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Comparative Analysis of forecasting exchange rate using ARCH and GARCH Models: A Case Study of China

In: Proceedings of the 9th International Conference on Financial Innovation and Economic Development (ICFIED 2024)

Author

Listed:
  • Qiqi Zhang

    (University of Birmingham, College of Engineering and Physical Science)

  • Jianing Pan

    (School of Ningbo Foreign Language)

  • Jiahao Geng

    (School of Shanghai United International)

  • Xun Zhu

    (School of Meihua)

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.

Suggested Citation

  • Qiqi Zhang & Jianing Pan & Jiahao Geng & Xun Zhu, 2024. "Comparative Analysis of forecasting exchange rate using ARCH and GARCH Models: A Case Study of China," Advances in Economics, Business and Management Research, in: Khaled Elbagory & Zefu Wu & Hamdan Amer Ali Al-Jaifi & Shafie Mohamed Zabri (ed.), Proceedings of the 9th International Conference on Financial Innovation and Economic Development (ICFIED 2024), pages 618-625, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-408-2_69
    DOI: 10.2991/978-94-6463-408-2_69
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