Notice of Retraction: An empirical study on the effects of rmb exchange rate volatility on China's exports

2011 ◽  
Author(s):  
Li Shen ◽  
Liping Xu
Keyword(s):  
Exchange Rate ◽  
Empirical Study ◽  
Exchange Rate Volatility ◽  
Rmb Exchange Rate

scholarly journals Research on RMB Exchange Rate Volatility Risk Based on MSGARCH-VaR Model

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Xiaofei Wu ◽  
Shuzhen Zhu ◽  
Junjie Zhou
Keyword(s):  
Exchange Rate ◽  
Value At Risk ◽  
Financial Risk ◽  
Deviance Information Criterion ◽  
Exchange Rate Volatility ◽  
Information Criterion ◽  
Model Parameters ◽  
Volatility Risk ◽  
Rmb Exchange Rate ◽  
Trade Friction

This paper captures the RMB exchange rate volatility using the Markov-switching GARCH (MSGARCH) models and traditional single-regime GARCH models. Through the Markov Chain Monte Carlo (MCMC) method, the model parameters are estimated to study the volatility dynamics of the RMB exchange rate. Furthermore, we compare the MSGARCH models to the single-regime GARCH specifications in terms of Value-at-Risk (VaR) prediction accuracy. According to the Deviance information criterion method, the research shows that MSGARCH models outperform the single-regime specifications in capturing the complexity of RMB exchange rate volatility. After the RMB exchange rate reform in 2015, the volatility is more asymmetric and persistent, and the probability of being in the turbulent volatility regime is significantly increased. The continuous escalation of Sino-US trade friction has increased the VaR of RMB exchange rate log-returns. From the evaluation results of the actual over expected exceedance ratio (AE), the conditional coverage (CC) test, and the dynamic quantile (DQ) test, we find strong evidence that two-regime MSGARCH models could forecast VaR more accurately, which provides practical value for China’s foreign exchange management authorities to manage the financial risk.

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