Understanding the characteristics of the dynamic relationship between the onshore Ren- minbi （CNY） and the offshore Renminbi （CNH） exchange rates considering the impact of some extreme events is very important and...Understanding the characteristics of the dynamic relationship between the onshore Ren- minbi （CNY） and the offshore Renminbi （CNH） exchange rates considering the impact of some extreme events is very important and it has wide implications in several areas such as hedging. For better esti- mating the dynamic relationship between CNY and CNH, the Granger-causality test and Bry-Boschan Business Cycle Dating Algorithm were employed in this paper. Due to the intrinsic complexity of the lead-lag relationships between CNY and CNH, the empirical mode decomposition （EMD） algorithm is used to decompose those time series data into several intrinsic mode function （IMF） components and a residual sequence, from high to low frequency. Based on the frequencies, the IMFs and a residual sequence are combined into three components, identified as short-term composition caused by some market activities, medium-term composition caused by some extreme events and the long-term trend.The empirical results indicate that when it only matters the short-term market activities, CNH always leads CNY; while the medium-term impact caused by those extreme events may alternate the lead-lag relationships between CNY and CNH.展开更多
基金partially supported by the National Natural Science Foundation of China under Grant Nos.71390330,71390331,71390335the National Nature Science Foundation of China for financial support to this study+1 种基金supported by the Postdoctorate Programme of Centre University of Economics and Financethe Postodctorate Programme of China Great Wall Asset Management Corporation
文摘Understanding the characteristics of the dynamic relationship between the onshore Ren- minbi （CNY） and the offshore Renminbi （CNH） exchange rates considering the impact of some extreme events is very important and it has wide implications in several areas such as hedging. For better esti- mating the dynamic relationship between CNY and CNH, the Granger-causality test and Bry-Boschan Business Cycle Dating Algorithm were employed in this paper. Due to the intrinsic complexity of the lead-lag relationships between CNY and CNH, the empirical mode decomposition （EMD） algorithm is used to decompose those time series data into several intrinsic mode function （IMF） components and a residual sequence, from high to low frequency. Based on the frequencies, the IMFs and a residual sequence are combined into three components, identified as short-term composition caused by some market activities, medium-term composition caused by some extreme events and the long-term trend.The empirical results indicate that when it only matters the short-term market activities, CNH always leads CNY; while the medium-term impact caused by those extreme events may alternate the lead-lag relationships between CNY and CNH.
