Research on RMB Exchange Rate Volatility Risk Based on MSGARCH-VaR Model
Joint Authors
Wu, Xiaofei
Zhu, Shuzhen
Zhou, Junjie
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-01
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Wu, Xiaofei& Zhu, Shuzhen& Zhou, Junjie. 2020. Research on RMB Exchange Rate Volatility Risk Based on MSGARCH-VaR Model. Discrete Dynamics in Nature and Society،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1153526
Modern Language Association (MLA)
Wu, Xiaofei…[et al.]. Research on RMB Exchange Rate Volatility Risk Based on MSGARCH-VaR Model. Discrete Dynamics in Nature and Society No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1153526
American Medical Association (AMA)
Wu, Xiaofei& Zhu, Shuzhen& Zhou, Junjie. Research on RMB Exchange Rate Volatility Risk Based on MSGARCH-VaR Model. Discrete Dynamics in Nature and Society. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1153526
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1153526