This paper investigates the dependence of the exchange rate of onshore Renminbi(RMB)and offshore RMB against US dollar(i.e., CNY and CNH) based on copula models. Eleven different copulas were selected to construct mul...This paper investigates the dependence of the exchange rate of onshore Renminbi(RMB)and offshore RMB against US dollar(i.e., CNY and CNH) based on copula models. Eleven different copulas were selected to construct multivariate distribution and estimate the value-at-risk for RMB exchange rate. Empirical results show that time-invariant Student-t copula is the best model to fit the sample data. The positive upper and lower dependence indicates that CNY and CNH series tend to move in the same direction. Moreover, the dependence between the two exchange rates is asymmetric,which means that traditional models, such as Pearson's correlation, are inappropriate to measure the correlations between these markets. The best fitted model is chosen to estimate the financial risk,which can help business practitioners and policymakers track risk evolution and make good decisions.展开更多
基金supported by Strategic Research Grant of City University of Hong Kong under Grant No.7004268
文摘This paper investigates the dependence of the exchange rate of onshore Renminbi(RMB)and offshore RMB against US dollar(i.e., CNY and CNH) based on copula models. Eleven different copulas were selected to construct multivariate distribution and estimate the value-at-risk for RMB exchange rate. Empirical results show that time-invariant Student-t copula is the best model to fit the sample data. The positive upper and lower dependence indicates that CNY and CNH series tend to move in the same direction. Moreover, the dependence between the two exchange rates is asymmetric,which means that traditional models, such as Pearson's correlation, are inappropriate to measure the correlations between these markets. The best fitted model is chosen to estimate the financial risk,which can help business practitioners and policymakers track risk evolution and make good decisions.
