Empirical Study on Volatility of RMB against US Dollar Based on ARCH Family Model
- DOI
- 10.2991/icemaess-18.2018.44How to use a DOI?
- Keywords
- RMB Exchange Rate, Volatility, ARCH Family Model, Heteroscedasticity Test
- Abstract
Based on the daily data of the central parity of the RMB against the US dollar from August 2015 to March 2017, this paper uses the ARCH model as the main research tool and through corresponding tests to establish the ARCH model of the yield rate of the exchange rate of RMB against the US dollar, thereby studying its volatility. The empirical analysis shows that the fluctuation of the RMB exchange rate does not obey the normal distribution, and the RMB exchange rate bears the significant characteristics of a sharp peak and a thick tail. In addition, through the establishment of the EGARCH model, this paper concludes that there is a certain leverage effect on the yield rate of the exchange rate of RMB against the US dollar, that is, the impact of bull news on the RMB exchange rate will be greater than the bear news. At the same time, this paper also finds that the relationship between the yield rate of the exchange rate of RMB against the US dollar and its lagging terms is not significant, which shows that the exchange rate of RMB against the US dollar is not only effective for the market, but also has a certain degree for the effectiveness of China’s exchange rate reform.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yudong Wu PY - 2018/11 DA - 2018/11 TI - Empirical Study on Volatility of RMB against US Dollar Based on ARCH Family Model BT - Proceedings of the 2018 5th International Conference on Education, Management, Arts, Economics and Social Science (ICEMAESS 2018) PB - Atlantis Press SP - 210 EP - 214 SN - 2352-5398 UR - https://doi.org/10.2991/icemaess-18.2018.44 DO - 10.2991/icemaess-18.2018.44 ID - Wu2018/11 ER -