Comparative Analysis of forecasting exchange rate using ARCH and GARCH Models: A Case Study of China
Authors
Qiqi Zhang1, *, Jianing Pan2, Jiahao Geng3, Xun Zhu4
1College of Engineering and Physical Science, University of Birmingham, Birmingham, B15 2TT, UK
2School of Ningbo Foreign Language, Ningbo, 315121, China
3School of Shanghai United International, Shanghai, 200124, China
4School of Meihua, Jiangsu, 215311, China
*Corresponding author.
Email: qxz330@student.bham.ac.uk
Corresponding Author
Qiqi Zhang
Available Online 7 May 2024.
- DOI
- 10.2991/978-94-6463-408-2_69How to use a DOI?
- Keywords
- GARCH Model; ARCH Model; China; exchange rate
- Abstract
This paper is focused on two different models, which are the Auto-Regressive Conditional Heteroskedasticity Model (ARCH) and the Generalized Autoregressive Conditional Heteroskedasticity model (GARCH). Furthermore, first, this work will explain what the ARCH Model is and what the GARCH Model is. Secondly, comparing the ARCH Model to the GARCH Model to show which key benefits can help people forecast the exchange rate. After that based on some cases in China to illustrate how these two models work. Then proving the GARCH Model is more useful than the ARCH model when the GARCH Model connects with another model.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Qiqi Zhang AU - Jianing Pan AU - Jiahao Geng AU - Xun Zhu PY - 2024 DA - 2024/05/07 TI - Comparative Analysis of forecasting exchange rate using ARCH and GARCH Models: A Case Study of China BT - Proceedings of the 9th International Conference on Financial Innovation and Economic Development (ICFIED 2024) PB - Atlantis Press SP - 618 EP - 625 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-408-2_69 DO - 10.2991/978-94-6463-408-2_69 ID - Zhang2024 ER -