Research on the Volatility Forecast of RMB/USD Exchange Rate Based on GARCH Model

Siying Tao

doi:10.47297/wspceWSP2516-251914.20261002

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Research on the Volatility Forecast of RMB/USD Exchange Rate Based on GARCH Model

10卷第2期

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Research on the Volatility Forecast of RMB/USD Exchange Rate Based on GARCH Model
Research on the Volatility Forecast of RMB/USD Exchange Rate Based on GARCH Model
Jinshen College, Nanjing Audit University, Nanjing, Jiangsu, 210000, China
2026年10卷第2期页码：65-72
纸质出版：2026-04-30
DOI：10.47297/wspceWSP2516-251914.20261002
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Siying Tao. (2026). Research on the Volatility Forecast of RMB/USD Exchange Rate Based on GARCH Model. 创意经济（英文版）, 10(2), 65-72.

Tao Siying.Research on the Volatility Forecast of RMB/USD Exchange Rate Based on GARCH Model[J].Creative Economy,2026,10(02):65-72.
Siying Tao. (2026). Research on the Volatility Forecast of RMB/USD Exchange Rate Based on GARCH Model. 创意经济（英文版）, 10(2), 65-72. DOI： 10.47297/wspceWSP2516-251914.20261002.

Tao Siying.Research on the Volatility Forecast of RMB/USD Exchange Rate Based on GARCH Model[J].Creative Economy,2026,10(02):65-72. DOI： 10.47297/wspceWSP2516-251914.20261002.

摘要

Abstract

With more and more countries cooperating together in economic globalisation

we must continue researching their impacts on the formulation of national policies or corporate risk responses continually.This study examines the daily RMB/USD exchange rate data from the 2015 August 11th exchange rate reform to 2025. Using ADF and ARCH-LM tests

we analyze the exchange rate yield series for stationarity and heteroskedasticity

and construct three volatility models: GARCH(1

EGARCH(1

and GJR-GARCH(1

1). Maximum-likelihood estimation is utilized to obtain precise parameters for the respective models.Addressing the severe volatility clustering of the RMB/USD exchange rate with the GJR-GARCH(1

1) model is most appropriate. It will be able to detect asymmetric variations and have good performance when in practice. While the standard GARCH(1

1) model

despite its structural simplicity

maintains stable forecasting performance

the EGARCH(1

1) model shows relatively weaker predictive efficacy during periods of severe market volatility.

关键词

Keywords

references

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