE Key Laboratory of Econometrics at Xiamen University, Xiamen 361005, China; 4. Fujian Key Laboratory of Statistical Science, Xiamen University, Xiamen 361005, China
Abstract：Using the daily USD/CNY exchange rate time series data from January 4th, 2006 to July 18th, 2008, this paper proposes a semi-parametric approach to model the conditional mean and conditional volatility simultaneously. A nonparametric functional-coefficient model is employed to estimate the conditional mean, and a GARCH-type model with a policy change dummy is adopted to describe the dynamics of the conditional volatility. Moreover, the corresponding policies play a significant role on both mean and volatility. Finally, a nonparametric quantile regression estimation is applied to compute prediction intervals. The empirical results demonstrate that the proposed semi-parametric model has good performance in terms of in-sample goodness of fit and out-of-sample forecasts.
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2012, Vol. 32 
